Veterinary Research Manpower Development for Defense

DTIC Science & Technology

2007-09-01

Participatory Disease Surveillance Method for Detection of Highly Pathogenic Avian Influenza in Java, Indonesia Rebecca Steers Dr. Lindenmeyer Detection of...Transmission of Nipah Virus in Bangladesh Summary: My project aims to investigate the risk of zoonotic transmission of Nipah virus as a food-borne...Participatory Disease Surveillance Method for Detection of Highly Pathogenic Avian Influenza in Java, Indonesia Summary: Two epidemics of H5N1 Highly

A simple high performance liquid chromatography method for analyzing paraquat in soil solution samples.

PubMed

Ouyang, Ying; Mansell, Robert S; Nkedi-Kizza, Peter

2004-01-01

A high performance liquid chromatography (HPLC) method with UV detection was developed to analyze paraquat (1,1'-dimethyl-4,4'-dipyridinium dichloride) herbicide content in soil solution samples. The analytical method was compared with the liquid scintillation counting (LSC) method using 14C-paraquat. Agreement obtained between the two methods was reasonable. However, the detection limit for paraquat analysis was 0.5 mg L(-1) by the HPLC method and 0.05 mg L(-1) by the LSC method. The LSC method was, therefore, 10 times more precise than the HPLC method for solution concentrations less than 1 mg L(-1). In spite of the high detection limit, the UC (nonradioactive) HPLC method provides an inexpensive and environmentally safe means for determining paraquat concentration in soil solution compared with the 14C-LSC method.

Optical fiber sensor of partial discharges in High Voltage DC experiments

NASA Astrophysics Data System (ADS)

Búa-Núñez, I.; Azcárraga-Ramos, C. G.; Posada-Román, J. E.; Garcia-Souto, J. A.

2014-05-01

A setup simulating High Voltage DC (HVDC) transformers barriers was developed to demonstrate the effectiveness of an optical fiber (OF) sensor in detecting partial discharges (PD) under these peculiar conditions. Different PD detection techniques were compared: electrical methods, and acoustic methods. Standard piezoelectric sensors (R15i-AST) and the above mentioned OF sensors were used for acoustic detection. The OF sensor was able to detect PD acoustically with a sensitivity better than the other detection methods. The multichannel instrumentation system was tested in real HVDC conditions with the aim of analyzing the behavior of the insulation (mineral oil/pressboard).

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

PubMed Central

Sivaraks, Haemwaan

2015-01-01

Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

Detection method based on Kalman filter for high speed rail defect AE signal on wheel-rail rolling rig

NASA Astrophysics Data System (ADS)

Hao, Qiushi; Shen, Yi; Wang, Yan; Zhang, Xin

2018-01-01

Nondestructive test (NDT) of rails has been carried out intermittently in traditional approaches, which highly restricts the detection efficiency under rapid development of high speed railway nowadays. It is necessary to put forward a dynamic rail defect detection method for rail health monitoring. Acoustic emission (AE) as a practical real-time detection technology takes advantage of dynamic AE signal emitted from plastic deformation of material. Detection capacities of AE on rail defects have been verified due to its sensitivity and dynamic merits. Whereas the application under normal train service circumstance has been impeded by synchronous background noises, which are directly linked to the wheel speed. In this paper, surveys on a wheel-rail rolling rig are performed to investigate defect AE signals with varying speed. A dynamic denoising method based on Kalman filter is proposed and its detection effectiveness and flexibility are demonstrated by theory and computational results. Moreover, after comparative analysis of modelling precision at different speeds, it is predicted that the method is also applicable for high speed condition beyond experiments.

Detection of IgG aggregation by a high throughput method based on extrinsic fluorescence.

PubMed

He, Feng; Phan, Duke H; Hogan, Sabine; Bailey, Robert; Becker, Gerald W; Narhi, Linda O; Razinkov, Vladimir I

2010-06-01

The utility of extrinsic fluorescence as a tool for high throughput detection of monoclonal antibody aggregates was explored. Several IgG molecules were thermally stressed and the high molecular weight species were fractionated using size-exclusion chromatography (SEC). The isolated aggregates and monomers were studied by following the fluorescence of an extrinsic probe, SYPRO Orange. The dye displayed high sensitivity to structurally altered, aggregated IgG structures compared to the native form, which resulted in very low fluorescence in the presence of the dye. An example of the application is presented here to demonstrate the properties of this detection method. The fluorescence assay was shown to correlate with the SEC method in quantifying IgG aggregates. The fluorescent probe method appears to have potential to detect protein particles that could not be analyzed by SEC. This method may become a powerful high throughput tool to detect IgG aggregates in pharmaceutical solutions and to study other protein properties involving aggregation. It can also be used to study the kinetics of antibody particle formation, and perhaps allow identification of the species, which are the early building blocks of protein particles. (c) 2009 Wiley-Liss, Inc. and the American Pharmacists Association

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

PubMed Central

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-01-01

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE. PMID:27447635

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

PubMed

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-07-19

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated by OKTAL-SE.

Light Weight MP3 Watermarking Method for Mobile Terminals

NASA Astrophysics Data System (ADS)

Takagi, Koichi; Sakazawa, Shigeyuki; Takishima, Yasuhiro

This paper proposes a novel MP3 watermarking method which is applicable to a mobile terminal with limited computational resources. Considering that in most cases the embedded information is copyright information or metadata, which should be extracted before playing back audio contents, the watermark detection process should be executed at high speed. However, when conventional methods are used with a mobile terminal, it takes a considerable amount of time to detect a digital watermark. This paper focuses on scalefactor manipulation to enable high speed watermark embedding/detection for MP3 audio and also proposes the manipulation method which minimizes audio quality degradation adaptively. Evaluation tests showed that the proposed method is capable of embedding 3 bits/frame information without degrading audio quality and detecting it at very high speed. Finally, this paper describes application examples for authentication with a digital signature.

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

PubMed

Levman, Jacob E D; Gallego-Ortiz, Cristina; Warner, Ellen; Causer, Petrina; Martel, Anne L

2016-02-01

Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.

A spatial scan statistic for nonisotropic two-level risk cluster.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2012-01-30

Spatial scan statistic methods are commonly used for geographical disease surveillance and cluster detection. The standard spatial scan statistic does not model any variability in the underlying risks of subregions belonging to a detected cluster. For a multilevel risk cluster, the isotonic spatial scan statistic could model a centralized high-risk kernel in the cluster. Because variations in disease risks are anisotropic owing to different social, economical, or transport factors, the real high-risk kernel will not necessarily take the central place in a whole cluster area. We propose a spatial scan statistic for a nonisotropic two-level risk cluster, which could be used to detect a whole cluster and a noncentralized high-risk kernel within the cluster simultaneously. The performance of the three methods was evaluated through an intensive simulation study. Our proposed nonisotropic two-level method showed better power and geographical precision with two-level risk cluster scenarios, especially for a noncentralized high-risk kernel. Our proposed method is illustrated using the hand-foot-mouth disease data in Pingdu City, Shandong, China in May 2009, compared with two other methods. In this practical study, the nonisotropic two-level method is the only way to precisely detect a high-risk area in a detected whole cluster. Copyright © 2011 John Wiley & Sons, Ltd.

An intelligent detection method for high-field asymmetric waveform ion mobility spectrometry.

PubMed

Li, Yue; Yu, Jianwen; Ruan, Zhiming; Chen, Chilai; Chen, Ran; Wang, Han; Liu, Youjiang; Wang, Xiaozhi; Li, Shan

2018-04-01

In conventional high-field asymmetric waveform ion mobility spectrometry signal acquisition, multi-cycle detection is time consuming and limits somewhat the technique's scope for rapid field detection. In this study, a novel intelligent detection approach has been developed in which a threshold was set on the relative error of α parameters, which can eliminate unnecessary time spent on detection. In this method, two full-spectrum scans were made in advance to obtain the estimated compensation voltage at different dispersion voltages, resulting in a narrowing down of the whole scan area to just the peak area(s) of interest. This intelligent detection method can reduce the detection time to 5-10% of that of the original full-spectrum scan in a single cycle.

Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

PubMed

Uddin, M B; Chow, C M; Su, S W

2018-03-26

Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

Long distance high power optical laser fiber break detection and continuity monitoring systems and methods

DOEpatents

Rinzler, Charles C.; Gray, William C.; Faircloth, Brian O.; Zediker, Mark S.

2016-02-23

A monitoring and detection system for use on high power laser systems, long distance high power laser systems and tools for performing high power laser operations. In particular, the monitoring and detection systems provide break detection and continuity protection for performing high power laser operations on, and in, remote and difficult to access locations.

Highly sensitive chemiluminescent point mutation detection by circular strand-displacement amplification reaction.

PubMed

Shi, Chao; Ge, Yujie; Gu, Hongxi; Ma, Cuiping

2011-08-15

Single nucleotide polymorphism (SNP) genotyping is attracting extensive attentions owing to its direct connections with human diseases including cancers. Here, we have developed a highly sensitive chemiluminescence biosensor based on circular strand-displacement amplification and the separation by magnetic beads reducing the background signal for point mutation detection at room temperature. This method took advantage of both the T4 DNA ligase recognizing single-base mismatch with high selectivity and the strand-displacement reaction of polymerase to perform signal amplification. The detection limit of this method was 1.3 × 10(-16)M, which showed better sensitivity than that of most of those reported detection methods of SNP. Additionally, the magnetic beads as carrier of immobility was not only to reduce the background signal, but also may have potential apply in high through-put screening of SNP detection in human genome. Copyright © 2011 Elsevier B.V. All rights reserved.

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

NASA Astrophysics Data System (ADS)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

PubMed

Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

2012-01-01

The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

Analysis of microdialysate monoamines, including noradrenaline, dopamine and serotonin, using capillary ultra-high performance liquid chromatography and electrochemical detection.

PubMed

Ferry, Barbara; Gifu, Elena-Patricia; Sandu, Ioana; Denoroy, Luc; Parrot, Sandrine

2014-03-01

Electrochemical methods are very often used to detect catecholamine and indolamine neurotransmitters separated by conventional reverse-phase high performance liquid chromatography (HPLC). The present paper presents the development of a chromatographic method to detect monoamines present in low-volume brain dialysis samples using a capillary column filled with sub-2μm particles. Several parameters (repeatability, linearity, accuracy, limit of detection) for this new ultrahigh performance liquid chromatography (UHPLC) method with electrochemical detection were examined after optimization of the analytical conditions. Noradrenaline, adrenaline, serotonin, dopamine and its metabolite 3-methoxytyramine were separated in 1μL of injected sample volume; they were detected above concentrations of 0.5-1nmol/L, with 2.1-9.5% accuracy and intra-assay repeatability equal to or less than 6%. The final method was applied to very low volume dialysates from rat brain containing monoamine traces. The study demonstrates that capillary UHPLC with electrochemical detection is suitable for monitoring dialysate monoamines collected at high sampling rate. Copyright © 2014 Elsevier B.V. All rights reserved.

Visual detection of glial cell line-derived neurotrophic factor based on a molecular translator and isothermal strand-displacement polymerization reaction.

PubMed

Zhang, Li-Yong; Xing, Tao; Du, Li-Xin; Li, Qing-Min; Liu, Wei-Dong; Wang, Ji-Yue; Cai, Jing

2015-01-01

Glial cell line-derived neurotrophic factor (GDNF) is a small protein that potently promotes the survival of many types of neurons. Detection of GDNF is vital to monitoring the survival of sympathetic and sensory neurons. However, the specific method for GDNF detection is also un-discovered. The purpose of this study is to explore the method for protein detection of GDNF. A novel visual detection method based on a molecular translator and isothermal strand-displacement polymerization reaction (ISDPR) has been proposed for the detection of GDNF. In this study, a molecular translator was employed to convert the input protein to output deoxyribonucleic acid signal, which was further amplified by ISDPR. The product of ISDPR was detected by a lateral flow biosensor within 30 minutes. This novel visual detection method based on a molecular translator and ISDPR has very high sensitivity and selectivity, with a dynamic response ranging from 1 pg/mL to 10 ng/mL, and the detection limit was 1 pg/mL of GDNF. This novel visual detection method exhibits high sensitivity and selectivity, which is very simple and universal for GDNF detection to help disease therapy in clinical practice.

Development of an Efficient Entire-Capsid-Coding-Region Amplification Method for Direct Detection of Poliovirus from Stool Extracts

PubMed Central

Kilpatrick, David R.; Nakamura, Tomofumi; Burns, Cara C.; Bukbuk, David; Oderinde, Soji B.; Oberste, M. Steven; Kew, Olen M.; Pallansch, Mark A.; Shimizu, Hiroyuki

2014-01-01

Laboratory diagnosis has played a critical role in the Global Polio Eradication Initiative since 1988, by isolating and identifying poliovirus (PV) from stool specimens by using cell culture as a highly sensitive system to detect PV. In the present study, we aimed to develop a molecular method to detect PV directly from stool extracts, with a high efficiency comparable to that of cell culture. We developed a method to efficiently amplify the entire capsid coding region of human enteroviruses (EVs) including PV. cDNAs of the entire capsid coding region (3.9 kb) were obtained from as few as 50 copies of PV genomes. PV was detected from the cDNAs with an improved PV-specific real-time reverse transcription-PCR system and nucleotide sequence analysis of the VP1 coding region. For assay validation, we analyzed 84 stool extracts that were positive for PV in cell culture and detected PV genomes from 100% of the extracts (84/84 samples) with this method in combination with a PV-specific extraction method. PV could be detected in 2/4 stool extract samples that were negative for PV in cell culture. In PV-positive samples, EV species C viruses were also detected with high frequency (27% [23/86 samples]). This method would be useful for direct detection of PV from stool extracts without using cell culture. PMID:25339406

Multiplex enrichment quantitative PCR (ME-qPCR): a high-throughput, highly sensitive detection method for GMO identification.

PubMed

Fu, Wei; Zhu, Pengyu; Wei, Shuang; Zhixin, Du; Wang, Chenguang; Wu, Xiyang; Li, Feiwu; Zhu, Shuifang

2017-04-01

Among all of the high-throughput detection methods, PCR-based methodologies are regarded as the most cost-efficient and feasible methodologies compared with the next-generation sequencing or ChIP-based methods. However, the PCR-based methods can only achieve multiplex detection up to 15-plex due to limitations imposed by the multiplex primer interactions. The detection throughput cannot meet the demands of high-throughput detection, such as SNP or gene expression analysis. Therefore, in our study, we have developed a new high-throughput PCR-based detection method, multiplex enrichment quantitative PCR (ME-qPCR), which is a combination of qPCR and nested PCR. The GMO content detection results in our study showed that ME-qPCR could achieve high-throughput detection up to 26-plex. Compared to the original qPCR, the Ct values of ME-qPCR were lower for the same group, which showed that ME-qPCR sensitivity is higher than the original qPCR. The absolute limit of detection for ME-qPCR could achieve levels as low as a single copy of the plant genome. Moreover, the specificity results showed that no cross-amplification occurred for irrelevant GMO events. After evaluation of all of the parameters, a practical evaluation was performed with different foods. The more stable amplification results, compared to qPCR, showed that ME-qPCR was suitable for GMO detection in foods. In conclusion, ME-qPCR achieved sensitive, high-throughput GMO detection in complex substrates, such as crops or food samples. In the future, ME-qPCR-based GMO content identification may positively impact SNP analysis or multiplex gene expression of food or agricultural samples. Graphical abstract For the first-step amplification, four primers (A, B, C, and D) have been added into the reaction volume. In this manner, four kinds of amplicons have been generated. All of these four amplicons could be regarded as the target of second-step PCR. For the second-step amplification, three parallels have been taken for the final evaluation. After the second evaluation, the final amplification curves and melting curves have been achieved.

Visual detection of glial cell line-derived neurotrophic factor based on a molecular translator and isothermal strand-displacement polymerization reaction

PubMed Central

Zhang, Li-Yong; Xing, Tao; Du, Li-Xin; Li, Qing-Min; Liu, Wei-Dong; Wang, Ji-Yue; Cai, Jing

2015-01-01

Background Glial cell line-derived neurotrophic factor (GDNF) is a small protein that potently promotes the survival of many types of neurons. Detection of GDNF is vital to monitoring the survival of sympathetic and sensory neurons. However, the specific method for GDNF detection is also un-discovered. The purpose of this study is to explore the method for protein detection of GDNF. Methods A novel visual detection method based on a molecular translator and isothermal strand-displacement polymerization reaction (ISDPR) has been proposed for the detection of GDNF. In this study, a molecular translator was employed to convert the input protein to output deoxyribonucleic acid signal, which was further amplified by ISDPR. The product of ISDPR was detected by a lateral flow biosensor within 30 minutes. Results This novel visual detection method based on a molecular translator and ISDPR has very high sensitivity and selectivity, with a dynamic response ranging from 1 pg/mL to 10 ng/mL, and the detection limit was 1 pg/mL of GDNF. Conclusion This novel visual detection method exhibits high sensitivity and selectivity, which is very simple and universal for GDNF detection to help disease therapy in clinical practice. PMID:25848224

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens

PubMed Central

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-01-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue® mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents. PMID:22735701

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens.

PubMed

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-08-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents.

Method for oil pipeline leak detection based on distributed fiber optic technology

NASA Astrophysics Data System (ADS)

Chen, Huabo; Tu, Yaqing; Luo, Ting

1998-08-01

Pipeline leak detection is a difficult problem to solve up to now. Some traditional leak detection methods have such problems as high rate of false alarm or missing detection, low location estimate capability. For the problems given above, a method for oil pipeline leak detection based on distributed optical fiber sensor with special coating is presented. The fiber's coating interacts with hydrocarbon molecules in oil, which alters the refractive indexed of the coating. Therefore the light-guiding properties of the fiber are modified. Thus pipeline leak location can be determined by OTDR. Oil pipeline lead detection system is designed based on the principle. The system has some features like real time, multi-point detection at the same time and high location accuracy. In the end, some factors that probably influence detection are analyzed and primary improving actions are given.

Oil defect detection of electrowetting display

NASA Astrophysics Data System (ADS)

Chiang, Hou-Chi; Tsai, Yu-Hsiang; Yan, Yung-Jhe; Huang, Ting-Wei; Mang, Ou-Yang

2015-08-01

In recent years, transparent display is an emerging topic in display technologies. Apply in many fields just like mobile device, shopping or advertising window, and etc. Electrowetting Display (EWD) is one kind of potential transparent display technology advantages of high transmittance, fast response time, high contrast and rich color with pigment based oil system. In mass production process of Electrowetting Display, oil defects should be found by Automated Optical Inspection (AOI) detection system. It is useful in determination of panel defects for quality control. According to the research of our group, we proposed a mechanism of AOI detection system detecting the different kinds of oil defects. This mechanism can detect different kinds of oil defect caused by oil overflow or material deteriorated after oil coating or driving. We had experiment our mechanism with a 6-inch Electrowetting Display panel from ITRI, using an Epson V750 scanner with 1200 dpi resolution. Two AOI algorithms were developed, which were high speed method and high precision method. In high precision method, oil jumping or non-recovered can be detected successfully. This mechanism of AOI detection system can be used to evaluate the oil uniformity in EWD panel process. In the future, our AOI detection system can be used in quality control of panel manufacturing for mass production.

Investigation of Human Cancers for Retrovirus by Low-Stringency Target Enrichment and High-Throughput Sequencing.

PubMed

Vinner, Lasse; Mourier, Tobias; Friis-Nielsen, Jens; Gniadecki, Robert; Dybkaer, Karen; Rosenberg, Jacob; Langhoff, Jill Levin; Cruz, David Flores Santa; Fonager, Jannik; Izarzugaza, Jose M G; Gupta, Ramneek; Sicheritz-Ponten, Thomas; Brunak, Søren; Willerslev, Eske; Nielsen, Lars Peter; Hansen, Anders Johannes

2015-08-19

Although nearly one fifth of all human cancers have an infectious aetiology, the causes for the majority of cancers remain unexplained. Despite the enormous data output from high-throughput shotgun sequencing, viral DNA in a clinical sample typically constitutes a proportion of host DNA that is too small to be detected. Sequence variation among virus genomes complicates application of sequence-specific, and highly sensitive, PCR methods. Therefore, we aimed to develop and characterize a method that permits sensitive detection of sequences despite considerable variation. We demonstrate that our low-stringency in-solution hybridization method enables detection of <100 viral copies. Furthermore, distantly related proviral sequences may be enriched by orders of magnitude, enabling discovery of hitherto unknown viral sequences by high-throughput sequencing. The sensitivity was sufficient to detect retroviral sequences in clinical samples. We used this method to conduct an investigation for novel retrovirus in samples from three cancer types. In accordance with recent studies our investigation revealed no retroviral infections in human B-cell lymphoma cells, cutaneous T-cell lymphoma or colorectal cancer biopsies. Nonetheless, our generally applicable method makes sensitive detection possible and permits sequencing of distantly related sequences from complex material.

Detection of high-risk mucosal human papillomavirus DNA in human specimens by a novel and sensitive multiplex PCR method combined with DNA microarray.

PubMed

Gheit, Tarik; Tommasino, Massimo

2011-01-01

Epidemiological and functional studies have clearly demonstrated that certain types of human papillomavirus (HPV) from the genus alpha of the HPV phylogenetic tree, referred to as high-risk (HR) types, are the etiological cause of cervical cancer. Several methods for HPV detection and typing have been developed, and their importance in clinical and epidemiological studies has been well demonstrated. However, comparative studies have shown that several assays have different sensitivities for the detection of specific HPV types, particularly in the case of multiple infections. In this chapter, we describe a novel one-shot method for the detection and typing of 19 mucosal HR HPV types (types 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 70, 73, and 82). The assay combines the advantages of the multiplex PCR methods, i.e., high sensitivity and the possibility to perform multiple amplifications in a single reaction, with an array primer extension (APEX) assay. The latter method offers the benefits of Sanger dideoxy sequencing with the high-throughput potential of the microarray. Initial studies have revealed that the assay is very sensitive in detecting multiple HPV infections.

A fuzzy pattern matching method based on graph kernel for lithography hotspot detection

NASA Astrophysics Data System (ADS)

Nitta, Izumi; Kanazawa, Yuzi; Ishida, Tsutomu; Banno, Koji

2017-03-01

In advanced technology nodes, lithography hotspot detection has become one of the most significant issues in design for manufacturability. Recently, machine learning based lithography hotspot detection has been widely investigated, but it has trade-off between detection accuracy and false alarm. To apply machine learning based technique to the physical verification phase, designers require minimizing undetected hotspots to avoid yield degradation. They also need a ranking of similar known patterns with a detected hotspot to prioritize layout pattern to be corrected. To achieve high detection accuracy and to prioritize detected hotspots, we propose a novel lithography hotspot detection method using Delaunay triangulation and graph kernel based machine learning. Delaunay triangulation extracts features of hotspot patterns where polygons locate irregularly and closely one another, and graph kernel expresses inner structure of graphs. Additionally, our method provides similarity between two patterns and creates a list of similar training patterns with a detected hotspot. Experiments results on ICCAD 2012 benchmarks show that our method achieves high accuracy with allowable range of false alarm. We also show the ranking of the similar known patterns with a detected hotspot.

Rapid concentration and sensitive detection of hookworm ova from wastewater matrices using a real-time PCR method.

PubMed

Gyawali, P; Sidhu, J P S; Ahmed, W; Jagals, P; Toze, S

2015-12-01

The risk of human hookworm infections from land application of wastewater matrices could be high in regions with high hookworm prevalence. A rapid, sensitive and specific hookworm detection method from wastewater matrices is required in order to assess human health risks. Currently available methods used to identify hookworm ova to the species level are time consuming and lack accuracy. In this study, a real-time PCR method was developed for the rapid, sensitive and specific detection of canine hookworm (Ancylostoma caninum) ova from wastewater matrices. A. caninum was chosen because of its morphological similarity to the human hookworm (Ancylostoma duodenale and Necator americanus). The newly developed PCR method has high detection sensitivity with the ability to detect less than one A. caninum ova from 1 L of secondary treated wastewater at the mean threshold cycle (CT) values ranging from 30.1 to 34.3. The method is also able to detect four A. caninum ova from 1 L of raw wastewater and from ∼4 g of treated sludge with mean CT values ranging from 35.6 to 39.8 and 39.8 to 39.9, respectively. The better detection sensitivity obtained for secondary treated wastewater compared to raw wastewater and sludge samples could be attributed to sample turbidity. The proposed method appears to be rapid, sensitive and specific compared to traditional methods and has potential to aid in the public health risk assessment associated with land application of wastewater matrices. Furthermore, the method can be adapted to detect other helminth ova of interest from wastewater matrices. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Ultra-high sensitivity radiation detection apparatus and method

DOEpatents

Gross, Kenneth C.; Valentine, John D.; Markum, Francis; Zawadzki, Mary; Dickerman, Charles

1999-01-01

A method and apparatus are provided to concentrate and detect very low levels of radioactive noble gases from the atmosphere. More specifically the invention provides a method and apparatus to concentrate xenon, krypton and radon in an organic fluid and to detect these gases by the radioactive emissions.

Detecting Tooth Damage in Geared Drive Trains

NASA Technical Reports Server (NTRS)

Nachtsheim, Philip R.

1997-01-01

This paper describes a method that was developed to detect gear tooth damage that does not require a priori knowledge of the frequency characteristic of the fault. The basic idea of the method is that a few damaged teeth will cause transient load fluctuations unlike the normal tooth load fluctuations. The method attempts to measure the energy in the lower side bands of the modulated signal caused by the transient load fluctuations. The method monitors the energy in the frequency interval which excludes the frequency of the lowest dominant normal tooth load fluctuation and all frequencies above it. The method reacted significantly to the tooth fracture damage results documented in the Lewis data sets which were obtained from tests of the OH-58A transmission and tests of high contact ratio spiral bevel gears. The method detected gear tooth fractures in all four of the high contact ratio spiral bevel gear runs. Published results indicate other detection methods were only able to detect faults for three out of four runs.

Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study

PubMed Central

Le Strat, Yann

2017-01-01

The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489

Development of an efficient entire-capsid-coding-region amplification method for direct detection of poliovirus from stool extracts.

PubMed

Arita, Minetaro; Kilpatrick, David R; Nakamura, Tomofumi; Burns, Cara C; Bukbuk, David; Oderinde, Soji B; Oberste, M Steven; Kew, Olen M; Pallansch, Mark A; Shimizu, Hiroyuki

2015-01-01

Laboratory diagnosis has played a critical role in the Global Polio Eradication Initiative since 1988, by isolating and identifying poliovirus (PV) from stool specimens by using cell culture as a highly sensitive system to detect PV. In the present study, we aimed to develop a molecular method to detect PV directly from stool extracts, with a high efficiency comparable to that of cell culture. We developed a method to efficiently amplify the entire capsid coding region of human enteroviruses (EVs) including PV. cDNAs of the entire capsid coding region (3.9 kb) were obtained from as few as 50 copies of PV genomes. PV was detected from the cDNAs with an improved PV-specific real-time reverse transcription-PCR system and nucleotide sequence analysis of the VP1 coding region. For assay validation, we analyzed 84 stool extracts that were positive for PV in cell culture and detected PV genomes from 100% of the extracts (84/84 samples) with this method in combination with a PV-specific extraction method. PV could be detected in 2/4 stool extract samples that were negative for PV in cell culture. In PV-positive samples, EV species C viruses were also detected with high frequency (27% [23/86 samples]). This method would be useful for direct detection of PV from stool extracts without using cell culture. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

A novel rail defect detection method based on undecimated lifting wavelet packet transform and Shannon entropy-improved adaptive line enhancer

NASA Astrophysics Data System (ADS)

Hao, Qiushi; Zhang, Xin; Wang, Yan; Shen, Yi; Makis, Viliam

2018-07-01

Acoustic emission (AE) technology is sensitive to subliminal rail defects, however strong wheel-rail contact rolling noise under high-speed condition has gravely impeded detecting of rail defects using traditional denoising methods. In this context, the paper develops an adaptive detection method for rail cracks, which combines multiresolution analysis with an improved adaptive line enhancer (ALE). To obtain elaborate multiresolution information of transient crack signals with low computational cost, lifting scheme-based undecimated wavelet packet transform is adopted. In order to feature the impulsive property of crack signals, a Shannon entropy-improved ALE is proposed as a signal enhancing approach, where Shannon entropy is introduced to improve the cost function. Then a rail defect detection plan based on the proposed method for high-speed condition is put forward. From theoretical analysis and experimental verification, it is demonstrated that the proposed method has superior performance in enhancing the rail defect AE signal and reducing the strong background noise, offering an effective multiresolution approach for rail defect detection under high-speed and strong-noise condition.

High-performance Chinese multiclass traffic sign detection via coarse-to-fine cascade and parallel support vector machine detectors

NASA Astrophysics Data System (ADS)

Chang, Faliang; Liu, Chunsheng

2017-09-01

The high variability of sign colors and shapes in uncontrolled environments has made the detection of traffic signs a challenging problem in computer vision. We propose a traffic sign detection (TSD) method based on coarse-to-fine cascade and parallel support vector machine (SVM) detectors to detect Chinese warning and danger traffic signs. First, a region of interest (ROI) extraction method is proposed to extract ROIs using color contrast features in local regions. The ROI extraction can reduce scanning regions and save detection time. For multiclass TSD, we propose a structure that combines a coarse-to-fine cascaded tree with a parallel structure of histogram of oriented gradients (HOG) + SVM detectors. The cascaded tree is designed to detect different types of traffic signs in a coarse-to-fine process. The parallel HOG + SVM detectors are designed to do fine detection of different types of traffic signs. The experiments demonstrate the proposed TSD method can rapidly detect multiclass traffic signs with different colors and shapes in high accuracy.

Single-copy gene detection using branched DNA (bDNA) in situ hybridization.

PubMed

Player, A N; Shen, L P; Kenny, D; Antao, V P; Kolberg, J A

2001-05-01

We have developed a branched DNA in situ hybridization (bDNA ISH) method for detection of human papillomavirus (HPV) DNA in whole cells. Using human cervical cancer cell lines with known copies of HPV DNA, we show that the bDNA ISH method is highly sensitive, detecting as few as one or two copies of HPV DNA per cell. By modifying sample pretreatment, viral mRNA or DNA sequences can be detected using the same set of oligonucleotide probes. In experiments performed on mixed populations of cells, the bDNA ISH method is highly specific and can distinguish cells with HPV-16 from cells with HPV-18 DNA. Furthermore, we demonstrate that the bDNA ISH method provides precise localization, yielding positive signals retained within the subcellular compartments in which the target nucleic acid sequences are localized. As an effective and convenient means for nucleic acid detection, the bDNA ISH method is applicable to the detection of cancers and infectious agents. (J Histochem Cytochem 49:603-611, 2001)

A Self-Powered Thin-Film Radiation Detector Using Intrinsic High-Energy Current (HEC) (Author’s Final Version)

DTIC Science & Technology

2016-09-08

10.1118/1.4935531. A new radiation detection method relies on high-energy current (HEC) formed by secondary charged particles in the detector material...photocurrent, radiation detection , self-powered, thin-film U U U SAR 17 Dr. Joseph Wander Reset A Self-powered thin-film radiation detector using intrinsic...Program, Lowell, MA 01854 Purpose: We introduce a radiation detection method that relies on high-energy current (HEC) formed by secondary 10 charged

Mobile/android application for QRS detection using zero cross method

NASA Astrophysics Data System (ADS)

Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

2018-03-01

In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

Highly Sensitive and Automated Surface Enhanced Raman Scattering-based Immunoassay for H5N1 Detection with Digital Microfluidics.

PubMed

Wang, Yang; Ruan, Qingyu; Lei, Zhi-Chao; Lin, Shui-Chao; Zhu, Zhi; Zhou, Leiji; Yang, Chaoyong

2018-04-17

Digital microfluidics (DMF) is a powerful platform for a broad range of applications, especially immunoassays having multiple steps, due to the advantages of low reagent consumption and high automatization. Surface enhanced Raman scattering (SERS) has been proven as an attractive method for highly sensitive and multiplex detection, because of its remarkable signal amplification and excellent spatial resolution. Here we propose a SERS-based immunoassay with DMF for rapid, automated, and sensitive detection of disease biomarkers. SERS tags labeled with Raman reporter 4-mercaptobenzoic acid (4-MBA) were synthesized with a core@shell nanostructure and showed strong signals, good uniformity, and high stability. A sandwich immunoassay was designed, in which magnetic beads coated with antibodies were used as solid support to capture antigens from samples to form a beads-antibody-antigen immunocomplex. By labeling the immunocomplex with a detection antibody-functionalized SERS tag, antigen can be sensitively detected through the strong SERS signal. The automation capability of DMF can greatly simplify the assay procedure while reducing the risk of exposure to hazardous samples. Quantitative detection of avian influenza virus H5N1 in buffer and human serum was implemented to demonstrate the utility of the DMF-SERS method. The DMF-SERS method shows excellent sensitivity (LOD of 74 pg/mL) and selectivity for H5N1 detection with less assay time (<1 h) and lower reagent consumption (∼30 μL) compared to the standard ELISA method. Therefore, this DMF-SERS method holds great potentials for automated and sensitive detection of a variety of infectious diseases.

Community Detection in Complex Networks via Clique Conductance.

PubMed

Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye

2018-04-13

Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

Study of comparison between Ultra-high Frequency (UHF) method and ultrasonic method on PD detection for GIS

NASA Astrophysics Data System (ADS)

Li, Yanran; Chen, Duo; Li, Li; Zhang, Jiwei; Li, Guang; Liu, Hongxia

2017-11-01

GIS (gas insulated switchgear), is an important equipment in power system. Partial discharge plays an important role in detecting the insulation performance of GIS. UHF method and ultrasonic method frequently used in partial discharge (PD) detection for GIS. However, few studies have been conducted on comparison of this two methods. From the view point of safety, it is necessary to investigate UHF method and ultrasonic method for partial discharge in GIS. This paper presents study aimed at clarifying the effect of UHF method and ultrasonic method for partial discharge caused by free metal particles in GIS. Partial discharge tests were performed in laboratory simulated environment. Obtained results show the ability of anti-interference of signal detection and the accuracy of fault localization for UHF method and ultrasonic method. A new method based on UHF method and ultrasonic method of PD detection for GIS is proposed in order to greatly enhance the ability of anti-interference of signal detection and the accuracy of detection localization.

Fluorescent microplate assay method for high-throughput detection of lipase transesterification activity.

PubMed

Zheng, Jianyong; Wei, Wei; Lan, Xing; Zhang, Yinjun; Wang, Zhao

2018-05-15

This study describes a sensitive and fluorescent microplate assay method to detect lipase transesterification activity. Lipase-catalyzed transesterification between butyryl 4-methyl umbelliferone (Bu-4-Mu) and methanol in tert-butanol was selected as the model reaction. The release of 4-methylumbelliferone (4-Mu) in the reaction was determined by detecting the fluorescence intensity at λ ex 330 nm and λ em 390 nm. Several lipases were used to investigate the accuracy and efficiency of the proposed method. Apparent Michaelis constant (Km) was calculated for transesterification between Bu-4-Mu and methanol by the lipases. The main advantages of the assay method include high sensitivity, inexpensive reagents, and simple detection process. Copyright © 2018 Elsevier Inc. All rights reserved.

High-resolution metabolomics assessment of military personnel: Evaluating analytical strategies for chemical detection

PubMed Central

Liu, Ken H.; Walker, Douglas I.; Uppal, Karan; Tran, ViLinh; Rohrbeck, Patricia; Mallon, Timothy M.; Jones, Dean P.

2016-01-01

Objective To maximize detection of serum metabolites with high-resolution metabolomics (HRM). Methods Department of Defense Serum Repository (DoDSR) samples were analyzed using ultra-high resolution mass spectrometry with three complementary chromatographic phases and four ionization modes. Chemical coverage was evaluated by number of ions detected and accurate mass matches to a human metabolomics database. Results Individual HRM platforms provided accurate mass matches for up to 58% of the KEGG metabolite database. Combining two analytical methods increased matches to 72%, and included metabolites in most major human metabolic pathways and chemical classes. Detection and feature quality varied by analytical configuration. Conclusions Dual chromatography HRM with positive and negative electrospray ionization provides an effective generalized method for metabolic assessment of military personnel. PMID:27501105

Automatic Building Damage Detection Method Using High-Resolution Remote Sensing Images and 3d GIS Model

NASA Astrophysics Data System (ADS)

Tu, Jihui; Sui, Haigang; Feng, Wenqing; Song, Zhina

2016-06-01

In this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various building damaged types(e.g., trivial damaged, severely damaged and totally collapsed.) Therefore, we want to detect the different building damaged type using 2D and 3D feature of scenes because the real world we live in is a 3D space. The proposed method generalizes that the image geometric correction method firstly corrects the post-disasters remote sensing image using the 3D GIS model or RPC parameters, then detects the different building damaged types using the change of the height and area between the pre- and post-disasters and the texture feature of post-disasters. The results, evaluated on a selected study site of the Beichuan earthquake ruins, Sichuan, show that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and well suited for rapid damage assessment after natural disasters.

Vision Based Obstacle Detection in Uav Imaging

NASA Astrophysics Data System (ADS)

Badrloo, S.; Varshosaz, M.

2017-08-01

Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

A simple and sensitive high-throughput GFP screening in woody and herbaceous plants.

PubMed

Hily, Jean-Michel; Liu, Zongrang

2009-03-01

Green fluorescent protein (GFP) has been used widely as a powerful bioluminescent reporter, but its visualization by existing methods in tissues or whole plants and its utilization for high-throughput screening remains challenging in many species. Here, we report a fluorescence image analyzer-based method for GFP detection and its utility for high-throughput screening of transformed plants. Of three detection methods tested, the Typhoon fluorescence scanner was able to detect GFP fluorescence in all Arabidopsis thaliana tissues and apple leaves, while regular fluorescence microscopy detected it only in Arabidopsis flowers and siliques but barely in the leaves of either Arabidopsis or apple. The hand-held UV illumination method failed in all tissues of both species. Additionally, the Typhoon imager was able to detect GFP fluorescence in both green and non-green tissues of Arabidopsis seedlings as well as in imbibed seeds, qualifying it as a high-throughput screening tool, which was further demonstrated by screening the seedlings of primary transformed T(0) seeds. Of the 30,000 germinating Arabidopsis seedlings screened, at least 69 GFP-positive lines were identified, accounting for an approximately 0.23% transformation efficiency. About 14,000 seedlings grown in 16 Petri plates could be screened within an hour, making the screening process significantly more efficient and robust than any other existing high-throughput screening method for transgenic plants.

[High-sensitive detection of multiple allergenic proteins in infant food with high-resolution mass spectrometry].

PubMed

Wu, Ci; Chen, Xi; Liu, Jianhui; Zhang, Xiaolin; Xue, Weifeng; Liang, Zhen; Liu, Mengyao; Cui, Yan; Huang, Daliang; Zhang, Lihua

2017-10-08

A novel method of the simultaneous detection of multiple kinds of allergenic proteins in infant food with parallel reaction monitoring (PRM) mode using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was established. In this method, unique peptides with good stability and high sensibility were used to quantify the corresponding allergenic proteins. Furthermore, multiple kinds of allergenic proteins are inspected simultaneously with high sensitivity. In addition, such method was successfully used for the detection of multiple allergenic proteins in infant food. As for the sample preparation for infant food, compared with the traditional acetone precipitation strategy, the protein extraction efficiency and capacity of resisting disturbance are both higher with in-situ filter-aided sample pretreatment (i-FASP) method. All allergenic proteins gave a good linear response with the correlation coefficients ( R 2 ) ≥ 0.99, and the largest concentration range of the allergenic proteins could be four orders of magnitude, and the lowest detection limit was 0.028 mg/L, which was better than that reported in references. Finally, the method was conveniently used to detect the allergens from four imported infant food real samples. All the results demonstrate that this novel strategy is of great significance for providing a rapid and reliable analytical technique for allergen proteomics.

Fundamentals, achievements and challenges in the electrochemical sensing of pathogens.

PubMed

Monzó, Javier; Insua, Ignacio; Fernandez-Trillo, Francisco; Rodriguez, Paramaconi

2015-11-07

Electrochemical sensors are powerful tools widely used in industrial, environmental and medical applications. The versatility of electrochemical methods allows for the investigation of chemical composition in real time and in situ. Electrochemical detection of specific biological molecules is a powerful means for detecting disease-related markers. In the last 10 years, highly-sensitive and specific methods have been developed to detect waterborne and foodborne pathogens. In this review, we classify the different electrochemical techniques used for the qualitative and quantitative detection of pathogens. The robustness of electrochemical methods allows for accurate detection even in heterogeneous and impure samples. We present a fundamental description of the three major electrochemical sensing methods used in the detection of pathogens and the advantages and disadvantages of each of these methods. In each section, we highlight recent breakthroughs, including the utilisation of microfluidics, immunomagnetic separation and multiplexing for the detection of multiple pathogens in a single device. We also include recent studies describing new strategies for the design of future immunosensing systems and protocols. The high sensitivity and selectivity, together with the portability and the cost-effectiveness of the instrumentation, enhances the demand for further development in the electrochemical detection of microbes.

Rapid Isolation of Phenol Degrading Bacteria by Fourier Transform Infrared (FTIR) Spectroscopy.

PubMed

Li, Fei; Song, Wen-jun; Wei, Ji-ping; Wang, Su-ying; Liu, Chong-ji

2015-05-01

Phenol is an important chemical engineering material and ubiquitous in industry wastewater, its existence has become a thorny issue in many developed and developing country. More and more stringent standards for effluent all over the world with human realizing the toxicity of phenol have been announced. Many advanced biological methods are applied to industrial wastewater treatment with low cost, high efficiency and no secondary pollution, but the screening of function microorganisms is certain cumbersome process. In our study a rapid procedure devised for screening bacteria on solid medium can degrade phenol coupled with attenuated total reflection fourier transform infrared (ATR-FTIR) which is a detection method has the characteristics of efficient, fast, high fingerprint were used. Principal component analysis (PCA) is a method in common use to extract fingerprint peaks effectively, it couples with partial least squares (PLS) statistical method could establish a credible model. The model we created using PCA-PLS can reach 99. 5% of coefficient determination and validation data get 99. 4%, which shows the promising fitness and forecasting of the model. The high fitting model is used for predicting the concentration of phenol at solid medium where the bacteria were grown. The highly consistent result of two screening methods, solid cultural with ATR-FTIR detected and traditional liquid cultural detected by GC methods, suggests the former can rapid isolate the bacteria which can degrade substrates as well as traditional cumbersome liquid cultural method. Many hazardous substrates widely existed in industry wastewater, most of them has specialize fingerprint peaks detected by ATR-FTIR, thereby this detected method could be used as a rapid detection for isolation of functional microorganisms those can degrade many other toxic substrates.

A Bayesian Method for Managing Uncertainties Relating to Distributed Multistatic Sensor Search

DTIC Science & Technology

2006-07-01

before - detect process. There will also be an increased probability of high signal-to-noise ratio (SNR) detections associated with specular and near...and high target strength and high Doppler opportunities give rise to the expectation of an increased number of detections that could feed a track

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

Use of diaminofluoresceins to detect and measure nitric oxide in low level generating human immune cells.

PubMed

Tiscornia, Adriana; Cairoli, Ernesto; Marquez, Maria; Denicola, Ana; Pritsch, Otto; Cayota, Alfonso

2009-03-15

Nitric oxide ((*)NO) has been implicated in multiple physiological and pathological immune processes. Different methods have been developed to detect and quantify (*)NO, where one of the principal difficulties are the accurately detection in cellular system with low levels of (*)NO production. The choice of the (*)NO detection method to be used depends on the characteristics of the experimental system and the levels of (*)NO production which depend on either the organism source of samples or the experimental conditions. Recently, high sensitive methods to detect and image (*)NO have been reported using 4,5-diaminofluorescein-based fluorescent probes (DAF) and its derivate 4,5-diaminofluorescein diacetate (DAF-2 DA). This work was aimed to adapt and optimize the use of DAF probes to detect and quantify the (*)NO production in systems of high, moderate and low out-put production, especially in human PBMC and their subpopulations. Here, we report an original experimental design which is useful to detect and estimate (*)NO fluxes in human PBMC and their subpopulations with high specificity and sensitivity.

Comparing real-time and conventional PCR to culture-based methods for detecting and quantifying Escherichia coli O157 in cattle feces.

PubMed

Jacob, M E; Bai, J; Renter, D G; Rogers, A T; Shi, X; Nagaraja, T G

2014-02-01

Detection of Escherichia coli O157 in cattle feces has traditionally used culture-based methods; PCR-based methods have been suggested as an alternative. We aimed to determine if multiplex real-time (mq) or conventional PCR methods could reliably detect cattle naturally shedding high (≥10(4) CFU/g of feces) and low (∼10(2) CFU/g of feces) concentrations of E. coli O157. Feces were collected from pens of feedlot cattle and evaluated for E. coli O157 by culture methods. Samples were categorized as (i) high shedders, (ii) immunomagnetic separation (IMS) positive after enrichment, or (iii) culture negative. DNA was extracted pre- and postenrichment from 100 fecal samples from each category (high shedder, IMS positive, culture negative) and subjected to mqPCR and conventional PCR assays based on detecting three genes, rfbE, stx1, and stx2. In feces from cattle determined to be E. coli O157 high shedders by culture, 37% were positive by mqPCR prior to enrichment; 85% of samples were positive after enrichment. In IMS-positive samples, 4% were positive by mqPCR prior to enrichment, while 43% were positive after enrichment. In culture-negative feces, 7% were positive by mqPCR prior to enrichment, and 40% were positive after enrichment. The proportion of high shedder-positive and culture-positive (high shedder and IMS) samples were significantly different from mqPCR-positive samples before and after enrichment (P < 0.01). Similar results were observed for conventional PCR. Our data suggest that mqPCR and conventional PCR are most useful in identifying high shedder animals and may not be an appropriate substitute to culture-based methods for detection of E. coli O157 in cattle feces.

Eyelid contour detection and tracking for startle research related eye-blink measurements from high-speed video records.

PubMed

Bernard, Florian; Deuter, Christian Eric; Gemmar, Peter; Schachinger, Hartmut

2013-10-01

Using the positions of the eyelids is an effective and contact-free way for the measurement of startle induced eye-blinks, which plays an important role in human psychophysiological research. To the best of our knowledge, no methods for an efficient detection and tracking of the exact eyelid contours in image sequences captured at high-speed exist that are conveniently usable by psychophysiological researchers. In this publication a semi-automatic model-based eyelid contour detection and tracking algorithm for the analysis of high-speed video recordings from an eye tracker is presented. As a large number of images have been acquired prior to method development it was important that our technique is able to deal with images that are recorded without any special parametrisation of the eye tracker. The method entails pupil detection, specular reflection removal and makes use of dynamic model adaption. In a proof-of-concept study we could achieve a correct detection rate of 90.6%. With this approach, we provide a feasible method to accurately assess eye-blinks from high-speed video recordings. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Rapid Detection and Simultaneous Genotyping of Cronobacter spp. (formerly Enterobacter sakazakii) in Powdered Infant Formula Using Real-time PCR and High Resolution Melting (HRM) Analysis

PubMed Central

Cai, Xian-Quan; Yu, Hai-Qiong; Ruan, Zhou-Xi; Yang, Lei-Liang; Bai, Jian-Shan; Qiu, De-Yi; Jian, Zhi-Hua; Xiao, Yi-Qian; Yang, Jie-Yang; Le, Thanh Hoa; Zhu, Xing-Quan

2013-01-01

Cronobacter spp. is an emerging pathogen that causes meningitis, sepsis, bacteremia, and necrotizing enterocolitis in neonates and children. The present study developed an assay integrating real-time PCR and high resolution melting (HRM) analysis targeting the OmpA gene for the specific detection and rapid identification of Cronobacter spp. (formerly Enterobacter sakazakii) in powdered infant formula. Eleven Cronobacter field isolates and 25 reference strains were examined using one pair of primers, having the accuracy of 100% in reference to conventional methods. The assay was proved to be highly sensitive with a detection limit of 102 CFU/ml without pre-enrichment, and highly concordant (100%) when compared with ISO-IDF 22964 in 89 actual samples. The method performed for Cronobacter spp. detection was less than 24 h, drastically shortened, compared to several days using standard culturing method, it is probe-free and reduces a risk of PCR carryover. Moreover, all Cronobacter strains examined in this study were genotyped into two species according to their HRM profiles. The established method should provide a molecular tool for direct detection and simultaneous genotyping of Cronobacter spp. in powdered infant formula. PMID:23825624

Rapid detection and simultaneous genotyping of Cronobacter spp. (formerly Enterobacter sakazakii) in powdered infant formula using real-time PCR and high resolution melting (HRM) analysis.

PubMed

Cai, Xian-Quan; Yu, Hai-Qiong; Ruan, Zhou-Xi; Yang, Lei-Liang; Bai, Jian-Shan; Qiu, De-Yi; Jian, Zhi-Hua; Xiao, Yi-Qian; Yang, Jie-Yang; Le, Thanh Hoa; Zhu, Xing-Quan

2013-01-01

Cronobacter spp. is an emerging pathogen that causes meningitis, sepsis, bacteremia, and necrotizing enterocolitis in neonates and children. The present study developed an assay integrating real-time PCR and high resolution melting (HRM) analysis targeting the OmpA gene for the specific detection and rapid identification of Cronobacter spp. (formerly Enterobacter sakazakii) in powdered infant formula. Eleven Cronobacter field isolates and 25 reference strains were examined using one pair of primers, having the accuracy of 100% in reference to conventional methods. The assay was proved to be highly sensitive with a detection limit of 10(2) CFU/ml without pre-enrichment, and highly concordant (100%) when compared with ISO-IDF 22964 in 89 actual samples. The method performed for Cronobacter spp. detection was less than 24 h, drastically shortened, compared to several days using standard culturing method, it is probe-free and reduces a risk of PCR carryover. Moreover, all Cronobacter strains examined in this study were genotyped into two species according to their HRM profiles. The established method should provide a molecular tool for direct detection and simultaneous genotyping of Cronobacter spp. in powdered infant formula.

Highly sensitive screening method for nitroaromatic, nitramine and nitrate ester explosives by high performance liquid chromatography-atmospheric pressure ionization-mass spectrometry (HPLC-API-MS) in forensic applications.

PubMed

Xu, Xiaoma; van de Craats, Anick M; de Bruyn, Peter C A M

2004-11-01

A highly sensitive screening method based on high performance liquid chromatography atmospheric pressure ionization mass spectrometry (HPLC-API-MS) has been developed for the analysis of 21 nitroaromatic, nitramine and nitrate ester explosives, which include the explosives most commonly encountered in forensic science. Two atmospheric pressure ionization (API) methods, atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI), and various experimental conditions have been applied to allow for the detection of all 21 explosive compounds. The limit of detection (LOD) in the full-scan mode has been found to be 0.012-1.2 ng on column for the screening of most explosives investigated. For nitrobenzene, an LOD of 10 ng was found with the APCI method in the negative mode. Although the detection of nitrobenzene, 2-, 3-, and 4-nitrotoluene is hindered by the difficult ionization of these compounds, we have found that by forming an adduct with glycine, LOD values in the range of 3-16 ng on column can be achieved. Compared with previous screening methods with thermospray ionization, the API method has distinct advantages, including simplicity and stability of the method applied, an extended screening range and a low detection limit for the explosives studied.

Study of New Method Combined Ultra-High Frequency (UHF) Method and Ultrasonic Method on PD Detection for GIS

NASA Astrophysics Data System (ADS)

Li, Yanran; Chen, Duo; Zhang, Jiwei; Chen, Ning; Li, Xiaoqi; Gong, Xiaojing

2017-09-01

GIS (gas insulated switchgear), is an important equipment in power system. Partial discharge plays an important role in detecting the insulation performance of GIS. UHF method and ultrasonic method frequently used in partial discharge (PD) detection for GIS. It is necessary to investigate UHF method and ultrasonic method for partial discharge in GIS. However, very few studies have been conducted on the method combined this two methods. From the view point of safety, a new method based on UHF method and ultrasonic method of PD detection for GIS is proposed in order to greatly enhance the ability of anti-interference of signal detection and the accuracy of fault localization. This paper presents study aimed at clarifying the effect of the new method combined UHF method and ultrasonic method. Partial discharge tests were performed in laboratory simulated environment. Obtained results show the ability of anti-interference of signal detection and the accuracy of fault localization for this new method combined UHF method and ultrasonic method.

Efficient and Specific Detection of Salmonella in Food Samples Using a stn-Based Loop-Mediated Isothermal Amplification Method

PubMed Central

2015-01-01

The Salmonella enterotoxin (stn) gene exhibits high homology among S. enterica serovars and S. bongori. A set of 6 specific primers targeting the stn gene were designed for detection of Salmonella spp. using the loop-mediated isothermal amplification (LAMP) method. The primers amplified target sequences in all 102 strains of 87 serovars of Salmonella tested and no products were detected in 57 non-Salmonella strains. The detection limit in pure cultures was 5 fg DNA/reaction when amplified at 65°C for 25 min. The LAMP assay could detect Salmonella in artificially contaminated food samples as low as 220 cells/g of food without a preenrichment step. However, the sensitivity was increased 100-fold (~2 cells/g) following 5 hr preenrichment at 35°C. The LAMP technique, with a preenrichment step for 5 and 16 hr, was shown to give 100% specificity with food samples compared to the reference culture method in which 67 out of 90 food samples gave positive results. Different food matrixes did not interfere with LAMP detection which employed a simple boiling method for DNA template preparation. The results indicate that the LAMP method, targeting the stn gene, has great potential for detection of Salmonella in food samples with both high specificity and high sensitivity. PMID:26543859

Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

PubMed

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

A Method of Face Detection with Bayesian Probability

NASA Astrophysics Data System (ADS)

Sarker, Goutam

2010-10-01

The objective of face detection is to identify all images which contain a face, irrespective of its orientation, illumination conditions etc. This is a hard problem, because the faces are highly variable in size, shape lighting conditions etc. Many methods have been designed and developed to detect faces in a single image. The present paper is based on one `Appearance Based Method' which relies on learning the facial and non facial features from image examples. This in its turn is based on statistical analysis of examples and counter examples of facial images and employs Bayesian Conditional Classification Rule to detect the probability of belongingness of a face (or non-face) within an image frame. The detection rate of the present system is very high and thereby the number of false positive and false negative detection is substantially low.

Digital transillumination in caries detection versus radiographic and clinical methods: an in-vivo study

PubMed Central

Lara-Capi, Cynthia; Lingström, Peter; Lai, Gianfranco; Cocco, Fabio; Simark-Mattsson, Charlotte; Campus, Guglielmo

2017-01-01

Objectives: This article aimed to evaluate: (a) the agreement between a near-infrared light transillumination device and clinical and radiographic examinations in caries lesion detection and (b) the reliability of images captured by the transillumination device. Methods: Two calibrated examiners evaluated the caries status in premolars and molars on 52 randomly selected subjects by comparing the transillumination device with a clinical examination for the occlusal surfaces and by comparing the transillumination device with a radiographic examination (bitewing radiographs) for the approximal surfaces. Forty-eight trained dental hygienists evaluated and reevaluated 30 randomly selected images 1-month later. Results: A high concordance between transillumination method and clinical examination (kappa = 0.99) was detected for occlusal caries lesions, while for approximal surfaces, the transillumination device identified a higher number of lesions with respect to bitewing (kappa = 0.91). At the dentinal level, the two methods identified the same number of caries lesions (kappa = 1), whereas more approximal lesions were recorded using the transillumination device in the enamel (kappa = 0.24). The intraexaminer reliability was substantial/almost perfect in 59.4% of the participants. Conclusions: The transillumination method showed a high concordance compared with traditional methods (clinical examination and bitewing radiographs). Caries detection reliability using the transillumination device images showed a high intraexaminer agreement. Transillumination showed to be a reliable method and as effective as traditional methods in caries detection. PMID:28191797

Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions.

PubMed

Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J

2014-03-20

Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.

Method and apparatus for data sampling

DOEpatents

Odell, Daniel M. C.

1994-01-01

A method and apparatus for sampling radiation detector outputs and determining event data from the collected samples. The method uses high speed sampling of the detector output, the conversion of the samples to digital values, and the discrimination of the digital values so that digital values representing detected events are determined. The high speed sampling and digital conversion is performed by an A/D sampler that samples the detector output at a rate high enough to produce numerous digital samples for each detected event. The digital discrimination identifies those digital samples that are not representative of detected events. The sampling and discrimination also provides for temporary or permanent storage, either serially or in parallel, to a digital storage medium.

Immunohistochemistry and Polymerase Chain Reaction for Detection Human Papilloma Virus in Warts: A Comparative Study

PubMed Central

Lee, Hong Sun; Lee, Ji Hyun; Choo, Ji Yoon; Byun, Hee Jin; Jun, Jin Hyun

2016-01-01

Background Immunohistochemistry and polymerase chain reaction (PCR) are the most widely used methods for the detection of viruses. PCR is known to be a more sensitive and specific method than the immunohistochemical method at this time, but PCR has the disadvantages of high cost and skilled work to use widely. With the progress of technology, the immunohistochemical methods used in these days has come to be highly sensitive and actively used in the diagnostic fields. Objective To evaluate and compare the usefulness of immunohistochemistry and PCR for detection human papilloma virus (HPV) in wart lesions. Methods Nine biopsy samples of verruca vulgaris and 10 of condyloma accuminatum were examined. Immunohistochemical staining using monoclonal antibody to HPV L1 capsid protein and PCR were done for the samples. DNA sequencing of the PCR products and HPV genotyping were also done. Results HPV detection rate was 78.9% (88.9% in verruca vulgaris, 70.0% in condyloma accuminatum) on immunohistochemistry and 100.0% for PCR. HPV-6 genotype showed a lower positivity rate on immunohistochemistry (50.0%) as compared to that of the other HPV genotypes. Conclusion Immunohistochemistry for HPV L1 capsid protein showed comparable sensitivity for detection HPV. Considering the high cost and great effort needed for the PCR methods, we can use immunohistochemistry for HPV L1 capsid protein with the advantage of lower cost and simple methods for HPV detection. PMID:27489431

Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

PubMed

Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

2013-01-01

Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

Automated methods for multiplexed pathogen detection.

PubMed

Straub, Timothy M; Dockendorff, Brian P; Quiñonez-Díaz, Maria D; Valdez, Catherine O; Shutthanandan, Janani I; Tarasevich, Barbara J; Grate, Jay W; Bruckner-Lea, Cynthia J

2005-09-01

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cycler where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides "live vs. dead" capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.

Automated Methods for Multiplexed Pathogen Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straub, Tim M.; Dockendorff, Brian P.; Quinonez-Diaz, Maria D.

2005-09-01

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cyclermore » where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides ''live vs. dead'' capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.« less

Large-scale protein-protein interactions detection by integrating big biosensing data with computational model.

PubMed

You, Zhu-Hong; Li, Shuai; Gao, Xin; Luo, Xin; Ji, Zhen

2014-01-01

Protein-protein interactions are the basis of biological functions, and studying these interactions on a molecular level is of crucial importance for understanding the functionality of a living cell. During the past decade, biosensors have emerged as an important tool for the high-throughput identification of proteins and their interactions. However, the high-throughput experimental methods for identifying PPIs are both time-consuming and expensive. On the other hand, high-throughput PPI data are often associated with high false-positive and high false-negative rates. Targeting at these problems, we propose a method for PPI detection by integrating biosensor-based PPI data with a novel computational model. This method was developed based on the algorithm of extreme learning machine combined with a novel representation of protein sequence descriptor. When performed on the large-scale human protein interaction dataset, the proposed method achieved 84.8% prediction accuracy with 84.08% sensitivity at the specificity of 85.53%. We conducted more extensive experiments to compare the proposed method with the state-of-the-art techniques, support vector machine. The achieved results demonstrate that our approach is very promising for detecting new PPIs, and it can be a helpful supplement for biosensor-based PPI data detection.

A novel, colorimetric method for biogenic amine detection based on arylalkylamine N-acetyltransferase.

PubMed

Leng, Pei-Qiang; Zhao, Feng-Lan; Yin, Bin-Cheng; Ye, Bang-Ce

2015-05-21

We developed a novel colorimetric method for rapid detection of biogenic amines based on arylalkylamine N-acetyltransferase (aaNAT). The proposed method offers distinct advantages including simple handling, high speed, low cost, good sensitivity and selectivity.

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize detection errors. Given the great expense and effort associated with morphological identification of many...

Simultaneous mutation detection of three homoeologous genes in wheat by High Resolution Melting analysis and Mutation Surveyor.

PubMed

Dong, Chongmei; Vincent, Kate; Sharp, Peter

2009-12-04

TILLING (Targeting Induced Local Lesions IN Genomes) is a powerful tool for reverse genetics, combining traditional chemical mutagenesis with high-throughput PCR-based mutation detection to discover induced mutations that alter protein function. The most popular mutation detection method for TILLING is a mismatch cleavage assay using the endonuclease CelI. For this method, locus-specific PCR is essential. Most wheat genes are present as three similar sequences with high homology in exons and low homology in introns. Locus-specific primers can usually be designed in introns. However, it is sometimes difficult to design locus-specific PCR primers in a conserved region with high homology among the three homoeologous genes, or in a gene lacking introns, or if information on introns is not available. Here we describe a mutation detection method which combines High Resolution Melting (HRM) analysis of mixed PCR amplicons containing three homoeologous gene fragments and sequence analysis using Mutation Surveyor software, aimed at simultaneous detection of mutations in three homoeologous genes. We demonstrate that High Resolution Melting (HRM) analysis can be used in mutation scans in mixed PCR amplicons containing three homoeologous gene fragments. Combining HRM scanning with sequence analysis using Mutation Surveyor is sensitive enough to detect a single nucleotide mutation in the heterozygous state in a mixed PCR amplicon containing three homoeoloci. The method was tested and validated in an EMS (ethylmethane sulfonate)-treated wheat TILLING population, screening mutations in the carboxyl terminal domain of the Starch Synthase II (SSII) gene. Selected identified mutations of interest can be further analysed by cloning to confirm the mutation and determine the genomic origin of the mutation. Polyploidy is common in plants. Conserved regions of a gene often represent functional domains and have high sequence similarity between homoeologous loci. The method described here is a useful alternative to locus-specific based methods for screening mutations in conserved functional domains of homoeologous genes. This method can also be used for SNP (single nucleotide polymorphism) marker development and eco-TILLING in polyploid species.

Human ear detection in the thermal infrared spectrum

NASA Astrophysics Data System (ADS)

Abaza, Ayman; Bourlai, Thirimachos

2012-06-01

In this paper the problem of human ear detection in the thermal infrared (IR) spectrum is studied in order to illustrate the advantages and limitations of the most important steps of ear-based biometrics that can operate in day and night time environments. The main contributions of this work are two-fold: First, a dual-band database is assembled that consists of visible and thermal profile face images. The thermal data was collected using a high definition middle-wave infrared (3-5 microns) camera that is capable of acquiring thermal imprints of human skin. Second, a fully automated, thermal imaging based ear detection method is developed for real-time segmentation of human ears in either day or night time environments. The proposed method is based on Haar features forming a cascaded AdaBoost classifier (our modified version of the original Viola-Jones approach1 that was designed to be applied mainly in visible band images). The main advantage of the proposed method, applied on our profile face image data set collected in the thermal-band, is that it is designed to reduce the learning time required by the original Viola-Jones method from several weeks to several hours. Unlike other approaches reported in the literature, which have been tested but not designed to operate in the thermal band, our method yields a high detection accuracy that reaches ~ 91.5%. Further analysis on our data set yielded that: (a) photometric normalization techniques do not directly improve ear detection performance. However, when using a certain photometric normalization technique (CLAHE) on falsely detected images, the detection rate improved by ~ 4%; (b) the high detection accuracy of our method did not degrade when we lowered down the original spatial resolution of thermal ear images. For example, even after using one third of the original spatial resolution (i.e. ~ 20% of the original computational time) of the thermal profile face images, the high ear detection accuracy of our method remained unaffected. This resulted also in speeding up the detection time of an ear image from 265 to 17 milliseconds per image. To the best of our knowledge this is the first time that the problem of human ear detection in the thermal band is being investigated in the open literature.

An optimized method for neurotransmitters and their metabolites analysis in mouse hypothalamus by high performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry.

PubMed

Yang, Zong-Lin; Li, Hui; Wang, Bing; Liu, Shu-Ying

2016-02-15

Neurotransmitters (NTs) and their metabolites are known to play an essential role in maintaining various physiological functions in nervous system. However, there are many difficulties in the detection of NTs together with their metabolites in biological samples. A new method for NTs and their metabolites detection by high performance liquid chromatography coupled with Q Exactive hybrid quadruple-orbitrap high-resolution accurate mass spectrometry (HPLC-HRMS) was established in this paper. This method was a great development of the applying of Q Exactive MS in the quantitative analysis. This method enabled a rapid quantification of ten compounds within 18min. Good linearity was obtained with a correlation coefficient above 0.99. The concentration range of the limit of detection (LOD) and the limit of quantitation (LOQ) level were 0.0008-0.05nmol/mL and 0.002-25.0nmol/mL respectively. Precisions (relative standard deviation, RSD) of this method were at 0.36-12.70%. Recovery ranges were between 81.83% and 118.04%. Concentrations of these compounds in mouse hypothalamus were detected by Q Exactive LC-MS technology with this method. Copyright © 2016 Elsevier B.V. All rights reserved.

SiPM electro-optical detection system noise suppression method

NASA Astrophysics Data System (ADS)

Bi, Xiangli; Yang, Suhui; Hu, Tao; Song, Yiheng

2014-11-01

In this paper, the single photon detection principle of Silicon Photomultipliers (SiPM) device is introduced. The main noise factors that infect the sensitivity of the electro-optical detection system are analyzed, including background light noise, detector dark noise, preamplifier noise and signal light noise etc. The Optical, electrical and thermodynamic methods are used to suppress the SiPM electro-optical detection system noise, which improved the response sensitivity of the detector. Using SiPM optoelectronic detector with a even high sensitivity, together with small field large aperture optical system, high cutoff narrow bandwidth filters, low-noise operational amplifier circuit, the modular design of functional circuit, semiconductor refrigeration technology, greatly improved the sensitivity of optical detection system, reduced system noise and achieved long-range detection of weak laser radiation signal. Theoretical analysis and experimental results show that the proposed methods are reasonable and efficient.

Detection and differentiation of wild-type and vaccine strains of canine distemper virus by a duplex reverse transcription polymerase chain reaction

PubMed Central

Dong, X. Y.; Li, W. H.; Zhu, J. L.; Liu, W. J.; Zhao, M. Q.; Luo, Y. W.; Chen, J. D.

2015-01-01

Canine distemper virus (CDV) is the cause of canine distemper (CD) which is a severe and highly contagious disease in dogs. In the present study, a duplex reverse transcription polymerase chain reaction (RT-PCR) method was developed for the detection and differentiation of wild-type and vaccine strains of CDV. Four primers were designed to detect and discriminate the two viruses by generating 638- and 781-bp cDNA products, respectively. Furthermore, the duplex RT-PCR method was used to detect 67 field samples suspected of CD from Guangdong province in China. Results showed that, 33 samples were to be wild-type-like. The duplex RT-PCR method exhibited high specificity and sensitivity which could be used to effectively detect and differentiate wild-type and vaccine CDV, indicating its use for clinical detection and epidemiological surveillance. PMID:27175171

Rapid identification of salmonella serotypes with stereo and hyperspectral microscope imaging Methods

USDA-ARS?s Scientific Manuscript database

The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

Rapid Identification of Salmonella Serotypes with Stereo and Hyperspectral Microscope Imaging Methods

USDA-ARS?s Scientific Manuscript database

The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

The advance of non-invasive detection methods in osteoarthritis

NASA Astrophysics Data System (ADS)

Dai, Jiao; Chen, Yanping

2011-06-01

Osteoarthritis (OA) is one of the most prevalent chronic diseases which badly affected the patients' living quality and economy. Detection and evaluation technology can provide basic information for early treatment. A variety of imaging methods in OA were reviewed, such as conventional X-ray, computed tomography (CT), ultrasound (US), magnetic resonance imaging (MRI) and near-infrared spectroscopy (NIRS). Among the existing imaging modalities, the spatial resolution of X-ray is extremely high; CT is a three-dimensional method, which has high density resolution; US as an evaluation method of knee OA discriminates lesions sensitively between normal cartilage and degenerative one; as a sensitive and nonionizing method, MRI is suitable for the detection of early OA, but the cost is too expensive for routine use; NIRS is a safe, low cost modality, and is also good at detecting early stage OA. In a word, each method has its own advantages, but NIRS is provided with broader application prospect, and it is likely to be used in clinical daily routine and become the golden standard for diagnostic detection.

Oil leakage detection for electric power equipment based on ultraviolet fluorescence effect

NASA Astrophysics Data System (ADS)

Zhang, Jing; Wang, Jian-hui; Xu, Bin; Huang, Zhi-dong; Huang, Lan-tao

2018-03-01

This paper presents a method to detect the oil leakage of high voltage power equipment based on ultraviolet fluorescence effect. The method exploits the principle that the insulating oil has the fluorescent effect under the irradiation of specific ultraviolet light. The emission spectrum of insulating oil under excitation light with different wavelengths is measured and analyzed first. On this basis, a portable oil leakage detective device for high voltage power equipment is designed and developed with a selected 365 nm ultraviolet as the excitation light and the low light level camera as the fluorescence image collector. Then, the feasibility of the proposed method and device in different conditions is experimentally verified in the laboratory environment. Finally, the developed oil leakage detective device is applied to 500 kV Xiamen substation and Quanzhou substation. And the results show that the device can detect the oil leakage of high voltage electrical equipment quickly and conveniently even under the condition of a slight oil leakage especially in the low light environment.

Development of a Tandem Repeat-Based Polymerase Chain Displacement Reaction Method for Highly Sensitive Detection of 'Candidatus Liberibacter asiaticus'.

PubMed

Lou, Binghai; Song, Yaqin; RoyChowdhury, Moytri; Deng, Chongling; Niu, Ying; Fan, Qijun; Tang, Yan; Zhou, Changyong

2018-02-01

Huanglongbing (HLB) is one of the most destructive diseases in citrus production worldwide. Early detection of HLB pathogens can facilitate timely removal of infected citrus trees in the field. However, low titer and uneven distribution of HLB pathogens in host plants make reliable detection challenging. Therefore, the development of effective detection methods with high sensitivity is imperative. This study reports the development of a novel method, tandem repeat-based polymerase chain displacement reaction (TR-PCDR), for the detection of 'Candidatus Liberibacter asiaticus', a widely distributed HLB-associated bacterium. A uniquely designed primer set (TR2-PCDR-F/TR2-PCDR-1R) and a thermostable Taq DNA polymerase mutant with strand displacement activity were used for TR-PCDR amplification. Performed in a regular thermal cycler, TR-PCDR could produce more than two amplicons after each amplification cycle. Sensitivity of the developed TR-PCDR was 10 copies of target DNA fragment. The sensitive level was proven to be 100× higher than conventional PCR and similar to real-time PCR. Data from the detection of 'Ca. L. asiaticus' with filed samples using the above three methods also showed similar results. No false-positive TR-PCDR amplification was observed from healthy citrus samples and water controls. These results thereby illustrated that the developed TR-PCDR method can be applied to the reliable, highly sensitive, and cost-effective detection of 'Ca. L. asiaticus'.

Highly Sensitive GMO Detection Using Real-Time PCR with a Large Amount of DNA Template: Single-Laboratory Validation.

PubMed

Mano, Junichi; Hatano, Shuko; Nagatomi, Yasuaki; Futo, Satoshi; Takabatake, Reona; Kitta, Kazumi

2018-03-01

Current genetically modified organism (GMO) detection methods allow for sensitive detection. However, a further increase in sensitivity will enable more efficient testing for large grain samples and reliable testing for processed foods. In this study, we investigated real-time PCR-based GMO detection methods using a large amount of DNA template. We selected target sequences that are commonly introduced into many kinds of GM crops, i.e., 35S promoter and nopaline synthase (NOS) terminator. This makes the newly developed method applicable to a wide range of GMOs, including some unauthorized ones. The estimated LOD of the new method was 0.005% of GM maize events; to the best of our knowledge, this method is the most sensitive among the GM maize detection methods for which the LOD was evaluated in terms of GMO content. A 10-fold increase in the DNA amount as compared with the amount used under common testing conditions gave an approximately 10-fold reduction in the LOD without PCR inhibition. Our method is applicable to various analytical samples, including processed foods. The use of other primers and fluorescence probes would permit highly sensitive detection of various recombinant DNA sequences besides the 35S promoter and NOS terminator.

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

PubMed Central

2017-01-01

Rapid automatic detection of the fiducial points—namely, the P wave, QRS complex, and T wave—is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs. PMID:29065613

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

PubMed

Park, Jeong-Seon; Lee, Sang-Woong; Park, Unsang

2017-01-01

Rapid automatic detection of the fiducial points-namely, the P wave, QRS complex, and T wave-is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.

Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

PubMed

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

Nested methylation-specific polymerase chain reaction cancer detection method

DOEpatents

Belinsky, Steven A [Albuquerque, NM; Palmisano, William A [Edgewood, NM

2007-05-08

A molecular marker-based method for monitoring and detecting cancer in humans. Aberrant methylation of gene promoters is a marker for cancer risk in humans. A two-stage, or "nested" polymerase chain reaction method is disclosed for detecting methylated DNA sequences at sufficiently high levels of sensitivity to permit cancer screening in biological fluid samples, such as sputum, obtained non-invasively. The method is for detecting the aberrant methylation of the p16 gene, O 6-methylguanine-DNA methyltransferase gene, Death-associated protein kinase gene, RAS-associated family 1 gene, or other gene promoters. The method offers a potentially powerful approach to population-based screening for the detection of lung and other cancers.

An Ultra-Trace Analysis Technique for SF6 Using Gas Chromatography with Negative Ion Chemical Ionization Mass Spectrometry.

PubMed

Jong, Edmund C; Macek, Paul V; Perera, Inoka E; Luxbacher, Kray D; McNair, Harold M

2015-07-01

Sulfur hexafluoride (SF6) is widely used as a tracer gas because of its detectability at low concentrations. This attribute of SF6 allows the quantification of both small-scale flows, such as leakage, and large-scale flows, such as atmospheric currents. SF6's high detection sensitivity also facilitates greater usage efficiency and lower operating cost for tracer deployments by reducing quantity requirements. The detectability of SF6 is produced by its high molecular electronegativity. This property provides a high potential for negative ion formation through electron capture thus naturally translating to selective detection using negative ion chemical ionization mass spectrometry (NCI-MS). This paper investigates the potential of using gas chromatography (GC) with NCI-MS for the detection of SF6. The experimental parameters for an ultra-trace SF6 detection method utilizing minimal customizations of the analytical instrument are detailed. A method for the detection of parts per trillion (ppt) level concentrations of SF6 for the purpose of underground ventilation tracer gas analysis was successfully developed in this study. The method utilized a Shimadzu gas chromatography with negative ion chemical ionization mass spectrometry system equipped with an Agilent J&W HP-porous layer open tubular column coated with an alumina oxide (Al2O3) S column. The method detection limit (MDL) analysis as defined by the Environmental Protection Agency of the tracer data showed the method MDL to be 5.2 ppt. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Environmental DNA as a new method for early detection of New Zealand mudsnails (Potamopyrgus antipodarum)

USGS Publications Warehouse

Goldberg, Caren S.; Sepulveda, Adam; Ray, Andrew; Baumgardt, Jeremy A.; Waits, Lisette P.

2013-01-01

Early detection of aquatic invasive species is a critical task for management of aquatic ecosystems. This task is hindered by the difficulty and cost of surveying aquatic systems thoroughly. The New Zealand mudsnail (Potamopyrgus antipodarum) is a small, invasive parthenogenic mollusk that can reach very high population densities and severely affects ecosystem functioning. To assist in the early detection of this invasive species, we developed and validated a highly sensitive environmental deoxyribonucleic acid (eDNA) assay. We used a dose–response laboratory experiment to investigate the relationship between New Zealand mudsnail density and eDNA detected through time. We documented that as few as 1 individual in 1.5 L of water for 2 d could be detected with this method, and that eDNA from this species may remain detectable for 21 to 44 d after mudsnail removal. We used the eDNA method to confirm the presence of New Zealand mudsnail eDNA at densities as low as 11 to 144 snails/m2 in a eutrophic 5th-order river. Combined, these results demonstrate the high potential for eDNA surveys to assist with early detection of a widely distributed invasive aquatic invertebrate.

Efficient synthesis of highly fluorescent carbon dots by microreactor method and their application in Fe3+ ion detection.

PubMed

Rao, Longshi; Tang, Yong; Li, Zongtao; Ding, Xinrui; Liang, Guanwei; Lu, Hanguang; Yan, Caiman; Tang, Kairui; Yu, Binhai

2017-12-01

Rapidly obtaining strong photoluminescence (PL) of carbon dots with high stability is crucial in all practical applications of carbon dots, such as cell imaging and biological detection. In this study, we proposed a rapid, continuous carbon dots synthesis technique by using a microreactor method. By taking advantage of the microreactor, we were able to rapidly synthesized CDs at a large scale in less than 5min, and a high quantum yield of 60.1% was achieved. This method is faster and more efficient than most of the previously reported methods. To explore the relationship between the microreactor structure and CDs PL properties, Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) were carried out. The results show the surface functional groups and element contents influence the PL emission. Subsequent ion detection experiments indicated that CDs are very suitable for use as nanoprobes for Fe 3+ ion detection, and the lowest detection limit for Fe 3+ is 0.239μM, which is superior to many other research studies. This rapid and simple synthesis method will not only aid the development of the quantum dots industrialization but also provide a powerful and portable tool for the rapid and continuous online synthesis of quantum dots supporting their application in cell imaging and safety detection. Copyright © 2017 Elsevier B.V. All rights reserved.

High effective algorithm of the detection and identification of substance using the noisy reflected THz pulse

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.; Tikhomirov, Vasily V.

2015-08-01

Principal limitations of the standard THz-TDS method for the detection and identification are demonstrated under real conditions (at long distance of about 3.5 m and at a high relative humidity more than 50%) using neutral substances thick paper bag, paper napkins and chocolate. We show also that the THz-TDS method detects spectral features of dangerous substances even if the THz signals were measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); silicon-based semiconductors were used as the samples. However, the integral correlation criteria, based on SDA method, allows us to detect the absence of dangerous substances in the neutral substances. The discussed algorithm shows high probability of the substance identification and a reliability of realization in practice, especially for security applications and non-destructive testing.

Method and apparatus for data sampling

DOEpatents

Odell, D.M.C.

1994-04-19

A method and apparatus for sampling radiation detector outputs and determining event data from the collected samples is described. The method uses high speed sampling of the detector output, the conversion of the samples to digital values, and the discrimination of the digital values so that digital values representing detected events are determined. The high speed sampling and digital conversion is performed by an A/D sampler that samples the detector output at a rate high enough to produce numerous digital samples for each detected event. The digital discrimination identifies those digital samples that are not representative of detected events. The sampling and discrimination also provides for temporary or permanent storage, either serially or in parallel, to a digital storage medium. 6 figures.

Airplane detection based on fusion framework by combining saliency model with Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Dou, Hao; Sun, Xiao; Li, Bin; Deng, Qianqian; Yang, Xubo; Liu, Di; Tian, Jinwen

2018-03-01

Aircraft detection from very high resolution remote sensing images, has gained more increasing interest in recent years due to the successful civil and military applications. However, several problems still exist: 1) how to extract the high-level features of aircraft; 2) locating objects within such a large image is difficult and time consuming; 3) A common problem of multiple resolutions of satellite images still exists. In this paper, inspirited by biological visual mechanism, the fusion detection framework is proposed, which fusing the top-down visual mechanism (deep CNN model) and bottom-up visual mechanism (GBVS) to detect aircraft. Besides, we use multi-scale training method for deep CNN model to solve the problem of multiple resolutions. Experimental results demonstrate that our method can achieve a better detection result than the other methods.

Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-06-17

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as "our previous method") using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as "our new method"). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal.

Self-Tuning Threshold Method for Real-Time Gait Phase Detection Based on Ground Contact Forces Using FSRs.

PubMed

Tang, Jing; Zheng, Jianbin; Wang, Yang; Yu, Lie; Zhan, Enqi; Song, Qiuzhi

2018-02-06

This paper presents a novel methodology for detecting the gait phase of human walking on level ground. The previous threshold method (TM) sets a threshold to divide the ground contact forces (GCFs) into on-ground and off-ground states. However, the previous methods for gait phase detection demonstrate no adaptability to different people and different walking speeds. Therefore, this paper presents a self-tuning triple threshold algorithm (STTTA) that calculates adjustable thresholds to adapt to human walking. Two force sensitive resistors (FSRs) were placed on the ball and heel to measure GCFs. Three thresholds (i.e., high-threshold, middle-threshold andlow-threshold) were used to search out the maximum and minimum GCFs for the self-adjustments of thresholds. The high-threshold was the main threshold used to divide the GCFs into on-ground and off-ground statuses. Then, the gait phases were obtained through the gait phase detection algorithm (GPDA), which provides the rules that determine calculations for STTTA. Finally, the STTTA reliability is determined by comparing the results between STTTA and Mariani method referenced as the timing analysis module (TAM) and Lopez-Meyer methods. Experimental results show that the proposed method can be used to detect gait phases in real time and obtain high reliability when compared with the previous methods in the literature. In addition, the proposed method exhibits strong adaptability to different wearers walking at different walking speeds.

PCR method of detecting pork in foods for verifying allergen labeling and for identifying hidden pork ingredients in processed foods.

PubMed

Tanabe, Soichi; Miyauchi, Eiji; Muneshige, Akemi; Mio, Kazuhiro; Sato, Chikara; Sato, Masahiko

2007-07-01

A PCR method to detect porcine DNA was developed for verifying the allergen labeling of foods and for identifying hidden pork ingredients in processed foods. The primer pair, F2/R1, was designed to detect the gene encoding porcine cytochrome b for the specific detection of pork with high sensitivity. The amplified DNA fragment (130 bp) was specifically detected from porcine DNA, while no amplification occurred with other species such as cattle, chicken, sheep, and horse. When the developed PCR method was used for investigating commercial food products, porcine DNA was clearly detected in those containing pork in the list of ingredients. In addition, 100 ppb of pork in heated gyoza (pork and vegetable dumpling) could be detected by this method. This method is rapid, specific and sensitive, making it applicable for detecting trace amounts of pork in processed foods.

A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection

DOE PAGES

Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max D.; ...

2015-06-24

This study proposes and analyzes a hyperspherical adaptive hierarchical sparse-grid method for detecting jump discontinuities of functions in high-dimensional spaces. The method is motivated by the theoretical and computational inefficiencies of well-known adaptive sparse-grid methods for discontinuity detection. Our novel approach constructs a function representation of the discontinuity hypersurface of an N-dimensional discontinuous quantity of interest, by virtue of a hyperspherical transformation. Then, a sparse-grid approximation of the transformed function is built in the hyperspherical coordinate system, whose value at each point is estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of the hypersurface, the newmore » technique can identify jump discontinuities with significantly reduced computational cost, compared to existing methods. In addition, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. Rigorous complexity analyses of the new method are provided as are several numerical examples that illustrate the effectiveness of the approach.« less

A hyper-spherical adaptive sparse-grid method for high-dimensional discontinuity detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max D.

This work proposes and analyzes a hyper-spherical adaptive hierarchical sparse-grid method for detecting jump discontinuities of functions in high-dimensional spaces is proposed. The method is motivated by the theoretical and computational inefficiencies of well-known adaptive sparse-grid methods for discontinuity detection. Our novel approach constructs a function representation of the discontinuity hyper-surface of an N-dimensional dis- continuous quantity of interest, by virtue of a hyper-spherical transformation. Then, a sparse-grid approximation of the transformed function is built in the hyper-spherical coordinate system, whose value at each point is estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of themore » hyper-surface, the new technique can identify jump discontinuities with significantly reduced computational cost, compared to existing methods. Moreover, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. Rigorous error estimates and complexity analyses of the new method are provided as are several numerical examples that illustrate the effectiveness of the approach.« less

Damage detection and locating using tone burst and continuous excitation modulation method

NASA Astrophysics Data System (ADS)

Li, Zheng; Wang, Zhi; Xiao, Li; Qu, Wenzhong

2014-03-01

Among structural health monitoring techniques, nonlinear ultrasonic spectroscopy methods are found to be effective diagnostic approach to detecting nonlinear damage such as fatigue crack, due to their sensitivity to incipient structural changes. In this paper, a nonlinear ultrasonic modulation method was developed to detect and locate a fatigue crack on an aluminum plate. The method is different with nonlinear wave modulation method which recognizes the modulation of low-frequency vibration and high-frequency ultrasonic wave; it recognizes the modulation of tone burst and high-frequency ultrasonic wave. In the experiment, a Hanning window modulated sinusoidal tone burst and a continuous sinusoidal excitation were simultaneously imposed on the PZT array which was bonded on the surface of an aluminum plate. The modulations of tone burst and continuous sinusoidal excitation was observed in different actuator-sensor paths, indicating the presence and location of fatigue crack. The results of experiments show that the proposed method is capable of detecting and locating the fatigue crack successfully.

Towards high-throughput molecular detection of Plasmodium: new approaches and molecular markers

PubMed Central

Steenkeste, Nicolas; Incardona, Sandra; Chy, Sophy; Duval, Linda; Ekala, Marie-Thérèse; Lim, Pharath; Hewitt, Sean; Sochantha, Tho; Socheat, Doung; Rogier, Christophe; Mercereau-Puijalon, Odile; Fandeur, Thierry; Ariey, Frédéric

2009-01-01

Background Several strategies are currently deployed in many countries in the tropics to strengthen malaria control toward malaria elimination. To measure the impact of any intervention, there is a need to detect malaria properly. Mostly, decisions still rely on microscopy diagnosis. But sensitive diagnosis tools enabling to deal with a large number of samples are needed. The molecular detection approach offers a much higher sensitivity, and the flexibility to be automated and upgraded. Methods Two new molecular methods were developed: dot18S, a Plasmodium-specific nested PCR based on the 18S rRNA gene followed by dot-blot detection of species by using species-specific probes and CYTB, a Plasmodium-specific nested PCR based on cytochrome b gene followed by species detection using SNP analysis. The results were compared to those obtained with microscopic examination and the "standard" 18S rRNA gene based nested PCR using species specific primers. 337 samples were diagnosed. Results Compared to the microscopy the three molecular methods were more sensitive, greatly increasing the estimated prevalence of Plasmodium infection, including P. malariae and P. ovale. A high rate of mixed infections was uncovered with about one third of the villagers infected with more than one malaria parasite species. Dot18S and CYTB sensitivity outranged the "standard" nested PCR method, CYTB being the most sensitive. As a consequence, compared to the "standard" nested PCR method for the detection of Plasmodium spp., the sensitivity of dot18S and CYTB was respectively 95.3% and 97.3%. Consistent detection of Plasmodium spp. by the three molecular methods was obtained for 83% of tested isolates. Contradictory results were mostly related to detection of Plasmodium malariae and Plasmodium ovale in mixed infections, due to an "all-or-none" detection effect at low-level parasitaemia. Conclusion A large reservoir of asymptomatic infections was uncovered using the molecular methods. Dot18S and CYTB, the new methods reported herein are highly sensitive, allow parasite DNA extraction as well as genus- and species-specific diagnosis of several hundreds of samples, and are amenable to high-throughput scaling up for larger sample sizes. Such methods provide novel information on malaria prevalence and epidemiology and are suited for active malaria detection. The usefulness of such sensitive malaria diagnosis tools, especially in low endemic areas where eradication plans are now on-going, is discussed in this paper. PMID:19402894

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

PubMed

Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

2014-04-10

Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

PubMed Central

2014-01-01

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145

Precisely detecting atomic position of atomic intensity images.

PubMed

Wang, Zhijun; Guo, Yaolin; Tang, Sai; Li, Junjie; Wang, Jincheng; Zhou, Yaohe

2015-03-01

We proposed a quantitative method to detect atomic position in atomic intensity images from experiments such as high-resolution transmission electron microscopy, atomic force microscopy, and simulation such as phase field crystal modeling. The evaluation of detection accuracy proves the excellent performance of the method. This method provides a chance to precisely determine atomic interactions based on the detected atomic positions from the atomic intensity image, and hence to investigate the related physical, chemical and electrical properties. Copyright © 2014 Elsevier B.V. All rights reserved.

High sensitivity leak detection method and apparatus

DOEpatents

Myneni, Ganapatic R.

1994-01-01

An improved leak detection method is provided that utilizes the cyclic adsorption and desorption of accumulated helium on a non-porous metallic surface. The method provides reliable leak detection at superfluid helium temperatures. The zero drift that is associated with residual gas analyzers in common leak detectors is virtually eliminated by utilizing a time integration technique. The sensitivity of the apparatus of this disclosure is capable of detecting leaks as small as 1.times.10.sup.-18 atm cc sec.sup.-1.

High sensitivity leak detection method and apparatus

DOEpatents

Myneni, G.R.

1994-09-06

An improved leak detection method is provided that utilizes the cyclic adsorption and desorption of accumulated helium on a non-porous metallic surface. The method provides reliable leak detection at superfluid helium temperatures. The zero drift that is associated with residual gas analyzers in common leak detectors is virtually eliminated by utilizing a time integration technique. The sensitivity of the apparatus of this disclosure is capable of detecting leaks as small as 1 [times] 10[sup [minus]18] atm cc sec[sup [minus]1]. 2 figs.

A New Real-Time Cycle Slip Detection and Repair Method under High Ionospheric Activity for a Triple-Frequency GPS/BDS Receiver.

PubMed

Liu, Wanke; Jin, Xueyuan; Wu, Mingkui; Hu, Jie; Wu, Yun

2018-02-01

Cycle slip detection and repair is a prerequisite for high-precision global navigation satellite system (GNSS)-based positioning. With the modernization and development of GNSS systems, more satellites are available to transmit triple-frequency signals, which allows the introduction of additional linear combinations and provides new opportunities for cycle slip detection and repair. In this paper, we present a new real-time cycle slip detection and repair method under high ionospheric activity for undifferenced Global Positioning System (GPS)/BeiDou Navigation Satellite System (BDS) triple-frequency observations collected with a single receiver. First, three optimal linearly independent geometry-free pseudorange minus phase combinations are selected to correctly and uniquely determine the cycle slips on the original triple-frequency carrier phase observations. Then, a second-order time-difference algorithm is employed for the pseudorange minus phase combinations to mitigate the impact of between-epoch ionospheric residuals on cycle slip detection, which is especially beneficial under high ionospheric activity. The performance of the approach is verified with static GPS/BDS triple-frequency observations that are collected with a 30 s sampling interval under active ionospheric conditions, and observations are manually inserted with simulated cycle slips. The results show that the method can correctly detect and repair cycle slips at a resolution as small as 1 cycle. Moreover, kinematic data collected from car-driven and airborne experiments are also processed to verify the performance of the method. The experimental results also demonstrate that the method is effective in processing kinematic data.

A New Real-Time Cycle Slip Detection and Repair Method under High Ionospheric Activity for a Triple-Frequency GPS/BDS Receiver

PubMed Central

Liu, Wanke; Wu, Mingkui; Hu, Jie; Wu, Yun

2018-01-01

Cycle slip detection and repair is a prerequisite for high-precision global navigation satellite system (GNSS)-based positioning. With the modernization and development of GNSS systems, more satellites are available to transmit triple-frequency signals, which allows the introduction of additional linear combinations and provides new opportunities for cycle slip detection and repair. In this paper, we present a new real-time cycle slip detection and repair method under high ionospheric activity for undifferenced Global Positioning System (GPS)/BeiDou Navigation Satellite System (BDS) triple-frequency observations collected with a single receiver. First, three optimal linearly independent geometry-free pseudorange minus phase combinations are selected to correctly and uniquely determine the cycle slips on the original triple-frequency carrier phase observations. Then, a second-order time-difference algorithm is employed for the pseudorange minus phase combinations to mitigate the impact of between-epoch ionospheric residuals on cycle slip detection, which is especially beneficial under high ionospheric activity. The performance of the approach is verified with static GPS/BDS triple-frequency observations that are collected with a 30 s sampling interval under active ionospheric conditions, and observations are manually inserted with simulated cycle slips. The results show that the method can correctly detect and repair cycle slips at a resolution as small as 1 cycle. Moreover, kinematic data collected from car-driven and airborne experiments are also processed to verify the performance of the method. The experimental results also demonstrate that the method is effective in processing kinematic data. PMID:29389879

Highly Sensitive Naked-Eye Assay for Enterovirus 71 Detection Based on Catalytic Nanoparticle Aggregation and Immunomagnetic Amplification.

PubMed

Xiong, Ling-Hong; He, Xuewen; Xia, Junjie; Ma, Hanwu; Yang, Fan; Zhang, Qian; Huang, Dana; Chen, Long; Wu, Chunli; Zhang, Xiaomin; Zhao, Zheng; Wan, Chengsong; Zhang, Renli; Cheng, Jinquan

2017-05-03

Development of sensitive, convenient, and cost-effective virus detection product is of great significance to meet the growing demand of clinical diagnosis at the early stage of virus infection. Herein, a naked-eye readout of immunoassay by means of virion bridged catalase-mediated in situ reduction of gold ions and growth of nanoparticles, has been successfully proposed for rapid visual detection of Enterovirus 71 (EV71). Through tailoring the morphologies of the produced gold nanoparticles (GNPs) varying between dispersion and aggregation, a distinguishing color changing was ready for observation. This colorimetric detection assay, by further orchestrating the efficient magnetic enrichment and the high catalytic activity of enzyme, is managed to realize highly sensitive detection of EV71 virions with the limit of detection (LOD) down to 0.65 ng/mL. Our proposed method showed a much lower LOD value than the commercial ELISA for EV71 virion detection. Comparing to the current clinical gold standard polymerase chain reaction (PCR) method, our strategy provided the same diagnostic outcomes after testing real clinical samples. Besides, this strategy has no need of complicated sample pretreatment or expensive instruments. Our presented naked-eye immunoassay method holds a promising prospect for the early detection of virus-infectious disease especially in resource-constrained settings.

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.

Potential of cross-priming amplification and DNA-based lateral-flow strip biosensor for rapid on-site GMO screening.

PubMed

Huang, Xin; Zhai, Congcong; You, Qimin; Chen, Hongjun

2014-07-01

The requirement to monitor the presence of genetically modified organisms (GMO) in a variety of marked products has generated an increasing demand for reliable, rapid, and time and cost-effective analytical methods. Here we report an on-site method for rapid detection of cauliflower mosaic virus promoter (CaMV 35S), a common element present in most GMO, using cross-priming amplification (CPA) technology. Detection was achieved using a DNA-based contamination-proof strip biosensor. The limit of detection was 30 copies for the pBI121 plasmid containing the CaMV 35S gene. The certified reference sample of GM maize line MON810 was detectable even at the low relative mass concentration of 0.05%. The developed CPA method had high specificity for the CaMV 35S gene, as compared with other GM lines not containing this gene and non-GM products. The method was further validated using nine real-world samples, and the results were confirmed by real-time PCR analysis. Because of its simplicity, rapidity, and high sensitivity, this method of detecting the CaMV 35S gene has great commercial prospects for rapid GMO screening of high-consumption food and agriculture products.

Ricin detection: tracking active toxin.

PubMed

Bozza, William P; Tolleson, William H; Rivera Rosado, Leslie A; Zhang, Baolin

2015-01-01

Ricin is a plant toxin with high bioterrorism potential due to its natural abundance and potency in inducing cell death. Early detection of the active toxin is essential for developing appropriate countermeasures. Here we review concepts for designing ricin detection methods, including mechanism of action of the toxin, advantages and disadvantages of current detection assays, and perspectives on the future development of rapid and reliable methods for detecting ricin in environmental samples. Published by Elsevier Inc.

Highly sensitive detection of DNA methylation levels by using a quantum dot-based FRET method

NASA Astrophysics Data System (ADS)

Ma, Yunfei; Zhang, Honglian; Liu, Fangming; Wu, Zhenhua; Lu, Shaohua; Jin, Qinghui; Zhao, Jianlong; Zhong, Xinhua; Mao, Hongju

2015-10-01

DNA methylation is the most frequently studied epigenetic modification that is strongly involved in genomic stability and cellular plasticity. Aberrant changes in DNA methylation status are ubiquitous in human cancer and the detection of these changes can be informative for cancer diagnosis. Herein, we reported a facile quantum dot-based (QD-based) fluorescence resonance energy transfer (FRET) technique for the detection of DNA methylation. The method relies on methylation-sensitive restriction enzymes for the differential digestion of genomic DNA based on its methylation status. Digested DNA is then subjected to PCR amplification for the incorporation of Alexa Fluor-647 (A647) fluorophores. DNA methylation levels can be detected qualitatively through gel analysis and quantitatively by the signal amplification from QDs to A647 during FRET. Furthermore, the methylation levels of three tumor suppressor genes, PCDHGB6, HOXA9 and RASSF1A, in 20 lung adenocarcinoma and 20 corresponding adjacent nontumorous tissue (NT) samples were measured to verify the feasibility of the QD-based FRET method and a high sensitivity for cancer detection (up to 90%) was achieved. Our QD-based FRET method is a convenient, continuous and high-throughput method, and is expected to be an alternative for detecting DNA methylation as a biomarker for certain human cancers.DNA methylation is the most frequently studied epigenetic modification that is strongly involved in genomic stability and cellular plasticity. Aberrant changes in DNA methylation status are ubiquitous in human cancer and the detection of these changes can be informative for cancer diagnosis. Herein, we reported a facile quantum dot-based (QD-based) fluorescence resonance energy transfer (FRET) technique for the detection of DNA methylation. The method relies on methylation-sensitive restriction enzymes for the differential digestion of genomic DNA based on its methylation status. Digested DNA is then subjected to PCR amplification for the incorporation of Alexa Fluor-647 (A647) fluorophores. DNA methylation levels can be detected qualitatively through gel analysis and quantitatively by the signal amplification from QDs to A647 during FRET. Furthermore, the methylation levels of three tumor suppressor genes, PCDHGB6, HOXA9 and RASSF1A, in 20 lung adenocarcinoma and 20 corresponding adjacent nontumorous tissue (NT) samples were measured to verify the feasibility of the QD-based FRET method and a high sensitivity for cancer detection (up to 90%) was achieved. Our QD-based FRET method is a convenient, continuous and high-throughput method, and is expected to be an alternative for detecting DNA methylation as a biomarker for certain human cancers. Electronic supplementary information (ESI) available: Synthesis of CdSe/CdS/ZnS core/shell/shell QDs. Sequences of primers used for amplifying the promoter regions in bisulfate-modified DNA. Comparison of detected methylation levels in different gene promoters using the QD-based FRET method versus bisulfite pyrosequencing. Methylation levels of the RASSF1A gene in one pair of NT and cancer samples as indicated by pyrosequencing. Theoretical calculation of the Förster distance R0. See DOI: 10.1039/c5nr04956c

Wavelength band selection method for multispectral target detection.

PubMed

Karlholm, Jörgen; Renhorn, Ingmar

2002-11-10

A framework is proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data. Using the results from the detection theory we derive a cost function that is minimized by a set of spectral bands optimal in terms of detection performance for discrimination between a class of small rare targets and clutter with known spectral distribution. The method may be used, e.g., in the design of multispectral infrared search and track and electro-optical missile warning sensors, where a low false-alarm rate and a high-detection probability for detection of small targets against a clutter background are of critical importance, but the required high frame rate prevents the use of hyperspectral sensors.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

PubMed Central

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells. PMID:26066315

Detection of anabolic and androgenic steroids and/or their esters in horse hair using ultra-high performance liquid chromatography-high resolution mass spectrometry.

PubMed

Kwok, Karen Y; Choi, Timmy L S; Kwok, Wai Him; Wong, Jenny K Y; Wan, Terence S M

2017-04-14

Anabolic and androgenic steroids (AASs) are a class of prohibited substances banned in horseracing at all times. The common approach for controlling the misuse of AASs in equine sports is by detecting the presence of AASs and/or their metabolites in urine and blood samples using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). This approach, however, often falls short as the duration of effect for many AASs are longer than their detection time in both urine and blood. As a result, there is a high risk that such AASs could escape detection in their official race-day samples although they may have been used during the long period of training. Hair analysis, on the other hand, can afford significantly longer detection windows. In addition, the identification of synthetic ester derivatives of AASs in hair, particularly for the endogenous ones, can provide unequivocal proof of their exogenous origin. This paper describes the development of a sensitive method (at sub to low parts-per-billion or ppb levels) for detecting 48 AASs and/or their esters in horse hair using ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Decontaminated horse hair was pulverised and subjected to in-situ liquid-liquid extraction in a mixture of hexane - ethyl acetate (7:3, v/v) and phosphate buffer (0.1M, pH 9.5), followed by additional clean-up using mixed-mode solid-phase extraction. The final extract was analysed using UHPLC-HRMS in the positive electrospray ionisation (ESI) mode with both full scan and parallel reaction monitoring (PRM). This method was validated for qualitative identification purposes. Validation data, including method specificity, method sensitivity, extraction recovery, method precision and matrix effect are presented. Method applicability was demonstrated by the successful detection and confirmation of testosterone propionate in a referee hair sample. To our knowledge, this was the first report of a comprehensive screening method for detecting as many as 48 AASs and/or their esters in horse hair. Moreover, retrospective analysis of non-targeted AASs and/or their esters was made feasible by re-examining the full scan UHPLC-HRMS data acquired. Copyright © 2017 Elsevier B.V. All rights reserved.

Method and Apparatus for Reading Two Dimensional Identification Symbols Using Radar Techniques

NASA Technical Reports Server (NTRS)

Schramm, Harry F., Jr. (Inventor); Roxby, Donald L. (Inventor)

2003-01-01

A method and apparatus are provided for sensing two-dimensional identification marks provided on a substrate or embedded within a substrate below a surface of the substrate. Micropower impulse radar is used to transmit a high risetime, short duration pulse to a focussed radar target area of the substrate having the two dimensional identification marks. The method further includes the steps of listening for radar echoes returned from the identification marks during a short listening period window occurring a predetermined time after transmission of the radar pulse. If radar echoes are detected, an image processing step is carried out. If no radar echoes are detected, the method further includes sequentially transmitting further high risetime, short duration pulses, and listening for radar echoes from each of said further pulses after different elapsed times for each of the further pulses until radar echoes are detected. When radar echoes are detected, data based on the detected echoes is processed to produce an image of the identification marks.

A rapid low-cost high-density DNA-based multi-detection test for routine inspection of meat species.

PubMed

Lin, Chun Chi; Fung, Lai Ling; Chan, Po Kwok; Lee, Cheuk Man; Chow, Kwok Fai; Cheng, Shuk Han

2014-02-01

The increasing occurrence of food frauds suggests that species identification should be part of food authentication. Current molecular-based species identification methods have their own limitations or drawbacks, such as relatively time-consuming experimental steps, expensive equipment and, in particular, these methods cannot identify mixed species in a single experiment. This project proposes an improved method involving PCR amplification of the COI gene and detection of species-specific sequences by hybridisation. Major innovative breakthrough lies in the detection of multiple species, including pork, beef, lamb, horse, cat, dog and mouse, from a mixed sample within a single experiment. The probes used are species-specific either in sole or mixed species samples. As little as 5 pg of DNA template in the PCR is detectable in the proposed method. By designing species-specific probes and adopting reverse dot blot hybridisation and flow-through hybridisation, a low-cost high-density DNA-based multi-detection test suitable for routine inspection of meat species was developed. © 2013.

Sensitivity and accuracy of high-throughput metabarcoding methods used to describe aquatic communities for early detection of invasve fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize Type I and II detection errors. Given the great expense and effort associated with morphological identifi...

Assisted inhibition effect of acetylcholinesterase with n-octylphosphonic acid and application in high sensitive detection of organophosphorous pesticides by matrix-assisted laser desorption/ionization Fourier transform mass spectrometry.

PubMed

Cai, Tingting; Zhang, Li; Wang, Haoyang; Zhang, Jing; Guo, Yinlong

2011-11-14

A simple and practical approach to improve the sensitivity of acetylcholinesterase (AChE)-inhibited method has been developed for monitoring organophosphorous (OP) pesticide residues. In this work, matrix-assisted laser desorption/ionization Fourier transform mass spectrometry (MALDI-FTMS) was used to detect AChE activity. Due to its good salt-tolerance and low sample consumption, MALDI-FTMS facilitates rapid and high-throughput screening of OP pesticides. Here we describe a new method to obtain low detection limits via employing external reagents. Among candidate compounds, n-octylphosphonic acid (n-Octyl-PA) displays assistant effect to enhance AChE inhibition by OP pesticides. In presence of n-Octyl-PA, the percentages of AChE inhibition still kept correlation with OP pesticide concentrations. The detection limits were improved significantly even by 10(2)-10(3) folds in comparison with conventional enzyme-inhibited methods. Different detection limits of OP pesticides with different toxicities were as low as 0.005 μg L(-1) for high toxic pesticides and 0.05 μg L(-1) for low toxic pesticides. Besides, the reliability of results from this method to analyze cowpea samples had been demonstrated by liquid-chromatography tandem mass spectrometry (LC-MS/MS). The application of this commercial available assistant agent shows great promise to detect OP compounds in complicated biological matrix and broadens the mind for high sensitivity detection of OP pesticide residues in agricultural products. Copyright © 2011 Elsevier B.V. All rights reserved.

Low-resolution ship detection from high-altitude aerial images

NASA Astrophysics Data System (ADS)

Qi, Shengxiang; Wu, Jianmin; Zhou, Qing; Kang, Minyang

2018-02-01

Ship detection from optical images taken by high-altitude aircrafts such as unmanned long-endurance airships and unmanned aerial vehicles has broad applications in marine fishery management, ship monitoring and vessel salvage. However, the major challenge is the limited capability of information processing on unmanned high-altitude platforms. Furthermore, in order to guarantee the wide detection range, unmanned aircrafts generally cruise at high altitudes, resulting in imagery with low-resolution targets and strong clutters suffered by heavy clouds. In this paper, we propose a low-resolution ship detection method to extract ships from these high-altitude optical images. Inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, we propose the facet kernel filtering to rapidly suppress cluttered backgrounds and delineate candidate target regions from the sea surface. Then, the principal component analysis (PCA) is used to compute the orientation of the target axis, followed by a simplified histogram of oriented gradient (HOG) descriptor to characterize the ship shape property. Finally, support vector machine (SVM) is applied to discriminate real targets and false alarms. Experimental results show that the proposed method actually has high efficiency in low-resolution ship detection.

Determination of dasatinib in the tablet dosage form by ultra high performance liquid chromatography, capillary zone electrophoresis, and sequential injection analysis.

PubMed

Gonzalez, Aroa Garcia; Taraba, Lukáš; Hraníček, Jakub; Kozlík, Petr; Coufal, Pavel

2017-01-01

Dasatinib is a novel oral prescription drug proposed for treating adult patients with chronic myeloid leukemia. Three analytical methods, namely ultra high performance liquid chromatography, capillary zone electrophoresis, and sequential injection analysis, were developed, validated, and compared for determination of the drug in the tablet dosage form. The total analysis time of optimized ultra high performance liquid chromatography and capillary zone electrophoresis methods was 2.0 and 2.2 min, respectively. Direct ultraviolet detection with detection wavelength of 322 nm was employed in both cases. The optimized sequential injection analysis method was based on spectrophotometric detection of dasatinib after a simple colorimetric reaction with folin ciocalteau reagent forming a blue-colored complex with an absorbance maximum at 745 nm. The total analysis time was 2.5 min. The ultra high performance liquid chromatography method provided the lowest detection and quantitation limits and the most precise and accurate results. All three newly developed methods were demonstrated to be specific, linear, sensitive, precise, and accurate, providing results satisfactorily meeting the requirements of the pharmaceutical industry, and can be employed for the routine determination of the active pharmaceutical ingredient in the tablet dosage form. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DNA Extraction Method Affects the Detection of a Fungal Pathogen in Formalin-Fixed Specimens Using qPCR.

PubMed

Adams, Andrea J; LaBonte, John P; Ball, Morgan L; Richards-Hrdlicka, Kathryn L; Toothman, Mary H; Briggs, Cheryl J

2015-01-01

Museum collections provide indispensable repositories for obtaining information about the historical presence of disease in wildlife populations. The pathogenic amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd) has played a significant role in global amphibian declines, and examining preserved specimens for Bd can improve our understanding of its emergence and spread. Quantitative PCR (qPCR) enables Bd detection with minimal disturbance to amphibian skin and is significantly more sensitive to detecting Bd than histology; therefore, developing effective qPCR methodologies for detecting Bd DNA in formalin-fixed specimens can provide an efficient and effective approach to examining historical Bd emergence and prevalence. Techniques for detecting Bd in museum specimens have not been evaluated for their effectiveness in control specimens that mimic the conditions of animals most likely to be encountered in museums, including those with low pathogen loads. We used American bullfrogs (Lithobates catesbeianus) of known infection status to evaluate the success of qPCR to detect Bd in formalin-fixed specimens after three years of ethanol storage. Our objectives were to compare the most commonly used DNA extraction method for Bd (PrepMan, PM) to Macherey-Nagel DNA FFPE (MN), test optimizations for Bd detection with PM, and provide recommendations for maximizing Bd detection. We found that successful detection is relatively high (80-90%) when Bd loads before formalin fixation are high, regardless of the extraction method used; however, at lower infection levels, detection probabilities were significantly reduced. The MN DNA extraction method increased Bd detection by as much as 50% at moderate infection levels. Our results indicate that, for animals characterized by lower pathogen loads (i.e., those most commonly encountered in museum collections), current methods may underestimate the proportion of Bd-infected amphibians. Those extracting DNA from archived museum specimens should ensure that the techniques they are using are known to provide high-quality throughput DNA for later analysis.

Electrochemical and Infrared Absorption Spectroscopy Detection of SF₆ Decomposition Products.

PubMed

Dong, Ming; Zhang, Chongxing; Ren, Ming; Albarracín, Ricardo; Ye, Rixin

2017-11-15

Sulfur hexafluoride (SF₆) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF₆ decomposition and ultimately generates several types of decomposition products. These SF₆ decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF₆ decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF₆ gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF₆ decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF₆ gas decomposition and is verified to reliably and accurately detect the gas components and concentrations.

[Rapid detection of caffeine in blood by freeze-out extraction].

PubMed

Bekhterev, V N; Gavrilova, S N; Kozina, E P; Maslakov, I V

2010-01-01

A new method for the detection of caffeine in blood has been proposed based on the combination of extraction and freezing-out to eliminate the influence of sample matrix. Metrological characteristics of the method are presented. Selectivity of detection is achieved by optimal conditions of analysis by high performance liquid chromatography. The method is technically simple and cost-efficient, it ensures rapid performance of the studies.

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding

PubMed Central

Zeng, Jinle; Chang, Baohua; Du, Dong; Hong, Yuxiang; Chang, Shuhe; Zou, Yirong

2016-01-01

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process. PMID:27649173

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding.

PubMed

Zeng, Jinle; Chang, Baohua; Du, Dong; Hong, Yuxiang; Chang, Shuhe; Zou, Yirong

2016-09-13

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process.

Rapid detection and differentiation of Clonorchis sinensis and Opisthorchis viverrini using real-time PCR and high resolution melting analysis.

PubMed

Cai, Xian-Quan; Yu, Hai-Qiong; Li, Rong; Yue, Qiao-Yun; Liu, Guo-Hua; Bai, Jian-Shan; Deng, Yan; Qiu, De-Yi; Zhu, Xing-Quan

2014-01-01

Clonorchis sinensis and Opisthorchis viverrini are both important fish-borne pathogens, causing serious public health problem in Asia. The present study developed an assay integrating real-time PCR and high resolution melting (HRM) analysis for the specific detection and rapid identification of C. sinensis and O. viverrini. Primers targeting COX1 gene were highly specific for these liver flukes, as evidenced by the negative amplification of closely related trematodes. Assays using genomic DNA extracted from the two flukes yielded specific amplification and their identity was confirmed by sequencing, having the accuracy of 100% in reference to conventional methods. The assay was proved to be highly sensitive with a detection limit below 1 pg of purified genomic DNA, 5 EPG, or 1 metacercaria of C. sinensis. Moreover, C. sinensis and O. viverrini were able to be differentiated by their HRM profiles. The method can reduce labor of microscopic examination and the contamination of agarose electrophoresis. Moreover, it can differentiate these two flukes which are difficult to be distinguished using other methods. The established method provides an alternative tool for rapid, simple, and duplex detection of C. sinensis and O. viverrini.

A feasibility study of damage detection in beams using high-speed camera (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wan, Chao; Yuan, Fuh-Gwo

2017-04-01

In this paper a method for damage detection in beam structures using high-speed camera is presented. Traditional methods of damage detection in structures typically involve contact (i.e., piezoelectric sensor or accelerometer) or non-contact sensors (i.e., laser vibrometer) which can be costly and time consuming to inspect an entire structure. With the popularity of the digital camera and the development of computer vision technology, video cameras offer a viable capability of measurement including higher spatial resolution, remote sensing and low-cost. In the study, a damage detection method based on the high-speed camera was proposed. The system setup comprises a high-speed camera and a line-laser which can capture the out-of-plane displacement of a cantilever beam. The cantilever beam with an artificial crack was excited and the vibration process was recorded by the camera. A methodology called motion magnification, which can amplify subtle motions in a video is used for modal identification of the beam. A finite element model was used for validation of the proposed method. Suggestions for applications of this methodology and challenges in future work will be discussed.

Highly sensitive and selective detection of dopamine using one-pot synthesized highly photoluminescent silicon nanoparticles.

PubMed

Zhang, Xiaodong; Chen, Xiaokai; Kai, Siqi; Wang, Hong-Yin; Yang, Jingjing; Wu, Fu-Gen; Chen, Zhan

2015-03-17

A simple and highly efficient method for dopamine (DA) detection using water-soluble silicon nanoparticles (SiNPs) was reported. The SiNPs with a high quantum yield of 23.6% were synthesized by using a one-pot microwave-assisted method. The fluorescence quenching capability of a variety of molecules on the synthesized SiNPs has been tested; only DA molecules were found to be able to quench the fluorescence of these SiNPs effectively. Therefore, such a quenching effect can be used to selectively detect DA. All other molecules tested have little interference with the dopamine detection, including ascorbic acid, which commonly exists in cells and can possibly affect the dopamine detection. The ratio of the fluorescence intensity difference between the quenched and unquenched cases versus the fluorescence intensity without quenching (ΔI/I) was observed to be linearly proportional to the DA analyte concentration in the range from 0.005 to 10.0 μM, with a detection limit of 0.3 nM (S/N = 3). To the best of our knowledge, this is the lowest limit for DA detection reported so far. The mechanism of fluorescence quenching is attributed to the energy transfer from the SiNPs to the oxidized dopamine molecules through Förster resonance energy transfer. The reported method of SiNP synthesis is very simple and cheap, making the above sensitive and selective DA detection approach using SiNPs practical for many applications.

Bioanalytical Applications of Fluorescence Line-Narrowing and Non-Line-Narrowing Spectroscopy Interfaced with Capillary Electrophoresis and High-Performance Liquid Chromatography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, Kenneth Paul

Capillary electrophoresis (CE) and high-performance liquid chromatography (HPLC) are widely used analytical separation techniques with many applications in chemical, biochemical, and biomedical sciences. Conventional analyte identification in these techniques is based on retention/migration times of standards; requiring a high degree of reproducibility, availability of reliable standards, and absence of coelution. From this, several new information-rich detection methods (also known as hyphenated techniques) are being explored that would be capable of providing unambiguous on-line identification of separating analytes in CE and HPLC. As further discussed, a number of such on-line detection methods have shown considerable success, including Raman, nuclear magnetic resonancemore » (NMR), mass spectrometry (MS), and fluorescence line-narrowing spectroscopy (FLNS). In this thesis, the feasibility and potential of combining the highly sensitive and selective laser-based detection method of FLNS with analytical separation techniques are discussed and presented. A summary of previously demonstrated FLNS detection interfaced with chromatography and electrophoresis is given, and recent results from on-line FLNS detection in CE (CE-FLNS), and the new combination of HPLC-FLNS, are shown.« less

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

Development of bacteria-based bioassays for arsenic detection in natural waters.

PubMed

Diesel, Elizabeth; Schreiber, Madeline; van der Meer, Jan Roelof

2009-06-01

Arsenic contamination of natural waters is a worldwide concern, as the drinking water supplies for large populations can have high concentrations of arsenic. Traditional techniques to detect arsenic in natural water samples can be costly and time-consuming; therefore, robust and inexpensive methods to detect arsenic in water are highly desirable. Additionally, methods for detecting arsenic in the field have been greatly sought after. This article focuses on the use of bacteria-based assays as an emerging method that is both robust and inexpensive for the detection of arsenic in groundwater both in the field and in the laboratory. The arsenic detection elements in bacteria-based bioassays are biosensor-reporter strains; genetically modified strains of, e.g., Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Rhodopseudomonas palustris. In response to the presence of arsenic, such bacteria produce a reporter protein, the amount or activity of which is measured in the bioassay. Some of these bacterial biosensor-reporters have been successfully utilized for comparative in-field analyses through the use of simple solution-based assays, but future methods may concentrate on miniaturization using fiberoptics or microfluidics platforms. Additionally, there are other potential emerging bioassays for the detection of arsenic in natural waters including nematodes and clams.

Gamma/neutron time-correlation for special nuclear material detection – Active stimulation of highly enriched uranium

DOE PAGES

Paff, Marc G.; Monterial, Mateusz; Marleau, Peter; ...

2014-06-21

A series of simulations and experiments were undertaken to explore and evaluate the potential for a novel new technique for fissile material detection and characterization, the timecorrelated pulse-height (TCPH) method, to be used concurrent with active stimulation of potential nuclear materials. In previous work TCPH has been established as a highly sensitive method for the detection and characterization of configurations of fissile material containing Plutonium in passive measurements. By actively stimulating fission with the introduction of an external radiation source, we have shown that TCPH is also an effective method of detecting and characterizing configurations of fissile material containing Highlymore » Enriched Uranium (HEU). The TCPH method is shown to be robust in the presence of the proper choice of external radiation source. An evaluation of potential interrogation sources is presented.« less

Staircase-scene-based nonuniformity correction in aerial point target detection systems.

PubMed

Huo, Lijun; Zhou, Dabiao; Wang, Dejiang; Liu, Rang; He, Bin

2016-09-01

Focal-plane arrays (FPAs) are often interfered by heavy fixed-pattern noise, which severely degrades the detection rate and increases the false alarms in airborne point target detection systems. Thus, high-precision nonuniformity correction is an essential preprocessing step. In this paper, a new nonuniformity correction method is proposed based on a staircase scene. This correction method can compensate for the nonlinear response of the detector and calibrate the entire optical system with computational efficiency and implementation simplicity. Then, a proof-of-concept point target detection system is established with a long-wave Sofradir FPA. Finally, the local standard deviation of the corrected image and the signal-to-clutter ratio of the Airy disk of a Boeing B738 are measured to evaluate the performance of the proposed nonuniformity correction method. Our experimental results demonstrate that the proposed correction method achieves high-quality corrections.

[Multiplex real-time PCR method for rapid detection of Marburg virus and Ebola virus].

PubMed

Yang, Yu; Bai, Lin; Hu, Kong-Xin; Yang, Zhi-Hong; Hu, Jian-Ping; Wang, Jing

2012-08-01

Marburg virus and Ebola virus are acute infections with high case fatality rates. A rapid, sensitive detection method was established to detect Marburg virus and Ebola virus by multiplex real-time fluorescence quantitative PCR. Designing primers and Taqman probes from highly conserved sequences of Marburg virus and Ebola virus through whole genome sequences alignment, Taqman probes labeled by FAM and Texas Red, the sensitivity of the multiplex real-time quantitative PCR assay was optimized by evaluating the different concentrations of primers and Probes. We have developed a real-time PCR method with the sensitivity of 30.5 copies/microl for Marburg virus positive plasmid and 28.6 copies/microl for Ebola virus positive plasmids, Japanese encephalitis virus, Yellow fever virus, Dengue virus were using to examine the specificity. The Multiplex real-time PCR assays provide a sensitive, reliable and efficient method to detect Marburg virus and Ebola virus simultaneously.

Detecting exact breakpoints of deletions with diversity in hepatitis B viral genomic DNA from next-generation sequencing data.

PubMed

Cheng, Ji-Hong; Liu, Wen-Chun; Chang, Ting-Tsung; Hsieh, Sun-Yuan; Tseng, Vincent S

2017-10-01

Many studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads. Thus, detecting exact breakpoints of deletions from these big and complex data incurs very high computational cost. We proposed a novel analytical method named VirDelect (Virus Deletion Detect), which uses split read alignment base to detect exact breakpoint and diversity variable to consider high divergence in single-end reads data, such that the computational cost can be reduced without losing accuracy. We use four simulated reads datasets and two real pair-end reads datasets of HBV genome sequence to verify VirDelect accuracy by score functions. The experimental results show that VirDelect outperforms the state-of-the-art method Pindel in terms of accuracy score for all simulated datasets and VirDelect had only two base errors even in real datasets. VirDelect is also shown to deliver high accuracy in analyzing the single-end read data as well as pair-end data. VirDelect can serve as an effective and efficient bioinformatics tool for physiologists with high accuracy and efficient performance and applicable to further analysis with characteristics similar to HBV on genome length and high divergence. The software program of VirDelect can be downloaded at https://sourceforge.net/projects/virdelect/. Copyright © 2017. Published by Elsevier Inc.

Ultrasensitive Single Fluorescence-Labeled Probe-Mediated Single Universal Primer-Multiplex-Droplet Digital Polymerase Chain Reaction for High-Throughput Genetically Modified Organism Screening.

PubMed

Niu, Chenqi; Xu, Yuancong; Zhang, Chao; Zhu, Pengyu; Huang, Kunlun; Luo, Yunbo; Xu, Wentao

2018-05-01

As genetically modified (GM) technology develops and genetically modified organisms (GMOs) become more available, GMOs face increasing regulations and pressure to adhere to strict labeling guidelines. A singleplex detection method cannot perform the high-throughput analysis necessary for optimal GMO detection. Combining the advantages of multiplex detection and droplet digital polymerase chain reaction (ddPCR), a single universal primer-multiplex-ddPCR (SUP-M-ddPCR) strategy was proposed for accurate broad-spectrum screening and quantification. The SUP increases efficiency of the primers in PCR and plays an important role in establishing a high-throughput, multiplex detection method. Emerging ddPCR technology has been used for accurate quantification of nucleic acid molecules without a standard curve. Using maize as a reference point, four heterologous sequences ( 35S, NOS, NPTII, and PAT) were selected to evaluate the feasibility and applicability of this strategy. Surprisingly, these four genes cover more than 93% of the transgenic maize lines and serve as preliminary screening sequences. All screening probes were labeled with FAM fluorescence, which allows the signals from the samples with GMO content and those without to be easily differentiated. This fiveplex screening method is a new development in GMO screening. Utilizing an optimal amplification assay, the specificity, limit of detection (LOD), and limit of quantitation (LOQ) were validated. The LOD and LOQ of this GMO screening method were 0.1% and 0.01%, respectively, with a relative standard deviation (RSD) < 25%. This method could serve as an important tool for the detection of GM maize from different processed, commercially available products. Further, this screening method could be applied to other fields that require reliable and sensitive detection of DNA targets.

Sensitive SERS detection of lead ions via DNAzyme based quadratic signal amplification.

PubMed

Tian, Aihua; Liu, Yu; Gao, Jian

2017-08-15

Highly sensitive detection of Pb 2+ is very necessary for water quality control, clinical toxicology, and industrial monitoring. In this work, a simple and novel DNAzyme-based SERS quadratic amplification method is developed for the detection of Pb 2+ . This strategy possesses some remarkable features compared to the conventional DNAzyme-based SERS methods, which are as follows: (i) Coupled DNAzyme-activated hybridization chain reaction (HCR) with bio barcodes; a quadratic amplification method is designed using the unique catalytic selectivity of DNAzyme. The SERS signal is significantly amplified. This method is rapid with a detection time of 2h. (ii) The problem of high background induced by excess bio barcodes is circumvented by using magnetic beads (MBs) as the carrier of signal-output products, and this sensing system is simple in design and can easily be carried out by simple mixing and incubation. Given the unique and attractive characteristics, a simple and universal strategy is designed to accomplish sensitive detection of Pb 2+ . The detection limit of Pb 2+ via SERS detection is 70 fM, with the linear range from 1.0×10 -13 M to 1.0×10 -7 M. The method can be further extended to the quantitative detection of a variety of targets by replacing the lead-responsive DNAzyme with other functional DNA. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatially Resolved Chemical Imaging for Biosignature Analysis: Terrestrial and Extraterrestrial Examples

NASA Astrophysics Data System (ADS)

Bhartia, R.; Wanger, G.; Orphan, V. J.; Fries, M.; Rowe, A. R.; Nealson, K. H.; Abbey, W. J.; DeFlores, L. P.; Beegle, L. W.

2014-12-01

Detection of in situ biosignatures on terrestrial and planetary missions is becoming increasingly more important. Missions that target the Earth's deep biosphere, Mars, moons of Jupiter (including Europa), moons of Saturn (Titan and Enceladus), and small bodies such as asteroids or comets require methods that enable detection of materials for both in-situ analysis that preserve context and as a means to select high priority sample for return to Earth. In situ instrumentation for biosignature detection spans a wide range of analytical and spectroscopic methods that capitalize on amino acid distribution, chirality, lipid composition, isotopic fractionation, or textures that persist in the environment. Many of the existing analytical instruments are bulk analysis methods and while highly sensitive, these require sample acquisition and sample processing. However, by combining with triaging spectroscopic methods, biosignatures can be targeted on a surface and preserve spatial context (including mineralogy, textures, and organic distribution). To provide spatially correlated chemical analysis at multiple spatial scales (meters to microns) we have employed a dual spectroscopic approach that capitalizes on high sensitivity deep UV native fluorescence detection and high specificity deep UV Raman analysis.. Recently selected as a payload on the Mars 2020 mission, SHERLOC incorporates these optical methods for potential biosignatures detection on Mars. We present data from both Earth analogs that operate as our only examples known biosignatures and meteorite samples that provide an example of abiotic organic formation, and demonstrate how provenance effects the spatial distribution and composition of organics.

Detecting double compression of audio signal

NASA Astrophysics Data System (ADS)

Yang, Rui; Shi, Yun Q.; Huang, Jiwu

2010-01-01

MP3 is the most popular audio format nowadays in our daily life, for example music downloaded from the Internet and file saved in the digital recorder are often in MP3 format. However, low bitrate MP3s are often transcoded to high bitrate since high bitrate ones are of high commercial value. Also audio recording in digital recorder can be doctored easily by pervasive audio editing software. This paper presents two methods for the detection of double MP3 compression. The methods are essential for finding out fake-quality MP3 and audio forensics. The proposed methods use support vector machine classifiers with feature vectors formed by the distributions of the first digits of the quantized MDCT (modified discrete cosine transform) coefficients. Extensive experiments demonstrate the effectiveness of the proposed methods. To the best of our knowledge, this piece of work is the first one to detect double compression of audio signal.

Detecting and treating occlusal caries lesions: a cost-effectiveness analysis.

PubMed

Schwendicke, F; Stolpe, M; Meyer-Lueckel, H; Paris, S

2015-02-01

The health gains and costs resulting from using different caries detection strategies might not only depend on the accuracy of the used method but also the treatment emanating from its use in different populations. We compared combinations of visual-tactile, radiographic, or laser-fluorescence-based detection methods with 1 of 3 treatments (non-, micro-, and invasive treatment) initiated at different cutoffs (treating all or only dentinal lesions) in populations with low or high caries prevalence. A Markov model was constructed to follow an occlusal surface in a permanent molar in an initially 12-y-old male German patient over his lifetime. Prevalence data and transition probabilities were extracted from the literature, while validity parameters of different methods were synthesized or obtained from systematic reviews. Microsimulations were performed to analyze the model, assuming a German health care setting and a mixed public-private payer perspective. Radiographic and fluorescence-based methods led to more overtreatments, especially in populations with low prevalence. For the latter, combining visual-tactile or radiographic detection with microinvasive treatment retained teeth longest (mean 66 y) at lowest costs (329 and 332 Euro, respectively), while combining radiographic or fluorescence-based detections with invasive treatment was the least cost-effective (<60 y, >700 Euro). In populations with high prevalence, combining radiographic detection with microinvasive treatment was most cost-effective (63 y, 528 Euro), while sensitive detection methods combined with invasive treatments were again the least cost-effective (<59 y, >690 Euro). The suitability of detection methods differed significantly between populations, and the cost-effectiveness was greatly influenced by the treatment initiated after lesion detection. The accuracy of a detection method relative to a "gold standard" did not automatically convey into better health or reduced costs. Detection methods should be evaluated not only against their criterion validity but also the long-term effects resulting from their use in different populations. © International & American Associations for Dental Research 2014.

Assessing the detectability of antioxidants in two-dimensional high-performance liquid chromatography.

PubMed

Bassanese, Danielle N; Conlan, Xavier A; Barnett, Neil W; Stevenson, Paul G

2015-05-01

This paper explores the analytical figures of merit of two-dimensional high-performance liquid chromatography for the separation of antioxidant standards. The cumulative two-dimensional high-performance liquid chromatography peak area was calculated for 11 antioxidants by two different methods--the areas reported by the control software and by fitting the data with a Gaussian model; these methods were evaluated for precision and sensitivity. Both methods demonstrated excellent precision in regards to retention time in the second dimension (%RSD below 1.16%) and cumulative second dimension peak area (%RSD below 3.73% from the instrument software and 5.87% for the Gaussian method). Combining areas reported by the high-performance liquid chromatographic control software displayed superior limits of detection, in the order of 1 × 10(-6) M, almost an order of magnitude lower than the Gaussian method for some analytes. The introduction of the countergradient eliminated the strong solvent mismatch between dimensions, leading to a much improved peak shape and better detection limits for quantification. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mutation Analysis of SLC26A4 for Pendred Syndrome and Nonsyndromic Hearing Loss by High-Resolution Melting

PubMed Central

Chen, Neng; Tranebjærg, Lisbeth; Rendtorff, Nanna Dahl; Schrijver, Iris

2011-01-01

Pendred syndrome and DFNB4 (autosomal recessive nonsyndromic congenital deafness, locus 4) are associated with autosomal recessive congenital sensorineural hearing loss and mutations in the SLC26A4 gene. Extensive allelic heterogeneity, however, necessitates analysis of all exons and splice sites to identify mutations for individual patients. Although Sanger sequencing is the gold standard for mutation detection, screening methods supplemented with targeted sequencing can provide a cost-effective alternative. One such method, denaturing high-performance liquid chromatography, was developed for clinical mutation detection in SLC26A4. However, this method inherently cannot distinguish homozygous changes from wild-type sequences. High-resolution melting (HRM), on the other hand, can detect heterozygous and homozygous changes cost-effectively, without any post-PCR modifications. We developed a closed-tube HRM mutation detection method specific for SLC26A4 that can be used in the clinical diagnostic setting. Twenty-eight primer pairs were designed to cover all 21 SLC26A4 exons and splice junction sequences. Using the resulting amplicons, initial HRM analysis detected all 45 variants previously identified by sequencing. Subsequently, a 384-well plate format was designed for up to three patient samples per run. Blinded HRM testing on these plates of patient samples collected over 1 year in a clinical diagnostic laboratory accurately detected all variants identified by sequencing. In conclusion, HRM with targeted sequencing is a reliable, simple, and cost-effective method for SLC26A4 mutation screening and detection. PMID:21704276

Rapid and sensitive detection of Yersinia pestis using amplification of plague diagnostic bacteriophages monitored by real-time PCR.

PubMed

Sergueev, Kirill V; He, Yunxiu; Borschel, Richard H; Nikolich, Mikeljon P; Filippov, Andrey A

2010-06-28

Yersinia pestis, the agent of plague, has caused many millions of human deaths and still poses a serious threat to global public health. Timely and reliable detection of such a dangerous pathogen is of critical importance. Lysis by specific bacteriophages remains an essential method of Y. pestis detection and plague diagnostics. The objective of this work was to develop an alternative to conventional phage lysis tests--a rapid and highly sensitive method of indirect detection of live Y. pestis cells based on quantitative real-time PCR (qPCR) monitoring of amplification of reporter Y. pestis-specific bacteriophages. Plague diagnostic phages phiA1122 and L-413C were shown to be highly effective diagnostic tools for the detection and identification of Y. pestis by using qPCR with primers specific for phage DNA. The template DNA extraction step that usually precedes qPCR was omitted. phiA1122-specific qPCR enabled the detection of an initial bacterial concentration of 10(3) CFU/ml (equivalent to as few as one Y. pestis cell per 1-microl sample) in four hours. L-413C-mediated detection of Y. pestis was less sensitive (up to 100 bacteria per sample) but more specific, and thus we propose parallel qPCR for the two phages as a rapid and reliable method of Y. pestis identification. Importantly, phiA1122 propagated in simulated clinical blood specimens containing EDTA and its titer rise was detected by both a standard plating test and qPCR. Thus, we developed a novel assay for detection and identification of Y. pestis using amplification of specific phages monitored by qPCR. The method is simple, rapid, highly sensitive, and specific and allows the detection of only live bacteria.

Quantum dots as optical labels for ultrasensitive detection of polyphenols.

PubMed

Akshath, Uchangi Satyaprasad; Shubha, Likitha R; Bhatt, Praveena; Thakur, Munna Singh

2014-07-15

Considering the fact that polyphenols have versatile activity in-vivo, its detection and quantification is very much important for a healthy diet. Laccase enzyme can convert polyphenols to yield mono/polyquinones which can quench Quantum dots fluorescence. This phenomenon of charge transfer from quinones to QDs was exploited as optical labels to detect polyphenols. CdTe QD may undergo dipolar interaction with quinones as a result of broad spectral absorption due to multiple excitonic states resulting from quantum confinement effects. Thus, "turn-off" fluorescence method was applied for ultrasensitive detection of polyphenols by using laccase. We observed proportionate quenching of QDs fluorescence with respect to polyphenol concentration in the range of 100 µg to 1 ng/mL. Also, quenching of the photoluminescence was highly efficient and stable and could detect individual and total polyphenols with high sensitivity (LOD-1 ng/mL). Moreover, proposed method was highly efficient than any other reported methods in terms of sensitivity, specificity and selectivity. Therefore, a novel optical sensor was developed for the detection of polyphenols at a sensitive level based on the charge transfer mechanism. Copyright © 2014 Elsevier B.V. All rights reserved.

Facile and scalable disposable sensor based on laser engraved graphene for electrochemical detection of glucose

PubMed Central

Tehrani, Farshad; Bavarian, Behzad

2016-01-01

A novel and highly sensitive disposable glucose sensor strip was developed using direct laser engraved graphene (DLEG) decorated with pulse deposited copper nanocubes (CuNCs). The high reproducibility (96.8%), stability (97.4%) and low cost demonstrated by this 3-step fabrication method indicates that it could be used for high volume manufacturing of disposable glucose strips. The fabrication method also allows for a high degree of flexibility, allowing for control of the electrode size, design, and functionalization method. Additionally, the excellent selectivity and sensitivity (4,532.2 μA/mM.cm2), low detection limit (250 nM), and suitable linear range of 25 μM–4 mM, suggests that these sensors may be a great potential platform for glucose detection within the physiological range for tear, saliva, and/or sweat. PMID:27306706

Facile and scalable disposable sensor based on laser engraved graphene for electrochemical detection of glucose

NASA Astrophysics Data System (ADS)

Tehrani, Farshad; Bavarian, Behzad

2016-06-01

A novel and highly sensitive disposable glucose sensor strip was developed using direct laser engraved graphene (DLEG) decorated with pulse deposited copper nanocubes (CuNCs). The high reproducibility (96.8%), stability (97.4%) and low cost demonstrated by this 3-step fabrication method indicates that it could be used for high volume manufacturing of disposable glucose strips. The fabrication method also allows for a high degree of flexibility, allowing for control of the electrode size, design, and functionalization method. Additionally, the excellent selectivity and sensitivity (4,532.2 μA/mM.cm2), low detection limit (250 nM), and suitable linear range of 25 μM-4 mM, suggests that these sensors may be a great potential platform for glucose detection within the physiological range for tear, saliva, and/or sweat.

Visual detection of Ebola virus using reverse transcription loop-mediated isothermal amplification combined with nucleic acid strip detection.

PubMed

Xu, Changping; Wang, Hualei; Jin, Hongli; Feng, Na; Zheng, Xuexing; Cao, Zengguo; Li, Ling; Wang, Jianzhong; Yan, Feihu; Wang, Lina; Chi, Hang; Gai, Weiwei; Wang, Chong; Zhao, Yongkun; Feng, Yan; Wang, Tiecheng; Gao, Yuwei; Lu, Yiyu; Yang, Songtao; Xia, Xianzhu

2016-05-01

Ebola virus (species Zaire ebolavirus) (EBOV) is highly virulent in humans. The largest recorded outbreak of Ebola hemorrhagic fever in West Africa to date was caused by EBOV. Therefore, it is necessary to develop a detection method for this virus that can be easily distributed and implemented. In the current study, we developed a visual assay that can detect EBOV-associated nucleic acids. This assay combines reverse transcription loop-mediated isothermal amplification and nucleic acid strip detection (RT-LAMP-NAD). Nucleic acid amplification can be achieved in a one-step process at a constant temperature (58 °C, 35 min), and the amplified products can be visualized within 2-5 min using a nucleic acid strip detection device. The assay is capable of detecting 30 copies of artificial EBOV glycoprotein (GP) RNA and RNA encoding EBOV GP from 10(2) TCID50 recombinant viral particles per ml with high specificity. Overall, the RT-LAMP-NAD method is simple and has high sensitivity and specificity; therefore, it is especially suitable for the rapid detection of EBOV in African regions.

Detection and quantification of infectious avian influenza A (H5N1) virus in environmental water by using real-time reverse transcription-PCR.

PubMed

Dovas, C I; Papanastassopoulou, M; Georgiadis, M P; Chatzinasiou, E; Maliogka, V I; Georgiades, G K

2010-04-01

Routes of avian influenza virus (AIV) dispersal among aquatic birds involve direct (bird-to-bird) and indirect (waterborne) transmission. The environmental persistence of H5N1 virus in natural water reservoirs can be assessed by isolation of virus in embryonated chicken eggs. Here we describe development and evaluation of a real-time quantitative reverse transcription (RT)-PCR (qRT-PCR) method for detection of H5N1 AIV in environmental water. This method is based on adsorption of virus particles to formalin-fixed erythrocytes, followed by qRT-PCR detection. The numbers of hemagglutinin RNA copies from H5N1 highly pathogenic AIV particles adsorbed to erythrocytes detected correlated highly with the infectious doses of the virus that were determined for three different types of artificially inoculated environmental water over a 17-day incubation period. The advantages of this method include detection and quantification of infectious H5N1 AIVs with a high level of sensitivity, a wide dynamic range, and reproducibility, as well as increased biosecurity. The lowest concentration of H5N1 virus that could be reproducibly detected was 0.91 50% egg infective dose per ml. In addition, a virus with high virion stability (Tobacco mosaic virus) was used as an internal control to accurately monitor the efficiency of RNA purification, cDNA synthesis, and PCR amplification for each individual sample. This detection system could be useful for rapid high-throughput monitoring for the presence of H5N1 AIVs in environmental water and in studies designed to explore the viability and epidemiology of these viruses in different waterfowl ecosystems. The proposed method may also be adapted for detection of other AIVs and for assessment of their prevalence and distribution in environmental reservoirs.

The Detection Method of Escherichia coli in Water Resources: A Review

NASA Astrophysics Data System (ADS)

Nurliyana, M. R.; Sahdan, M. Z.; Wibowo, K. M.; Muslihati, A.; Saim, H.; Ahmad, S. A.; Sari, Y.; Mansor, Z.

2018-04-01

This article reviews several approaches for Escherichia coli (E. coli) bacteria detection from conventional methods, emerging method and goes to biosensor-based techniques. Detection and enumeration of E. coli bacteria usually required long duration of time in obtaining the result since laboratory-based approach is normally used in its assessment. It requires 24 hours to 72 hours after sampling to process the culturing samples before results are available. Although faster technique for detecting E. coli in water such as Polymerase Chain Reaction (PCR) and Enzyme-Linked Immunosorbent Assay (ELISA) have been developed, it still required transporting the samples from water resources to the laboratory, high-cost, complicated equipment usage, complex procedures, as well as the requirement of skilled specialist to cope with the complexity which limit their wide spread practice in water quality detection. Recently, development of biosensor device that is easy to perform, portable, highly sensitive and selective becomes indispensable in detecting extremely lower consolidation of pathogenic E. coli bacteria in water samples.

Portable evanescent wave fiber biosensor for highly sensitive detection of Shigella

NASA Astrophysics Data System (ADS)

Xiao, Rui; Rong, Zhen; Long, Feng; Liu, Qiqi

2014-11-01

A portable evanescent wave fiber biosensor was developed to achieve the rapid and highly sensitive detection of Shigella. In this study, a DNA probe was covalently immobilized onto fiber-optic biosensors that can hybridize with a fluorescently labeled complementary DNA. The sensitivity of detection for synthesized oligonucleotides can reach 10-10 M. The surface of the sensor can be regenerated with 0.5% sodium dodecyl sulfate solution (pH 1.9) for over 30 times without significant deterioration of performance. The total analysis time for a single sample, including the time for measurement and surface regeneration, was less than 6 min. We employed real-time polymerase chain reaction (PCR) and compared the results of both methods to investigate the actual Shigella DNA detection capability of the fiber-optic biosensor. The fiber-optic biosensor could detect as low as 102 colony-forming unit/mL Shigella. This finding was comparable with that by real-time PCR, which suggests that this method is a potential alternative to existing detection methods.

Speciation of chromium using reversed phase-high performance liquid chromatography coupled to different spectrometric detection methods

NASA Astrophysics Data System (ADS)

Andrle, C. M.; Jakubowski, N.; Broekaert, J. A. C.

1997-02-01

Speciation of Cr(III) and Cr(VI) based on the formation of different complexes with ammonium-pyrrolidinedithioate (APDC) in a continuous flow technique and their preconcentration using solid phase extraction (SPE) have been elaborated and applied to the analysis of waste waters from the galvanic industry. The Cr complexes were separated and determined using reversed phase-high performance liquid chromatography (RP-HPLC) coupled to different detection methods, namely UV-detection, graphite furnace-atomic absorption spectrometry (GF-AAS) and inductively coupled plasma mass spectrometry with hydraulic high pressure nebulization (HHPN/ICP-MS). After optimization the detection limits for Cr(III) and Cr(VI) of all methods are at the μg 1 -1 level and the precision in terms of RSD is 5% ( cCr = 100 μg 1 -1, N = 10). The procedure was applied to the determination of Cr(III) and Cr(VI) at the μg 1 -1 level in galvanic waste waters, and its accuracy was approved by comparing the results with those of independent methods.

Detecting Damage in Composite Material Using Nonlinear Elastic Wave Spectroscopy Methods

NASA Astrophysics Data System (ADS)

Meo, Michele; Polimeno, Umberto; Zumpano, Giuseppe

2008-05-01

Modern aerospace structures make increasing use of fibre reinforced plastic composites, due to their high specific mechanical properties. However, due to their brittleness, low velocity impact can cause delaminations beneath the surface, while the surface may appear to be undamaged upon visual inspection. Such damage is called barely visible impact damage (BVID). Such internal damages lead to significant reduction in local strengths and ultimately could lead to catastrophic failures. It is therefore important to detect and monitor damages in high loaded composite components to receive an early warning for a well timed maintenance of the aircraft. Non-linear ultrasonic spectroscopy methods are promising damage detection and material characterization tools. In this paper, two different non-linear elastic wave spectroscopy (NEWS) methods are presented: single mode nonlinear resonance ultrasound (NRUS) and nonlinear wave modulation technique (NWMS). The NEWS methods were applied to detect delamination damage due to low velocity impact (<12 J) on various composite plates. The results showed that the proposed methodology appear to be highly sensitive to the presence of damage with very promising future NDT and structural health monitoring applications.

Combining isothermal rolling circle amplification and electrochemiluminescence for highly sensitive point mutation detection

NASA Astrophysics Data System (ADS)

Su, Qiang; Zhou, Xiaoming

2008-12-01

Many pathogenic and genetic diseases are associated with changes in the sequence of particular genes. We describe here a rapid and highly efficient assay for the detection of point mutation. This method is a combination of isothermal rolling circle amplification (RCA) and high sensitive electrochemluminescence (ECL) detection. In the design, a circular template generated by ligation upon the recognition of a point mutation on DNA targets was amplified isothermally by the Phi29 polymerase using a biotinylated primer. The elongation products were hybridized with tris (bipyridine) ruthenium (TBR)-tagged probes and detected in a magnetic bead based ECL platform, indicating the mutation occurrence. P53 was chosen as a model for the identification of this method. The method allowed sensitive determination of the P53 mutation from wild-type and mutant samples. The main advantage of RCA-ECL is that it can be performed under isothermal conditions and avoids the generation of false-positive results. Furthermore, ECL provides a faster, more sensitive, and economical option to currently available electrophoresis-based methods.

Determination of mycotoxins produced by Fusarium isolates from banana fruits by capillary gas chromatography and high-performance liquid chromatography.

PubMed

Jiménez, M; Mateo, R

1997-08-22

A method of analysis for trichothecenes (nivalenol, deoxynivalenol, 3- and 15-acetyldeoxynivalenol, diacetoxyscirpenol, neosolaniol, T-2 tetraol, T-2 and HT-2 toxins), zearalenone and zearalenols, and another method for determination of fumonisin B1 are described and applied to cultures of Fusarium isolated from bananas. Both methods were adapted from different techniques of extraction, clean-up and determination of these mycotoxins. The first method involves extraction with methanol-1% aqueous sodium chloride, clean-up of extracts by partition with hexane and dichloromethane, additional solid reversed-phase clean-up and analysis of two eluates by both high-performance liquid chromatography with ultraviolet detection and capillary gas chromatography. The method for fumonisin B1 implies extraction with aqueous methanol, concentration, clean-up with water and methanol on Amberlite XAD-2 column, formation of a fluorescent 4-fluoro-7-nitrobenzofurazan derivative and analysis by high-performance liquid chromatography with fluorescence detection. Both procedures give good limits of detection and recoveries, and are considered suitable for the detection and quantification of the studied toxins in corn and rice cultures of Fusarium spp. isolated from banana fruits.

Explosive detection using high-volume vapor sampling and analysis by trained canines and ultra-trace detection equipment

NASA Astrophysics Data System (ADS)

Fisher, Mark; Sikes, John; Prather, Mark

2004-09-01

The dog's nose is an effective, highly-mobile sampling system, while the canine olfactory organs are an extremely sensitive detector. Having been trained to detect a wide variety of substances with exceptional results, canines are widely regarded as the 'gold standard' in chemical vapor detection. Historically, attempts to mimic the ability of dogs to detect vapors of explosives using electronic 'dogs noses' has proven difficult. However, recent advances in technology have resulted in development of detection (i.e., sampling and sensor) systems with performance that is rapidly approaching that of trained canines. The Nomadics Fido was the first sensor to demonstrate under field conditions the detection of landmines with performance approaching that of canines. More recently, comparative testing of Fido against canines has revealed that electronic vapor detection, when coupled with effective sampling methods, can produce results comparable to that of highly-trained canines. The results of these comparative tests will be presented, as will recent test results in which explosives hidden in cargo were detected using Fido with a high-volume sampling technique. Finally, the use of canines along with electronic sensors will be discussed as a means of improving the performance and expanding the capabilities of both methods.

An infrared spectroscopy method to detect ammonia in gastric juice.

PubMed

Giovannozzi, Andrea M; Pennecchi, Francesca; Muller, Paul; Balma Tivola, Paolo; Roncari, Silvia; Rossi, Andrea M

2015-11-01

Ammonia in gastric juice is considered a potential biomarker for Helicobacter pylori infection and as a factor contributing to gastric mucosal injury. High ammonia concentrations are also found in patients with chronic renal failure, peptic ulcer disease, and chronic gastritis. Rapid and specific methods for ammonia detection are urgently required by the medical community. Here we present a method to detect ammonia directly in gastric juice based on Fourier transform infrared spectroscopy. The ammonia dissolved in biological liquid samples as ammonium ion was released in air as a gas by the shifting of the pH equilibrium of the ammonium/ammonia reaction and was detected in line by a Fourier transform infrared spectroscopy system equipped with a gas cell for the quantification. The method developed provided high sensitivity and selectivity in ammonia detection both in pure standard solutions and in a simulated gastric juice matrix over the range of diagnostic concentrations tested. Preliminary analyses were also performed on real gastric juice samples from patients with gastric mucosal injury and with symptoms of H. pylori infection, and the results were in agreement with the clinicopathology information. The whole analysis, performed in less than 10 min, can be directly applied on the sample without extraction procedures and it ensures high specificity of detection because of the ammonia fingerprint absorption bands in the infrared spectrum. This method could be easily used with endoscopy instrumentation to provide information in real time and would enable the endoscopist to improve and integrate gastroscopic examinations.

Loop-mediated isothermal amplification for detection of Staphylococcus aureus in dairy cow suffering from mastitis.

PubMed

Tie, Zhang; Chunguang, Wang; Xiaoyuan, Wei; Xinghua, Zhao; Xiuhui, Zhong

2012-01-01

To develop a rapid detection method of Staphylococcus aureus using loop-mediated isothermal amplification (LAMP), four specific primers were designed according to six distinct sequences of the nuc gene. In addition, the specificity and sensitivity of LAMP were verified and compared with those of PCR. Results showed that the LAMP reaction was completed within 45 min at 62.5°C, and ladder bands were appeared in LAMP products analyzed by gel electrophoresis. After adding 1x SYBR Green l, the positive reaction tube showed green color and the negative reaction tube remained orange, indicating that the LAMP has high specificity. The minimal detectable concentration of LAMP was 1 × 10² CFU/mL and that of PCR was 1 × 10⁴ CFU/mL, indicating that the LAMP was 100 times more sensitive than the PCR. The LAMP method for detection of Staphylococcus aureus has many advantages, such as simple operation, high sensitivity, high specificity, and rapid analysis. Therefore, this method is more suitable for the rapid on-site detection of Staphylococcus aureus.

A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

PubMed

Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J

2014-02-01

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

Optoelectronic method for detection of cervical intraepithelial neoplasia and cervical cancer

NASA Astrophysics Data System (ADS)

Pruski, D.; Przybylski, M.; Kędzia, W.; Kędzia, H.; Jagielska-Pruska, J.; Spaczyński, M.

2011-12-01

The optoelectronic method is one of the most promising concepts of biophysical program of the diagnostics of CIN and cervical cancer. Objectives of the work are evaluation of sensitivity and specificity of the optoelectronic method in the detection of CIN and cervical cancer. The paper shows correlation between the pNOR number and sensitivity/specificity of the optoelectronic method. The study included 293 patients with abnormal cervical cytology result and the following examinations: examination with the use of the optoelectronic method — Truscreen, colposcopic examination, and histopathologic biopsy. Specificity of the optoelectronic method for LGSIL was estimated at 65.70%, for HGSIL and squamous cell carcinoma of cervix amounted to 90.38%. Specificity of the optoelectronic method used to confirm lack of cervical pathology was estimated at 78.89%. The field under the ROC curve for the optoelectronic method was estimated at 0.88 (95% CI, 0.84-0.92) which shows high diagnostic value of the test in the detection of HGSIL and squamous cell carcinoma. The optoelectronic method is characterised by high usefulness in the detection of CIN, present in the squamous epithelium and squamous cell carcinoma of cervix.

A Hybrid Approach for CpG Island Detection in the Human Genome.

PubMed

Yang, Cheng-Hong; Lin, Yu-Da; Chiang, Yi-Cheng; Chuang, Li-Yeh

2016-01-01

CpG islands have been demonstrated to influence local chromatin structures and simplify the regulation of gene activity. However, the accurate and rapid determination of CpG islands for whole DNA sequences remains experimentally and computationally challenging. A novel procedure is proposed to detect CpG islands by combining clustering technology with the sliding-window method (PSO-based). Clustering technology is used to detect the locations of all possible CpG islands and process the data, thus effectively obviating the need for the extensive and unnecessary processing of DNA fragments, and thus improving the efficiency of sliding-window based particle swarm optimization (PSO) search. This proposed approach, named ClusterPSO, provides versatile and highly-sensitive detection of CpG islands in the human genome. In addition, the detection efficiency of ClusterPSO is compared with eight CpG island detection methods in the human genome. Comparison of the detection efficiency for the CpG islands in human genome, including sensitivity, specificity, accuracy, performance coefficient (PC), and correlation coefficient (CC), ClusterPSO revealed superior detection ability among all of the test methods. Moreover, the combination of clustering technology and PSO method can successfully overcome their respective drawbacks while maintaining their advantages. Thus, clustering technology could be hybridized with the optimization algorithm method to optimize CpG island detection. The prediction accuracy of ClusterPSO was quite high, indicating the combination of CpGcluster and PSO has several advantages over CpGcluster and PSO alone. In addition, ClusterPSO significantly reduced implementation time.

A combination of immunohistochemistry and molecular approaches improves highly sensitive detection of BRAF mutations in papillary thyroid cancer.

PubMed

Martinuzzi, Claudia; Pastorino, Lorenza; Andreotti, Virginia; Garuti, Anna; Minuto, Michele; Fiocca, Roberto; Bianchi-Scarrà, Giovanna; Ghiorzo, Paola; Grillo, Federica; Mastracci, Luca

2016-09-01

The optimal method for BRAF mutation detection remains to be determined despite advances in molecular detection techniques. The aim of this study was to compare, against classical Sanger sequencing, the diagnostic performance of two of the most recently developed, highly sensitive methods: BRAF V600E immunohistochemistry (IHC) and peptide nucleic-acid (PNA)-clamp qPCR. BRAF exon 15 mutations were searched in formalin-fixed paraffin-embedded tissues from 86 papillary thyroid carcinoma using the three methods. The limits of detection of Sanger sequencing in borderline or discordant cases were quantified by next generation sequencing. BRAF mutations were found in 74.4 % of cases by PNA, in 71 % of cases by IHC, and in 64 % of cases by Sanger sequencing. Complete concordance for the three methods was observed in 80 % of samples. Better concordance was observed with the combination of two methods, particularly PNA and IHC (59/64) (92 %), while the combination of PNA and Sanger was concordant in 55 cases (86 %). Sensitivity of the three methods was 99 % for PNA, 94.2 % for IHC, and 89.5 % for Sanger. Our data show that IHC could be used as a cost-effective, first-line method for BRAF V600E detection in daily practice, followed by PNA analysis in negative or uninterpretable cases, as the most efficient method. PNA-clamp quantitative PCR is highly sensitive and complementary to IHC as it also recognizes other mutations besides V600E and it is suitable for diagnostic purposes.

The Trace Analysis of DEET in Water using an On-line Preconcentration Column and Liquid Chromatography with UV Photodiode Array Detection

EPA Science Inventory

A method for the detection of trace levels of N,N-diethyl-m-toluamide (DEET) in water is discussed. The method utilizes an on-line preconcentration column in series with high performance liquid chromatography (HPLC) and UV photodiode array detection. DEET, a common insect repel...

A compact imaging spectroscopic system for biomolecular detections on plasmonic chips.

PubMed

Lo, Shu-Cheng; Lin, En-Hung; Wei, Pei-Kuen; Tsai, Wan-Shao

2016-10-17

In this study, we demonstrate a compact imaging spectroscopic system for high-throughput detection of biomolecular interactions on plasmonic chips, based on a curved grating as the key element of light diffraction and light focusing. Both the curved grating and the plasmonic chips are fabricated on flexible plastic substrates using a gas-assisted thermal-embossing method. A fiber-coupled broadband light source and a camera are included in the system. Spectral resolution within 1 nm is achieved in sensing environmental index solutions and protein bindings. The detected sensitivities of the plasmonic chip are comparable with a commercial spectrometer. An extra one-dimensional scanning stage enables high-throughput detection of protein binding on a designed plasmonic chip consisting of several nanoslit arrays with different periods. The detected resonance wavelengths match well with the grating equation under an air environment. Wavelength shifts between 1 and 9 nm are detected for antigens of various concentrations binding with antibodies. A simple, mass-productive and cost-effective method has been demonstrated on the imaging spectroscopic system for real-time, label-free, highly sensitive and high-throughput screening of biomolecular interactions.

Variability of individual genetic load: consequences for the detection of inbreeding depression.

PubMed

Restoux, Gwendal; Huot de Longchamp, Priscille; Fady, Bruno; Klein, Etienne K

2012-03-01

Inbreeding depression is a key factor affecting the persistence of natural populations, particularly when they are fragmented. In species with mixed mating systems, inbreeding depression can be estimated at the population level by regressing the average progeny fitness by the selfing rate of their mothers. We applied this method using simulated populations to investigate how population genetic parameters can affect the detection power of inbreeding depression. We simulated individual selfing rates and genetic loads from which we computed fitness values. The regression method yielded high statistical power, inbreeding depression being detected as significant (5 % level) in 92 % of the simulations. High individual variation in selfing rate and high mean genetic load led to better detection of inbreeding depression while high among-individual variation in genetic load made it more difficult to detect inbreeding depression. For a constant sampling effort, increasing the number of progenies while decreasing the number of individuals per progeny enhanced the detection power of inbreeding depression. We discuss the implication of among-mother variability of genetic load and selfing rate on inbreeding depression studies.

Power System Transient Diagnostics Based on Novel Traveling Wave Detection

NASA Astrophysics Data System (ADS)

Hamidi, Reza Jalilzadeh

Modern electrical power systems demand novel diagnostic approaches to enhancing the system resiliency by improving the state-of-the-art algorithms. The proliferation of high-voltage optical transducers and high time-resolution measurements provide opportunities to develop novel diagnostic methods of very fast transients in power systems. At the same time, emerging complex configuration, such as multi-terminal hybrid transmission systems, limits the applications of the traditional diagnostic methods, especially in fault location and health monitoring. The impedance-based fault-location methods are inefficient for cross-bounded cables, which are widely used for connection of offshore wind farms to the main grid. Thus, this dissertation first presents a novel traveling wave-based fault-location method for hybrid multi-terminal transmission systems. The proposed method utilizes time-synchronized high-sampling voltage measurements. The traveling wave arrival times (ATs) are detected by observation of the squares of wavelet transformation coefficients. Using the ATs, an over-determined set of linear equations are developed for noise reduction, and consequently, the faulty segment is determined based on the characteristics of the provided equation set. Then, the fault location is estimated. The accuracy and capabilities of the proposed fault location method are evaluated and also compared to the existing traveling-wave-based method for a wide range of fault parameters. In order to improve power systems stability, auto-reclosing (AR), single-phase auto-reclosing (SPAR), and adaptive single-phase auto-reclosing (ASPAR) methods have been developed with the final objectives of distinguishing between the transient and permanent faults to clear the transient faults without de-energization of the solid phases. However, the features of the electrical arcs (transient faults) are severely influenced by a number of random parameters, including the convection of the air and plasma, wind speed, air pressure, and humidity. Therefore, the dead-time (the de-energization duration of the faulty phase) is unpredictable. Accordingly, conservatively long dead-times are usually considered by protection engineers. However, if the exact arc distinction time is determined, the power system stability and quality will enhance. Therefore, a new method for detection of arc extinction times leading to a new ASPAR method utilizing power line carrier (PLC) signals is presented. The efficiency of the proposed ASPAR method is verified through simulations and compared with the existing ASPAR methods. High-sampling measurements are prone to be skewed by the environmental noises and analog-to-digital (A/D) converters quantization errors. Therefore noise-contaminated measurements are the major source of uncertainties and errors in the outcomes of traveling wave-based diagnostic applications. The existing AT-detection methods do not provide enough sensitivity and selectivity at the same time. Therefore, a new AT-detection method based on short-time matrix pencil (STMPM) is developed to accurately detect ATs of the traveling waves with low signal-to-noise (SNR) ratios. As STMPM is based on matrix algebra, it is a challenging to implement this new technique in microprocessor-based fault locators. Hence, a fully recursive and computationally efficient method based on adaptive discrete Kalman filter (ADKF) is introduced for AT-detection, which is proper for microprocessors and able to accomplish accurate AT-detection for online applications such as ultra-high-speed protection. Both proposed AT-detection methods are evaluated based on extensive simulation studies, and the superior outcomes are compared to the existing methods.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Method and apparatus for acoustic plate mode liquid-solid phase transition detection

DOEpatents

Blair, Dianna S.; Freye, Gregory C.; Hughes, Robert C.; Martin, Stephen J.; Ricco, Antonio J.

1993-01-01

A method and apparatus for sensing a liquid-solid phase transition event is provided which comprises an acoustic plate mode detecting element placed in contact with a liquid or solid material which generates a high-frequency acoustic wave that is attenuated to an extent based on the physical state of the material is contact with the detecting element. The attenuation caused by the material in contact with the acoustic plate mode detecting element is used to determine the physical state of the material being detected. The method and device are particularly suited for detecting conditions such as the icing and deicing of wings of an aircraft. In another aspect of the present invention, a method is provided wherein the adhesion of a solid material to the detecting element can be measured using the apparatus of the invention.

A rapid silica spin column-based method of RNA extraction from fruit trees for RT-PCR detection of viruses.

PubMed

Yang, Fan; Wang, Guoping; Xu, Wenxing; Hong, Ni

2017-09-01

Efficient recovery of high quality RNA is very important for successful RT-PCR detection of plant RNA viruses. High levels of polyphenols and polysaccharides in plant tissues can irreversibly bind to and/or co-precipitate with RNA, which influences RNA isolation. In this study, a silica spin column-based RNA isolation method was developed by using commercially available silica columns combined with the application of a tissue lysis solution, and binding and washing buffers with high concentration guanidinium thiocyanate (GuSCN, 50% w/v), which helps remove plant proteins, polysaccharides and polyphenolic compounds. The method was successfully used to extract high quality RNA from citrus (Citrus aurantifolia), grapevine (Vitis vinifera), peach (Prunus persica), pear (Pyrus spp.), taro (Colocosia esculenta) and tobacco (Nicotiana benthamiana) samples. The method was comparable to conventional CTAB method in RNA isolation efficiency, but it was more sample-adaptable and cost-effective than commercial kits. High quality RNA isolated using silica spin column-based method was successfully used for the RT-PCR and/or multiplex RT-PCR amplification of woody fruit tree viruses and a viroid. The study provided a useful tool for the detection and characterization of plant viruses. Copyright © 2017 Elsevier B.V. All rights reserved.

Method 447.0 - Determination of Chlorophylls a and b and Identification of Other Pigments of Interest in Marine and Freshwater Algae Using High Performance Liquid Chromatography with Visible Wavelength Detection

EPA Science Inventory

This method provides a procedure for determination of chlorophylls a (chl a) and b (chl b) found in marine and freshwater phytoplankton. Reversed phase high performance liquid chromatography (HPLC) with detection at 440 nm is used to separate the pigments from a complex pigment ...

An Effective Electrical Resonance-Based Method to Detect Delamination in Thermal Barrier Coating

NASA Astrophysics Data System (ADS)

Kim, Jong Min; Park, Jae-Ha; Lee, Ho Girl; Kim, Hak-Joon; Song, Sung-Jin; Seok, Chang-Sung; Lee, Young-Ze

2017-12-01

This research proposes a simple yet highly sensitive method based on electrical resonance of an eddy-current probe to detect delamination of thermal barrier coating (TBC). This method can directly measure the mechanical characteristics of TBC compared to conventional ultrasonic testing and infrared thermography methods. The electrical resonance-based method can detect the delamination of TBC from the metallic bond coat by shifting the electrical impedance of eddy current testing (ECT) probe coupling with degraded TBC, and, due to this shift, the resonant frequencies near the peak impedance of ECT probe revealed high sensitivity to the delamination. In order to verify the performance of the proposed method, a simple experiment is performed with degraded TBC specimens by thermal cyclic exposure. Consequently, the delamination with growth of thermally grown oxide in a TBC system is experimentally identified. Additionally, the results are in good agreement with the results obtained from ultrasonic C-scanning.

An Effective Electrical Resonance-Based Method to Detect Delamination in Thermal Barrier Coating

NASA Astrophysics Data System (ADS)

Kim, Jong Min; Park, Jae-Ha; Lee, Ho Girl; Kim, Hak-Joon; Song, Sung-Jin; Seok, Chang-Sung; Lee, Young-Ze

2018-02-01

This research proposes a simple yet highly sensitive method based on electrical resonance of an eddy-current probe to detect delamination of thermal barrier coating (TBC). This method can directly measure the mechanical characteristics of TBC compared to conventional ultrasonic testing and infrared thermography methods. The electrical resonance-based method can detect the delamination of TBC from the metallic bond coat by shifting the electrical impedance of eddy current testing (ECT) probe coupling with degraded TBC, and, due to this shift, the resonant frequencies near the peak impedance of ECT probe revealed high sensitivity to the delamination. In order to verify the performance of the proposed method, a simple experiment is performed with degraded TBC specimens by thermal cyclic exposure. Consequently, the delamination with growth of thermally grown oxide in a TBC system is experimentally identified. Additionally, the results are in good agreement with the results obtained from ultrasonic C-scanning.

Review of Methods for the Detection and Determination of Malachite Green and Leuco-Malachite Green in Aquaculture.

PubMed

Zhou, Xinhui; Zhang, Jiaran; Pan, Zhongli; Li, Daoliang

2018-05-14

Malachite green (MG) has been widely used in the aquaculture industry as a fungicide and parasiticide because of its high efficiency and low cost, and it is commonly found in aquatic products and environmental water. However, MG and its primary metabolite, leuco-malachite green (LMG), are also toxic inorganic contaminants that are hazardous to the health of humans and other organisms. A variety of methods have been proposed in recent years for detecting and monitoring MG and LMG. This article was compiled as a general review of the methods proposed for MG and LMG detection, and several important detection parameters, such as the limit of detection, recovery and relative standard deviation, were tabulated. The analytical methods for the determination of MG and LMG in various matrices include high-performance liquid chromatography separation-based methods, liquid chromatography tandem mass spectrometry, surface-enhanced Raman spectroscopy, electrochemical methods, immunological assays, spectrophotometry and fluorescent methods which were described in detail in this article. In addition, some sample preparation techniques were also described. This review can provide expert guidance to the reader on the advantages, disadvantages and applicability of the different methodologies. This review also discussed challenges and several perspectives on the future trends in the determination of MG and LMG.

DETERMINATION OF CARBENDAZIM IN WATER BY HIGH-PERFORMANCE IMMUNOAFFINITY CHROMATOGRAPHY ON-LINE WITH HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY WITH DIODE-ARRAY OR MASS SPECTROMETRIC DETECTION

EPA Science Inventory

An automated method for the determination of carbendazim in water that combines high-performance immunoaffinity chromatography (HPIAC), high-performance liquid chromatography (HPLC) in the reversed-phase mode, and detection by either UV-Vis diode array detector (DAD) spectroscopy...

A novel approach for quantitation of nonderivatized sialic acid in protein therapeutics using hydrophilic interaction chromatographic separation and nano quantity analyte detection.

PubMed

Chemmalil, Letha; Suravajjala, Sreekanth; See, Kate; Jordan, Eric; Furtado, Marsha; Sun, Chong; Hosselet, Stephen

2015-01-01

This paper describes a novel approach for the quantitation of nonderivatized sialic acid in glycoproteins, separated by hydrophilic interaction chromatography, and detection by Nano Quantity Analyte Detector (NQAD). The detection technique of NQAD is based on measuring change in the size of dry aerosol and converting the particle count rate into chromatographic output signal. NQAD detector is suitable for the detection of sialic acid, which lacks sufficiently active chromophore or fluorophore. The water condensation particle counting technology allows the analyte to be enlarged using water vapor to provide highest sensitivity. Derivatization-free analysis of glycoproteins using HPLC/NQAD method with PolyGLYCOPLEX™ amide column is well correlated with HPLC method with precolumn derivatization using 1, 2-diamino-4, 5-methylenedioxybenzene (DMB) as well as the Dionex-based high-pH anion-exchange chromatography (or ion chromatography) with pulsed amperometric detection (HPAEC-PAD). With the elimination of derivatization step, HPLC/NQAD method is more efficient than HPLC/DMB method. HPLC/NQAD method is more reproducible than HPAEC-PAD method as HPAEC-PAD method suffers high variability because of electrode fouling during analysis. Overall, HPLC/NQAD method offers broad linear dynamic range as well as excellent precision, accuracy, repeatability, reliability, and ease of use, with acceptable comparability to the commonly used HPAEC-PAD and HPLC/DMB methods. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Dual channel sensitive detection of hsa-miR-21 based on rolling circle amplification and quantum dots tagging.

PubMed

Wangt, Dan-Chen; Hu, Li-Hui; Zhou, Yu-Hui; Huang, Yu-Ting; Li, Xinhua; Zhu, Jun-Jie

2014-04-01

An isothermal, highly sensitive and specific assay for the detection of hsa-miR-21 with the integration of QDs tagging and rolling circle amplification was offered. In addition, a dual channel strategy for miRNA detection was proposed: anodic stripping voltammetry (ASV) and fluorescent method were both performed for the final Cd2+ signal readout. The designed strategy exhibited good specificity to hsa-miR-21 and presented comparable detection results by detection methods.

Automated crack detection in conductive smart-concrete structures using a resistor mesh model

NASA Astrophysics Data System (ADS)

Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon

2018-03-01

Various nondestructive evaluation techniques are currently used to automatically detect and monitor cracks in concrete infrastructure. However, these methods often lack the scalability and cost-effectiveness over large geometries. A solution is the use of self-sensing carbon-doped cementitious materials. These self-sensing materials are capable of providing a measurable change in electrical output that can be related to their damage state. Previous work by the authors showed that a resistor mesh model could be used to track damage in structural components fabricated from electrically conductive concrete, where damage was located through the identification of high resistance value resistors in a resistor mesh model. In this work, an automated damage detection strategy that works through placing high value resistors into the previously developed resistor mesh model using a sequential Monte Carlo method is introduced. Here, high value resistors are used to mimic the internal condition of damaged cementitious specimens. The proposed automated damage detection method is experimentally validated using a 500 × 500 × 50 mm3 reinforced cement paste plate doped with multi-walled carbon nanotubes exposed to 100 identical impact tests. Results demonstrate that the proposed Monte Carlo method is capable of detecting and localizing the most prominent damage in a structure, demonstrating that automated damage detection in smart-concrete structures is a promising strategy for real-time structural health monitoring of civil infrastructure.

Quality evaluation of moluodan concentrated pill using high-performance liquid chromatography fingerprinting coupled with chemometrics.

PubMed

Tao, Lingyan; Zhang, Qing; Wu, Yongjiang; Liu, Xuesong

2016-12-01

In this study, a fast and effective high-performance liquid chromatography method was developed to obtain a fingerprint chromatogram and quantitative analysis simultaneously of four indexes including gallic acid, chlorogenic acid, albiflorin and paeoniflorin of the traditional Chinese medicine Moluodan Concentrated Pill. The method was performed by using a Waters X-bridge C 18 reversed phase column on an Agilent 1200S high-performance liquid chromatography system coupled with diode array detection. The mobile phase of the high-performance liquid chromatography method was composed of 20 mmol/L phosphate solution and acetonitrile with a 1 mL/min eluent velocity, under a detection temperature of 30°C and a UV detection wavelength of 254 nm. After the methodology validation, 16 batches of Moluodan Concentrated Pill were analyzed by this high-performance liquid chromatography method and both qualitative and quantitative evaluation results were achieved by similarity analysis, principal component analysis and hierarchical cluster analysis. The results of these three chemometrics were in good agreement and all indicated that batch 10 and batch 16 showed significant differences with the other 14 batches. This suggested that the developed high-performance liquid chromatography method could be applied in the quality evaluation of Moluodan Concentrated Pill. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

Study on thin wideband applicator for detecting blood characteristics in human body

NASA Astrophysics Data System (ADS)

Bamba, Kazuki; Kuki, Takao; Nikawa, Yoshio

2016-11-01

Preventive care as well as early detection method and monitoring technique for diseases are highly attracted attention to increase quality of life. Noninvasive measurement method for blood characteristics in body is expected by patients with kidney dysfunction. Complex permittivity of blood is changed a few present at 6GHz. This change is caused by the change of water and albumin contents in blood. In this study, to detect blood characteristics in human body, experiments with phantom model has been performed using thin wideband applicator for examining microwave transmission up to 6GHz. The thin wideband applicator has advantages for detecting living body information in detail. The thin wideband applicator is designed based on Antipodal Vivaldi Antenna and is not required any balun and is very easy handling. Using developed Antipodal Vivaldi Antenna, transmission coefficient can be obtained as a function of thickness of phantom model with high sensitivity. Using this method, highly sensitive sensor for obtaining characteristics of blood in body can be developed.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

77 FR 8258 - Availability of ICCVAM Evaluation Report and Recommendations on the Usefulness and Limitations of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... development of BG1Luc ER TA test method performance standards. ICCVAM assigned the activities a high priority... Vitro Test Methods for Detecting Potential Endocrine Disruptors. Research Triangle Park, NC: National...Final.pdf . ICCVAM. 2003a. ICCVAM Evaluation of In Vitro Test Methods For Detecting Potential Endocrine...

A novel method for the rapid detection of benzo(a)pyrene in liquid milk by dimethyl sulfoxide selectively enhanced synchronous fluorescence spectrometry.

PubMed

Lin, Li-Rong; Luo, He-Dong; Li, Xiu-Ying; Li, Na; Zhou, Na; Jia, Yu-Zhu; Liu, Yi-Hong; Li, Yao-Qun

2014-01-01

Based on the high solubility efficiency and strong fluorescence response of benzo(a)pyrene (BaP) in dimethyl sulfoxide in combination with the high-performance derivative constant-energy synchronous fluorescence spectroscopic (DCESFS) technique, a simple, sensitive and economic method was developed for the determination of BaP in liquid milk. This method comprises ultrasound-assisted solvent extraction, solvent replacement and DCESFS detection. No saponification or other tedious clean-up procedures were needed. The recoveries of BaP in different milk samples were greater than 82%. Detection limits in full- and low-fat milk were 0.03 and 0.04 μg kg(-1), respectively.

Using occupancy models to investigate the prevalence of ectoparasitic vectors on hosts: an example with fleas on prairie dogs

USGS Publications Warehouse

Eads, David A.; Biggins, Dean E.; Doherty, Paul F.; Gage, Kenneth L.; Huyvaert, Kathryn P.; Long, Dustin H.; Antolin, Michael F.

2013-01-01

Ectoparasites are often difficult to detect in the field. We developed a method that can be used with occupancy models to estimate the prevalence of ectoparasites on hosts, and to investigate factors that influence rates of ectoparasite occupancy while accounting for imperfect detection. We describe the approach using a study of fleas (Siphonaptera) on black-tailed prairie dogs (Cynomys ludovicianus). During each primary occasion (monthly trapping events), we combed a prairie dog three consecutive times to detect fleas (15 s/combing). We used robust design occupancy modeling to evaluate hypotheses for factors that might correlate with the occurrence of fleas on prairie dogs, and factors that might influence the rate at which prairie dogs are colonized by fleas. Our combing method was highly effective; dislodged fleas fell into a tub of water and could not escape, and there was an estimated 99.3% probability of detecting a flea on an occupied host when using three combings. While overall detection was high, the probability of detection was always <1.00 during each primary combing occasion, highlighting the importance of considering imperfect detection. The combing method (removal of fleas) caused a decline in detection during primary occasions, and we accounted for that decline to avoid inflated estimates of occupancy. Regarding prairie dogs, flea occupancy was heightened in old/natural colonies of prairie dogs, and on hosts that were in poor condition. Occupancy was initially low in plots with high densities of prairie dogs, but, as the study progressed, the rate of flea colonization increased in plots with high densities of prairie dogs in particular. Our methodology can be used to improve studies of ectoparasites, especially when the probability of detection is low. Moreover, the method can be modified to investigate the co-occurrence of ectoparasite species, and community level factors such as species richness and interspecific interactions.

Temporal similarity perfusion mapping: A standardized and model-free method for detecting perfusion deficits in stroke

PubMed Central

Song, Sunbin; Luby, Marie; Edwardson, Matthew A.; Brown, Tyler; Shah, Shreyansh; Cox, Robert W.; Saad, Ziad S.; Reynolds, Richard C.; Glen, Daniel R.; Cohen, Leonardo G.; Latour, Lawrence L.

2017-01-01

Introduction Interpretation of the extent of perfusion deficits in stroke MRI is highly dependent on the method used for analyzing the perfusion-weighted signal intensity time-series after gadolinium injection. In this study, we introduce a new model-free standardized method of temporal similarity perfusion (TSP) mapping for perfusion deficit detection and test its ability and reliability in acute ischemia. Materials and methods Forty patients with an ischemic stroke or transient ischemic attack were included. Two blinded readers compared real-time generated interactive maps and automatically generated TSP maps to traditional TTP/MTT maps for presence of perfusion deficits. Lesion volumes were compared for volumetric inter-rater reliability, spatial concordance between perfusion deficits and healthy tissue and contrast-to-noise ratio (CNR). Results Perfusion deficits were correctly detected in all patients with acute ischemia. Inter-rater reliability was higher for TSP when compared to TTP/MTT maps and there was a high similarity between the lesion volumes depicted on TSP and TTP/MTT (r(18) = 0.73). The Pearson's correlation between lesions calculated on TSP and traditional maps was high (r(18) = 0.73, p<0.0003), however the effective CNR was greater for TSP compared to TTP (352.3 vs 283.5, t(19) = 2.6, p<0.03.) and MTT (228.3, t(19) = 2.8, p<0.03). Discussion TSP maps provide a reliable and robust model-free method for accurate perfusion deficit detection and improve lesion delineation compared to traditional methods. This simple method is also computationally faster and more easily automated than model-based methods. This method can potentially improve the speed and accuracy in perfusion deficit detection for acute stroke treatment and clinical trial inclusion decision-making. PMID:28973000

Detection of artifacts from high energy bursts in neonatal EEG.

PubMed

Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar

2013-11-01

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the feature subset producing highest classification accuracy. The suggested feature based classification method is executed using our recorded neonatal EEG dataset, consisting of burst and artifact segments. We obtain 78% sensitivity and 72% specificity as the accuracy measures. The accuracy obtained using the proposed method is found to be about 20% higher than that of the reference approaches. Joint use of the proposed method with our previous work on burst detection outperforms reference methods on simultaneous burst and artifact detection. As the proposed method supports detection of a wide range of artifact patterns, it can be improved to incorporate the detection of artifacts within other seizure patterns and background EEG information as well. © 2013 Elsevier Ltd. All rights reserved.

Multiscale peak detection in wavelet space.

PubMed

Zhang, Zhi-Min; Tong, Xia; Peng, Ying; Ma, Pan; Zhang, Ming-Jin; Lu, Hong-Mei; Chen, Xiao-Qing; Liang, Yi-Zeng

2015-12-07

Accurate peak detection is essential for analyzing high-throughput datasets generated by analytical instruments. Derivatives with noise reduction and matched filtration are frequently used, but they are sensitive to baseline variations, random noise and deviations in the peak shape. A continuous wavelet transform (CWT)-based method is more practical and popular in this situation, which can increase the accuracy and reliability by identifying peaks across scales in wavelet space and implicitly removing noise as well as the baseline. However, its computational load is relatively high and the estimated features of peaks may not be accurate in the case of peaks that are overlapping, dense or weak. In this study, we present multi-scale peak detection (MSPD) by taking full advantage of additional information in wavelet space including ridges, valleys, and zero-crossings. It can achieve a high accuracy by thresholding each detected peak with the maximum of its ridge. It has been comprehensively evaluated with MALDI-TOF spectra in proteomics, the CAMDA 2006 SELDI dataset as well as the Romanian database of Raman spectra, which is particularly suitable for detecting peaks in high-throughput analytical signals. Receiver operating characteristic (ROC) curves show that MSPD can detect more true peaks while keeping the false discovery rate lower than MassSpecWavelet and MALDIquant methods. Superior results in Raman spectra suggest that MSPD seems to be a more universal method for peak detection. MSPD has been designed and implemented efficiently in Python and Cython. It is available as an open source package at .

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

PubMed

Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang

2017-10-13

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belinsky, Steven A; Palmisano, William A

A molecular marker-based method for monitoring and detecting cancer in humans. Aberrant methylation of gene promoters is a marker for cancer risk in humans. A two-stage, or "nested" polymerase chain reaction method is disclosed for detecting methylated DNA sequences at sufficiently high levels of sensitivity to permit cancer screening in biological fluid samples, such as sputum, obtained non-invasively. The method is for detecting the aberrant methylation of the p16 gene, O 6-methylguanine-DNA methyltransferase gene, Death-associated protein kinase gene, RAS-associated family 1 gene, or other gene promoters. The method offers a potentially powerful approach to population-based screening for the detection ofmore » lung and other cancers.« less

Water-Tree Modelling and Detection for Underground Cables

NASA Astrophysics Data System (ADS)

Chen, Qi

In recent years, aging infrastructure has become a major concern for the power industry. Since its inception in early 20th century, the electrical system has been the cornerstone of an industrial society. Stable and uninterrupted delivery of electrical power is now a base necessity for the modern world. As the times march-on, however, the electrical infrastructure ages and there is the inevitable need to renew and replace the existing system. Unfortunately, due to time and financial constraints, many electrical systems today are forced to operate beyond their original design and power utilities must find ways to prolong the lifespan of older equipment. Thus, the concept of preventative maintenance arises. Preventative maintenance allows old equipment to operate longer and at better efficiency, but in order to implement preventative maintenance, the operators must know minute details of the electrical system, especially some of the harder to assess issues such water-tree. Water-tree induced insulation degradation is a problem typically associated with older cable systems. It is a very high impedance phenomenon and it is difficult to detect using traditional methods such as Tan-Delta or Partial Discharge. The proposed dissertation studies water-tree development in underground cables, potential methods to detect water-tree location and water-tree severity estimation. The dissertation begins by developing mathematical models of water-tree using finite element analysis. The method focuses on surface-originated vented tree, the most prominent type of water-tree fault in the field. Using the standard operation parameters of North American electrical systems, the water-tree boundary conditions are defined. By applying finite element analysis technique, the complex water-tree structure is broken down to homogeneous components. The result is a generalized representation of water-tree capacitance at different stages of development. The result from the finite element analysis is used to model water-tree in large system. Both empirical measurements and the mathematical model show that the impedance of early-stage water-tree is extremely large. As the result, traditional detection methods such Tan-Delta or Partial Discharge are not effective due to the excessively high accuracy requirement. A high-frequency pulse detection method is developed instead. The water-tree impedance is capacitive in nature and it can be reduced to manageable level by high-frequency inputs. The method is able to determine the location of early-stage water-tree in long-distance cables using economically feasible equipment. A pattern recognition method is developed to estimate the severity of water-tree using its pulse response from the high-frequency test method. The early-warning system for water-tree appearance is a tool developed to assist the practical implementation of the high-frequency pulse detection method. Although the equipment used by the detection method is economically feasible, it is still a specialized test and not designed for constant monitoring of the system. The test also place heavy stress on the cable and it is most effective when the cable is taken offline. As the result, utilities need a method to estimate the likelihood of water-tree presence before subjecting the cable to the specialized test. The early-warning system takes advantage of naturally occurring high-frequency events in the system and uses a deviation-comparison method to estimate the probability of water-tree presence on the cable. If the likelihood is high, then the utility can use the high-frequency pulse detection method to obtain accurate results. Specific pulse response patterns can be used to calculate the capacitance of water-tree. The calculated result, however, is subjected to margins of error due to limitations from the real system. There are both long-term and short-term methods to improve the accuracy. Computation algorithm improvement allows immediate improvement on accuracy of the capacitance estimation. The probability distribution of the calculation solution showed that improvements in waveform time-step measurement allow fundamental improves to the overall result.

Total Count of Salmonella typhimurium Coupled on Water Soluble CdSe Quantum Dots by Fluorescence Detection

NASA Astrophysics Data System (ADS)

Feliciano Crespo, Raquel; Perales Perez, Oscar Juan; Ramirez, C.

2018-05-01

Health diseases due to the ingestion of water or food contaminated with pathogenic microorganisms are a main health problem around the world. The traditional methods for detecting foodborne pathogens are time-consuming (on the order of days). The development of methods that can help to detect and identify foodborne pathogens with high sensitivity and specificity have been proposed to overcome the limitations of traditional methods. Accordingly, this research is focused on the development of an experimental protocol for a high-sensitivity detection and quantification of bacterial pathogens with reduced detection times. This will lead to the development of a portable and low-cost technology with the opportunity to make onsite detection of pathogenic species. The proposed approach has modified the route reported in the literature; the method proposed is expected to be sensitive enough to detect a low limit of 102 CFU/mL counts of bacteria. The fluorescence-based method was tested in presence of Salmonella typhimurium (ATCC 14020) and Escherichia coli (ATCC 25922). CdSe water-soluble quantum dots (QDs) were synthesized in aqueous phase in presence of thioglycolic acid (TGA) as a capping agent. As-synthesized QDs were characterized by x-ray diffraction, near infrared and Fourier transform infrared spectroscopy, UV-Vis and photoluminescence techniques. Results of the CdSe/TGA-bacteria coupling and the determination of the corresponding quantification profiles (calibration curves) will be presented and discussed.

A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

PubMed

Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

2016-09-01

Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05). Copyright © 2016 Elsevier Ltd. All rights reserved.

High-sensitivity imaging method of singlet oxygen and superoxide anion in photodynamic and sonodynamic actions

NASA Astrophysics Data System (ADS)

Xing, Da; He, Yonghong; Hao, Min; Chen, Qun

2004-07-01

A novel method of photodynamic diagnosis (PDD) of cancer mediated by chemiluminescence (CL) probe is presented. The mechanism for photodynamic therapy (PDT) involves reactive oxygen species (ROS), such as singlet oxygen (1O2) and superoxide (O2-), generated by during the photochemical process. Both 1O2 and O2- can react with Cypridina luciferin analogue (FCLA), a highly selective CL probe for detecting the ROS. Chemiluminescence from the reaction of FCLA with the ROS, at about 530 nm, was detected by a highly sensitive ICCD system. The CL was markedly inhibited by the addition of 10 mmol/L sodium azide (NaN3) in a sample solution. Similar phenomena, with lesser extents of changes, were observed at the additions of 10 μmol/L superoxide dismutase (SOD), 10 mmol/L mannitol, and 100 μg/mL catalase, respectively. This indicates that the detected CL signals were mainly from ROS generated during the photosensitization reactions. Also, the chemiluminescence method was used to detect the ROS during sonodynamic action, both in vitro and in vivo. ROS formation during sonosensitizations of HpD and ATX-70 were detected using our newly-developed imaging technique, in real time, on tumor bearing animals. This method can provide a new means in clinics for tumor diagnosis.

Spoofing detection on facial images recognition using LBP and GLCM combination

NASA Astrophysics Data System (ADS)

Sthevanie, F.; Ramadhani, K. N.

2018-03-01

The challenge for the facial based security system is how to detect facial image falsification such as facial image spoofing. Spoofing occurs when someone try to pretend as a registered user to obtain illegal access and gain advantage from the protected system. This research implements facial image spoofing detection method by analyzing image texture. The proposed method for texture analysis combines the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) method. The experimental results show that spoofing detection using LBP and GLCM combination achieves high detection rate compared to that of using only LBP feature or GLCM feature.

Magnetically-focusing biochip structures for high-speed active biosensing with improved selectivity.

PubMed

Yoo, Haneul; Lee, Dong Jun; Kim, Daesan; Park, Juhun; Chen, Xing; Hong, Seunghun

2018-06-29

We report a magnetically-focusing biochip structure enabling a single layered magnetic trap-and-release cycle for biosensors with an improved detection speed and selectivity. Here, magnetic beads functionalized with specific receptor molecules were utilized to trap target molecules in a solution and transport actively to and away from the sensor surfaces to enhance the detection speed and reduce the non-specific bindings, respectively. Using our method, we demonstrated the high speed detection of IL-13 antigens with the improved detection speed by more than an order of magnitude. Furthermore, the release step in our method was found to reduce the non-specific bindings and improve the selectivity and sensitivity of biosensors. This method is a simple but powerful strategy and should open up various applications such as ultra-fast biosensors for point-of-care services.

Magnetically-focusing biochip structures for high-speed active biosensing with improved selectivity

NASA Astrophysics Data System (ADS)

Yoo, Haneul; Lee, Dong Jun; Kim, Daesan; Park, Juhun; Chen, Xing; Hong, Seunghun

2018-06-01

We report a magnetically-focusing biochip structure enabling a single layered magnetic trap-and-release cycle for biosensors with an improved detection speed and selectivity. Here, magnetic beads functionalized with specific receptor molecules were utilized to trap target molecules in a solution and transport actively to and away from the sensor surfaces to enhance the detection speed and reduce the non-specific bindings, respectively. Using our method, we demonstrated the high speed detection of IL-13 antigens with the improved detection speed by more than an order of magnitude. Furthermore, the release step in our method was found to reduce the non-specific bindings and improve the selectivity and sensitivity of biosensors. This method is a simple but powerful strategy and should open up various applications such as ultra-fast biosensors for point-of-care services.

Establishment and application of cross-priming isothermal amplification coupled with lateral flow dipstick (CPA-LFD) for rapid and specific detection of red-spotted grouper nervous necrosis virus.

PubMed

Su, Zi Dan; Shi, Cheng Yin; Huang, Jie; Shen, Gui Ming; Li, Jin; Wang, Sheng Qiang; Fan, Chao

2015-09-26

Red-spotted grouper nervous necrosis virus (RGNNV) is an important pathogen that causes diseases in many species of fish in marine aquaculture. The larvae and juveniles are more easily infected by RGNNV and the cumulative mortality is as high as 100 % after being infected with RGNNV. This virus imposes a serious threat to aquaculture of grouper fry. This study aimed to establish a simple, accurate and highly sensitive method for rapid detection of RGNNV on the spot. In this study, the primers specifically targeting RGNNV were designed and cross-priming isothermal amplification (CPA) system was established. The product amplified by CPA was detected through visualization with lateral flow dipstick (LFD). Three important parameters, including the amplification temperature, the concentration of dNTPs and the concentration of Mg(2+) for the CPA system, were optimized. The sensitivity and specificity of this method for RGNNV were tested and compared with those of the conventional RT-PCR and real-time quantitative RT-PCR (qRT-PCR). The optimized conditions for the CPA amplification system were determined as follows: the optimal amplification temperature, the optimized concentration of dNTPs and the concentration for Mg(2+) were 69 °C, 1.2 mmol/L and 5 mmol/L, respectively. The lowest limit of detection (LLOD) of this method for RGNNV was 10(1) copies/μL of RNA sample, which was 10 times lower than that of conventional RT-PCR and comparable to that of RT-qPCR. This method was specific for RGNNV in combination with SJNNV and had no cross-reactions with 8 types of virus and bacterial strains tested. This method was successfully applied to detect RGNNV in fish samples. This study established a CPA-LFD method for detection of RGNNV. This method is simple and rapid with high sensitivity and good specificity and can be widely applied for rapid detection of this virus on the spot.

[Application of optical flow dynamic texture in land use/cover change detection].

PubMed

Yan, Li; Gong, Yi-Long; Zhang, Yi; Duan, Wei

2014-11-01

In the present study, a novel change detection approach for high resolution remote sensing images is proposed based on the optical flow dynamic texture (OFDT), which could achieve the land use & land cover change information automatically with a dynamic description of ground-object changes. This paper describes the ground-object gradual change process from the principle using optical flow theory, which breaks the ground-object sudden change hypothesis in remote sensing change detection methods in the past. As the steps of this method are simple, it could be integrated in the systems and software such as Land Resource Management and Urban Planning software that needs to find ground-object changes. This method takes into account the temporal dimension feature between remote sensing images, which provides a richer set of information for remote sensing change detection, thereby improving the status that most of the change detection methods are mainly dependent on the spatial dimension information. In this article, optical flow dynamic texture is the basic reflection of changes, and it is used in high resolution remote sensing image support vector machine post-classification change detection, combined with spectral information. The texture in the temporal dimension which is considered in this article has a smaller amount of data than most of the textures in the spatial dimensions. The highly automated texture computing has only one parameter to set, which could relax the onerous manual evaluation present status. The effectiveness of the proposed approach is evaluated with the 2011 and 2012 QuickBird datasets covering Duerbert Mongolian Autonomous County of Daqing City, China. Then, the effects of different optical flow smooth coefficient and the impact on the description of the ground-object changes in the method are deeply analyzed: The experiment result is satisfactory, with an 87.29% overall accuracy and an 0.850 7 Kappa index, and the method achieves better performance than the post-classification change detection methods using spectral information only.

Robust Vehicle Detection under Various Environmental Conditions Using an Infrared Thermal Camera and Its Application to Road Traffic Flow Monitoring

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-01-01

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as “our previous method”) using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as “our new method”). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal. PMID:23774988

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry.

PubMed

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2010-11-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000-15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert's visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition.

Label-Free Toxin Detection by Means of Time-Resolved Electrochemical Impedance Spectroscopy

PubMed Central

Chai, Changhoon; Takhistov, Paul

2010-01-01

The real-time detection of trace concentrations of biological toxins requires significant improvement of the detection methods from those reported in the literature. To develop a highly sensitive and selective detection device it is necessary to determine the optimal measuring conditions for the electrochemical sensor in three domains: time, frequency and polarization potential. In this work we utilized a time-resolved electrochemical impedance spectroscopy for the detection of trace concentrations of Staphylococcus enterotoxin B (SEB). An anti-SEB antibody has been attached to the nano-porous aluminum surface using 3-aminopropyltriethoxysilane/glutaraldehyde coupling system. This immobilization method allows fabrication of a highly reproducible and stable sensing device. Using developed immobilization procedure and optimized detection regime, it is possible to determine the presence of SEB at the levels as low as 10 pg/mL in 15 minutes. PMID:22315560

Bayesian Peptide Peak Detection for High Resolution TOF Mass Spectrometry

PubMed Central

Zhang, Jianqiu; Zhou, Xiaobo; Wang, Honghui; Suffredini, Anthony; Zhang, Lin; Huang, Yufei; Wong, Stephen

2011-01-01

In this paper, we address the issue of peptide ion peak detection for high resolution time-of-flight (TOF) mass spectrometry (MS) data. A novel Bayesian peptide ion peak detection method is proposed for TOF data with resolution of 10 000–15 000 full width at half-maximum (FWHW). MS spectra exhibit distinct characteristics at this resolution, which are captured in a novel parametric model. Based on the proposed parametric model, a Bayesian peak detection algorithm based on Markov chain Monte Carlo (MCMC) sampling is developed. The proposed algorithm is tested on both simulated and real datasets. The results show a significant improvement in detection performance over a commonly employed method. The results also agree with expert’s visual inspection. Moreover, better detection consistency is achieved across MS datasets from patients with identical pathological condition. PMID:21544266

High-speed shaking of frozen blood clots for extraction of human and malaria parasite DNA

PubMed Central

2011-01-01

Background Frozen blood clots remaining after serum collection is an often disregarded source of host and pathogen DNA due to troublesome handling and suboptimal outcome. Methods High-speed shaking of clot samples in a cell disruptor manufactured for homogenization of tissue and faecal specimens was evaluated for processing frozen blood clots for DNA extraction. The method was compared to two commercial clot protocols based on a chemical kit and centrifugation through a plastic sieve, followed by the same DNA extraction protocol. Blood clots with different levels of parasitaemia (1-1,000 p/μl) were prepared from parasite cultures to assess sensitivity of PCR detection. In addition, clots retrieved from serum samples collected within two epidemiological studies in Kenya (n = 630) were processed by high speed shaking and analysed by PCR for detection of malaria parasites and the human α-thalassaemia gene. Results High speed shaking succeeded in fully dispersing the clots and the method generated the highest DNA yield. The level of PCR detection of P. falciparum parasites and the human thalassaemia gene was the same as samples optimally collected with an anticoagulant. The commercial clot protocol and centrifugation through a sieve failed to fully dissolve the clots and resulted in lower sensitivity of PCR detection. Conclusions High speed shaking was a simple and efficacious method for homogenizing frozen blood clots before DNA purification and resulted in PCR templates of high quality both from humans and malaria parasites. This novel method enables genetic studies from stored blood clots. PMID:21824391

Virus Particle Detection by Convolutional Neural Network in Transmission Electron Microscopy Images.

PubMed

Ito, Eisuke; Sato, Takaaki; Sano, Daisuke; Utagawa, Etsuko; Kato, Tsuyoshi

2018-06-01

A new computational method for the detection of virus particles in transmission electron microscopy (TEM) images is presented. Our approach is to use a convolutional neural network that transforms a TEM image to a probabilistic map that indicates where virus particles exist in the image. Our proposed approach automatically and simultaneously learns both discriminative features and classifier for virus particle detection by machine learning, in contrast to existing methods that are based on handcrafted features that yield many false positives and require several postprocessing steps. The detection performance of the proposed method was assessed against a dataset of TEM images containing feline calicivirus particles and compared with several existing detection methods, and the state-of-the-art performance of the developed method for detecting virus was demonstrated. Since our method is based on supervised learning that requires both the input images and their corresponding annotations, it is basically used for detection of already-known viruses. However, the method is highly flexible, and the convolutional networks can adapt themselves to any virus particles by learning automatically from an annotated dataset.

Probabilistic model for quick detection of dissimilar binary images

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2015-09-01

We present a quick method to detect dissimilar binary images. The method is based on a "probabilistic matching model" for image matching. The matching model is used to predict the probability of occurrence of distinct-dissimilar image pairs (completely different images) when matching one image to another. Based on this model, distinct-dissimilar images can be detected by matching only a few points between two images with high confidence, namely 11 points for a 99.9% successful detection rate. For image pairs that are dissimilar but not distinct-dissimilar, more points need to be mapped. The number of points required to attain a certain successful detection rate or confidence depends on the amount of similarity between the compared images. As this similarity increases, more points are required. For example, images that differ by 1% can be detected by mapping fewer than 70 points on average. More importantly, the model is image size invariant; so, images of any sizes will produce high confidence levels with a limited number of matched points. As a result, this method does not suffer from the image size handicap that impedes current methods. We report on extensive tests conducted on real images of different sizes.

[A quick algorithm of dynamic spectrum photoelectric pulse wave detection based on LabVIEW].

PubMed

Lin, Ling; Li, Na; Li, Gang

2010-02-01

Dynamic spectrum (DS) detection is attractive among the numerous noninvasive blood component detection methods because of the elimination of the main interference of the individual discrepancy and measure conditions. DS is a kind of spectrum extracted from the photoelectric pulse wave and closely relative to the artery blood. It can be used in a noninvasive blood component concentration examination. The key issues in DS detection are high detection precision and high operation speed. The precision of measure can be advanced by making use of over-sampling and lock-in amplifying on the pick-up of photoelectric pulse wave in DS detection. In the present paper, the theory expression formula of the over-sampling and lock-in amplifying method was deduced firstly. Then in order to overcome the problems of great data and excessive operation brought on by this technology, a quick algorithm based on LabVIEW and a method of using external C code applied in the pick-up of photoelectric pulse wave were presented. Experimental verification was conducted in the environment of LabVIEW. The results show that by the method pres ented, the speed of operation was promoted rapidly and the data memory was reduced largely.

Direct antigen detection from immunoprecipitated beads using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; a new method for immunobeads-mass spectrometry (iMS).

PubMed

Shimada, Takashi; Toyama, Atsuhiko; Aoki, Chikage; Aoki, Yutaka; Tanaka, Koichi; Sato, Taka-Aki

2011-12-15

One-step detection of biological molecules is one of the principal techniques for clinical diagnosis, and the potential of mass spectrometry for biomarker detection has been a promising new approach in the field of medical sciences. We demonstrate here a new and high-sensitivity method that we termed immunobeads-mass spectrometry (iMS), which combines conventional immunoprecipitation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The key feature of iMS is the MS-compatible condition of immunoprecipitation using detergents with a monosaccaride-C8 alkyl chain or a disaccharide-C10 alkyl chain, and the minimized number of steps required for high-sensitivity detection of target peptides in serum or biological fluid. This was achieved by optimizing the wash buffer and subjecting the immunobeads directly to MALDI-TOF MS analysis. Using this method, we showed that 1 fmol of amyloid beta peptide spiked in serum was readily detectable, demonstrating the powerful tool of iMS as a biomarker detection method. Copyright © 2011 John Wiley & Sons, Ltd.

Electrochemical and Infrared Absorption Spectroscopy Detection of SF6 Decomposition Products

PubMed Central

Dong, Ming; Ren, Ming; Ye, Rixin

2017-01-01

Sulfur hexafluoride (SF6) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF6 decomposition and ultimately generates several types of decomposition products. These SF6 decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF6 decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF6 gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF6 decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF6 gas decomposition and is verified to reliably and accurately detect the gas components and concentrations. PMID:29140268

Advanced DNA-Based Point-of-Care Diagnostic Methods for Plant Diseases Detection.

PubMed

Lau, Han Yih; Botella, Jose R

2017-01-01

Diagnostic technologies for the detection of plant pathogens with point-of-care capability and high multiplexing ability are an essential tool in the fight to reduce the large agricultural production losses caused by plant diseases. The main desirable characteristics for such diagnostic assays are high specificity, sensitivity, reproducibility, quickness, cost efficiency and high-throughput multiplex detection capability. This article describes and discusses various DNA-based point-of care diagnostic methods for applications in plant disease detection. Polymerase chain reaction (PCR) is the most common DNA amplification technology used for detecting various plant and animal pathogens. However, subsequent to PCR based assays, several types of nucleic acid amplification technologies have been developed to achieve higher sensitivity, rapid detection as well as suitable for field applications such as loop-mediated isothermal amplification, helicase-dependent amplification, rolling circle amplification, recombinase polymerase amplification, and molecular inversion probe. The principle behind these technologies has been thoroughly discussed in several review papers; herein we emphasize the application of these technologies to detect plant pathogens by outlining the advantages and disadvantages of each technology in detail.

Advanced DNA-Based Point-of-Care Diagnostic Methods for Plant Diseases Detection

PubMed Central

Lau, Han Yih; Botella, Jose R.

2017-01-01

Diagnostic technologies for the detection of plant pathogens with point-of-care capability and high multiplexing ability are an essential tool in the fight to reduce the large agricultural production losses caused by plant diseases. The main desirable characteristics for such diagnostic assays are high specificity, sensitivity, reproducibility, quickness, cost efficiency and high-throughput multiplex detection capability. This article describes and discusses various DNA-based point-of care diagnostic methods for applications in plant disease detection. Polymerase chain reaction (PCR) is the most common DNA amplification technology used for detecting various plant and animal pathogens. However, subsequent to PCR based assays, several types of nucleic acid amplification technologies have been developed to achieve higher sensitivity, rapid detection as well as suitable for field applications such as loop-mediated isothermal amplification, helicase-dependent amplification, rolling circle amplification, recombinase polymerase amplification, and molecular inversion probe. The principle behind these technologies has been thoroughly discussed in several review papers; herein we emphasize the application of these technologies to detect plant pathogens by outlining the advantages and disadvantages of each technology in detail. PMID:29375588

Simple detection of residual enrofloxacin in meat products using microparticles and biochips.

PubMed

Ha, Mi-Sun; Chung, Myung-Sub; Bae, Dong-Ho

2016-05-01

A simple and sensitive method for detecting enrofloxacin, a major veterinary fluoroquinolone, was developed. Monoclonal antibody specific for enrofloxacin was immobilised on a chip and fluorescent dye-labelled microparticles were covalently bound to the enrofloxacin molecules. Enrofloxacin in solution competes with the microparticle-immobilised enrofloxacin (enroMPs) to bind to the antibody on the chip. The presence of enrofloxacin was verified by detecting the fluorescence of enrofloxacin-bound microparticles. Under optimum conditions, a high dynamic range was achieved at enrofloxacin concentrations ranging from 1 to 1000 μg kg(-1). The limits of detection and quantification for standard solutions were 5 and 20 μg kg(-1) respectively, which are markedly lower than the maximum residue limit. Using simple extraction methods, recoveries from fortified beef, pork and chicken samples were 43.4-62.3%. This novel method also enabled approximate quantification of enrofloxacin concentration: the enroMP signal intensity decreased with increasing enrofloxacin concentration. Because of its sensitivity, specificity, simplicity and rapidity, the method described herein will facilitate the detection and approximate quantification of enrofloxacin residues in foods in a high-throughput manner.

Improved Detection of Local Earthquakes in the Vienna Basin (Austria), using Subspace Detectors

NASA Astrophysics Data System (ADS)

Apoloner, Maria-Theresia; Caffagni, Enrico; Bokelmann, Götz

2016-04-01

The Vienna Basin in Eastern Austria is densely populated and highly-developed; it is also a region of low to moderate seismicity, yet the seismological network coverage is relatively sparse. This demands improving our capability of earthquake detection by testing new methods, enlarging the existing local earthquake catalogue. This contributes to imaging tectonic fault zones for better understanding seismic hazard, also through improved earthquake statistics (b-value, magnitude of completeness). Detection of low-magnitude earthquakes or events for which the highest amplitudes slightly exceed the signal-to-noise-ratio (SNR), may be possible by using standard methods like the short-term over long-term average (STA/LTA). However, due to sparse network coverage and high background noise, such a technique may not detect all potentially recoverable events. Yet, earthquakes originating from the same source region and relatively close to each other, should be characterized by similarity in seismic waveforms, at a given station. Therefore, waveform similarity can be exploited by using specific techniques such as correlation-template based (also known as matched filtering) or subspace detection methods (based on the subspace theory). Matching techniques basically require a reference or template event, usually characterized by high waveform coherence in the array receivers, and high SNR, which is cross-correlated with the continuous data. Instead, subspace detection methods overcome in principle the necessity of defining template events as single events, but use a subspace extracted from multiple events. This approach theoretically should be more robust in detecting signals that exhibit a strong variability (e.g. because of source or magnitude). In this study we scan the continuous data recorded in the Vienna Basin with a subspace detector to identify additional events. This will allow us to estimate the increase of the seismicity rate in the local earthquake catalogue, therefore providing an evaluation of network performance and efficiency of the method.

Determination of acrylamide and methacrylamide by normal phase high performance liquid chromatography and UV detection.

PubMed

Paleologos, E K; Kontominas, M G

2005-06-10

A method using normal phase high performance liquid chromatography (NP-HPLC) with UV detection was developed for the analysis of acrylamide and methacrylamide. The method relies on the chromatographic separation of these analytes on a polar HPLC column designed for the separation of organic acids. Identification of acrylamide and methacrylamide is approached dually, that is directly in their protonated forms and as their hydrolysis products acrylic and methacrylic acid respectively, for confirmation. Detection and quantification is performed at 200 nm. The method is simple allowing for clear resolution of the target peaks from any interfering substances. Detection limits of 10 microg L(-1) were obtained for both analytes with the inter- and intra-day RSD for standard analysis lying below 1.0%. Use of acetonitrile in the elution solvent lowers detection limits and retention times, without impairing resolution of peaks. The method was applied for the determination of acrylamide and methacrylamide in spiked food samples without native acrylamide yielding recoveries between 95 and 103%. Finally, commercial samples of french and roasted fries, cookies, cocoa and coffee were analyzed to assess applicability of the method towards acrylamide, giving results similar with those reported in the literature.

Convolutional neural network features based change detection in satellite images

NASA Astrophysics Data System (ADS)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.

PubMed

Song, Hongchao; Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k -nearest neighbor graphs- ( K -NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

PubMed Central

Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k-nearest neighbor graphs- (K-NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity. PMID:29270197

Microbial biofilm detection on food contact surfaces by macro-scale fluorescence imaging

USDA-ARS?s Scientific Manuscript database

Hyperspectral fluorescence imaging methods were utilized to evaluate the potential of multispectral fluorescence methods for detection of pathogenic biofilm formations on four types of food contact surface materials: stainless steel, high density polyethylene (HDPE) commonly used for cutting boards,...

A Method for Simultaneous Determination of 20 Fusarium Toxins in Cereals by High-Resolution Liquid Chromatography-Orbitrap Mass Spectrometry with a Pentafluorophenyl Column

PubMed Central

Tamura, Masayoshi; Mochizuki, Naoki; Nagatomi, Yasushi; Harayama, Koichi; Toriba, Akira; Hayakawa, Kazuichi

2015-01-01

A high-resolution liquid chromatography-Orbitrap mass spectrometry (LC-Orbitrap MS) method was developed for simultaneous determination of 20 Fusarium toxins (nivalenol, fusarenon-X, deoxynivalenol, 3-acetyl deoxynivalenol, 15-acetyl deoxynivalenol, HT-2 toxin, T-2 toxin, neosolaniol, diacetoxyscirpenol, fumonisin B1, fumonisin B2, fumonisin B3, fumonisin A1, fumonisin A2, fumonisin A3, zearalenone, α-zearalenol, β-zearalenol, α-zearalanol, and β-zearalanol) in cereals. The separation of 20 Fusarium toxins with good peak shapes was achieved using a pentafluorophenyl column, and Orbitrap MS was able to detect accurately from cereal matrix components within ±0.77 ppm. The samples were prepared using a QuEChERS kit for extraction and a multifunctional cartridge for purification. The linearity, repeatability, and recovery of the method were >0.9964, 0.8%–14.7%, and 71%–106%, respectively. Using this method, an analysis of 34 commercially available cereals detected the presence of deoxynivalenol, 15-acetyl deoxynivalenol, fumonisin B1, fumonisin B2, fumonisin B3, fumonisn A1, fumonisin A2, fumonisin A3, and zearalenone in corn samples with high concentration and frequency. Trichothecenes was detected from wheat samples with high frequency; in particular, the concentration of deoxynivalenol was high. Conversely, α-zearalenol, β-zearalenol, α-zearalanol, and β-zearalanol were not detected in any of the samples. PMID:26008230

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

NASA Astrophysics Data System (ADS)

Hatzenbuhler, Chelsea; Kelly, John R.; Martinson, John; Okum, Sara; Pilgrim, Erik

2017-04-01

High-throughput DNA metabarcoding has gained recognition as a potentially powerful tool for biomonitoring, including early detection of aquatic invasive species (AIS). DNA based techniques are advancing, but our understanding of the limits to detection for metabarcoding complex samples is inadequate. For detecting AIS at an early stage of invasion when the species is rare, accuracy at low detection limits is key. To evaluate the utility of metabarcoding in future fish community monitoring programs, we conducted several experiments to determine the sensitivity and accuracy of routine metabarcoding methods. Experimental mixes used larval fish tissue from multiple “common” species spiked with varying proportions of tissue from an additional “rare” species. Pyrosequencing of genetic marker, COI (cytochrome c oxidase subunit I) and subsequent sequence data analysis provided experimental evidence of low-level detection of the target “rare” species at biomass percentages as low as 0.02% of total sample biomass. Limits to detection varied interspecifically and were susceptible to amplification bias. Moreover, results showed some data processing methods can skew sequence-based biodiversity measurements from corresponding relative biomass abundances and increase false absences. We suggest caution in interpreting presence/absence and relative abundance in larval fish assemblages until metabarcoding methods are optimized for accuracy and precision.

Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Feng; Dong, Junyu; Li, Bo; Xu, Qizhi; Xie, Cui

2016-10-01

Change detection is of high practical value to hazard assessment, crop growth monitoring, and urban sprawl detection. A synthetic aperture radar (SAR) image is the ideal information source for performing change detection since it is independent of atmospheric and sunlight conditions. Existing SAR image change detection methods usually generate a difference image (DI) first and use clustering methods to classify the pixels of DI into changed class and unchanged class. Some useful information may get lost in the DI generation process. This paper proposed an SAR image change detection method based on neighborhood-based ratio (NR) and extreme learning machine (ELM). NR operator is utilized for obtaining some interested pixels that have high probability of being changed or unchanged. Then, image patches centered at these pixels are generated, and ELM is employed to train a model by using these patches. Finally, pixels in both original SAR images are classified by the pretrained ELM model. The preclassification result and the ELM classification result are combined to form the final change map. The experimental results obtained on three real SAR image datasets and one simulated dataset show that the proposed method is robust to speckle noise and is effective to detect change information among multitemporal SAR images.

[Comparative research into sensitivity and specificity of immune-enzyme analysis with chemiluminescence and colorimetric detection for detecting antigens and antibodies to avian influenza viruses and newcastle disease].

PubMed

Vitkova, O N; Kapustina, T P; Mikhailova, V V; Safonov, G A; Vlasova, N N; Belousova, R V

2015-01-01

The goal of this work was to demonstrate the results of the development of the enzyme-linked immunosorbent tests with chemiluminescence detection and colorimetric detection of specific viral antigens and antibodies for identifying the avian influenza and the Newcastle disease viruses: high sensitivity and specificity of the immuno- chemiluminescence assay, which are 10-50 times higher than those of the ELISA colorimetric method. The high effectiveness of the results and the automation of the process of laboratory testing (using a luminometer) allow these methods to be recommended for including in primary screening tests for these infectious diseases.

Evaluation of microplate immunocapture method for detection of Vibrio cholerae, Salmonella Typhi and Shigella flexneri from food.

PubMed

Fakruddin, Md; Hossain, Md Nur; Ahmed, Monzur Morshed

2017-08-29

Improved methods with better separation and concentration ability for detection of foodborne pathogens are in constant need. The aim of this study was to evaluate microplate immunocapture (IC) method for detection of Salmonella Typhi, Shigella flexneri and Vibrio cholerae from food samples to provide a better alternative to conventional culture based methods. The IC method was optimized for incubation time, bacterial concentration, and capture efficiency. 6 h incubation and log 6 CFU/ml cell concentration provided optimal results. The method was shown to be highly specific for the pathogens concerned. Capture efficiency (CE) was around 100% of the target pathogens, whereas CE was either zero or very low for non-target pathogens. The IC method also showed better pathogen detection ability at different concentrations of cells from artificially contaminated food samples in comparison with culture based methods. Performance parameter of the method was also comparable (Detection limit- 25 CFU/25 g; sensitivity 100%; specificity-96.8%; Accuracy-96.7%), even better than culture based methods (Detection limit- 125 CFU/25 g; sensitivity 95.9%; specificity-97%; Accuracy-96.2%). The IC method poses to be the potential to be used as a method of choice for detection of foodborne pathogens in routine laboratory practice after proper validation.

Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain

NASA Astrophysics Data System (ADS)

Zhou, Anran; Xie, Weixin; Pei, Jihong

2018-06-01

Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

Evaluation of 3M™ Molecular Detection Assay (MDA) Listeria for the Detection of Listeria species in Selected Foods and Environmental Surfaces: Collaborative Study, First Action 2014.06.

PubMed

Bird, Patrick; Flannery, Jonathan; Crowley, Erin; Agin, James; Goins, David; Monteroso, Lisa; Benesh, DeAnn

2015-01-01

The 3M™ Molecular Detection Assay (MDA) Listeria is used with the 3M Molecular Detection System for the detection of Listeria species in food, food-related, and environmental samples after enrichment. The assay utilizes loop-mediated isothermal amplification to rapidly amplify Listeria target DNA with high specificity and sensitivity, combined with bioluminescence to detect the amplification. The 3M MDA Listeria method was evaluated using an unpaired study design in a multilaboratory collaborative study and compared to the AOAC Official Method of AnalysisSM (OMA) 993.12 Listeria monocytogenes in Milk and Dairy Products reference method for the detection of Listeria species in full-fat (4% milk fat) cottage cheese (25 g test portions). A total of 15 laboratories located in the continental United States and Canada participated. Each matrix had three inoculation levels: an uninoculated control level (0 CFU/test portion), and two levels artificially contaminated with Listeria monocytogenes, a low inoculum level (0.2-2 CFU/test portion) and a high inoculum level (2-5 CFU/test portion) using nonheat-stressed cells. In total, 792 unpaired replicate portions were analyzed. Statistical analysis was conducted according to the probability of detection (POD) model. Results obtained for the low inoculum level test portions produced a difference in cross-laboratory POD value of -0.07 with a 95% confidence interval of (-0.19, 0.06). No statistically significant differences were observed in the number of positive samples detected by the 3M MDA Listeria method versus the AOAC OMA method.

Challenges for Detecting Valproic Acid in a Nontargeted Urine Drug Screening Method.

PubMed

Pope, Jeffrey D; Black, Marion J; Drummer, Olaf H; Schneider, Hans G

2017-08-01

Valproic acid (VPA) is a widely prescribed medicine, and acute toxicity is possible. As such, it should be included in any nontargeted urine drug screening method. In many published liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS) methods, VPA is usually measured using a pseudo-multiple reaction monitoring (MRM) transition. We investigate a simple ultra-high-performance liquid chromatography-quadrupole time-of-flight (QTof) approach to detect the presence of VPA with more confidence. Three commercially sourced VPA metabolites were characterized and added to a nontargeted high-resolution MS urine drug screening method. All analyses were performed on a Waters Xevo G2-XS LC-QTof in negative electrospray ionization mode. The mass detector was operated in MS mode, and data were processed with UNIFI software. Sixty-eight patient urine samples, which were previously identified by a well-established gas chromatography-MS method as containing VPA, were analyzed on the Waters Xevo G2-XS LC-QTof, to validate this approach. VPA metabolite standards were characterized, and their detection data were added to the broad drug screening library. VPA metabolites were readily detectable in the urine of patients taking VPA. The inclusion of characterized VPA metabolites provides a simple and reliable method enabling the detection of VPA in nontargeted urine drug screening.

Rapid detection of Ganoderma-infected oil palms by microwave ergosterol extraction with HPLC and TLC.

PubMed

Muniroh, M S; Sariah, M; Zainal Abidin, M A; Lima, N; Paterson, R R M

2014-05-01

Detection of basal stem rot (BSR) by Ganoderma of oil palms was based on foliar symptoms and production of basidiomata. Enzyme-Linked Immunosorbent Assays-Polyclonal Antibody (ELISA-PAB) and PCR have been proposed as early detection methods for the disease. These techniques are complex, time consuming and have accuracy limitations. An ergosterol method was developed which correlated well with the degree of infection in oil palms, including samples growing in plantations. However, the method was capable of being optimised. This current study was designed to develop a simpler, more rapid and efficient ergosterol method with utility in the field that involved the use of microwave extraction. The optimised procedure involved extracting a small amount of Ganoderma, or Ganoderma-infected oil palm suspended in low volumes of solvent followed by irradiation in a conventional microwave oven at 70°C and medium high power for 30s, resulting in simultaneous extraction and saponification. Ergosterol was detected by thin layer chromatography (TLC) and quantified using high performance liquid chromatography with diode array detection. The TLC method was novel and provided a simple, inexpensive method with utility in the field. The new method was particularly effective at extracting high yields of ergosterol from infected oil palm and enables rapid analysis of field samples on site, allowing infected oil palms to be treated or culled very rapidly. Some limitations of the method are discussed herein. The procedures lend themselves to controlling the disease more effectively and allowing more effective use of land currently employed to grow oil palms, thereby reducing pressure to develop new plantations. Copyright © 2014 Elsevier B.V. All rights reserved.

Species Specific Bacterial Spore Detection Using Lateral-Flow Immunoassay with DPA-Triggered Tb Luminescence

NASA Technical Reports Server (NTRS)

Ponce, Adrian

2003-01-01

A method of detecting bacterial spores incorporates (1) A method of lateral-flow immunoassay in combination with (2) A method based on the luminescence of Tb3+ ions to which molecules of dipicolinic acid (DPA) released from the spores have become bound. The present combination of lateral-flow immunoassay and DPA-triggered Tb luminescence was developed as a superior alternative to a prior lateral-flow immunoassay method in which detection involves the visual observation and/or measurement of red light scattered from colloidal gold nanoparticles. The advantage of the present combination method is that it affords both (1) High selectivity for spores of the species of bacteria that one seeks to detect (a characteristic of lateral-flow immunoassay in general) and (2) Detection sensitivity much greater (by virtue of the use of DPA-triggered Tb luminescence instead of gold nanoparticles) than that of the prior lateral-flow immunoassay method

Initial Results in Using a Self-Coherence Method for Detecting Sustained Oscillations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ning; Dagle, Jeffery E.

2015-01-01

This paper develops a self-coherence method for detecting sustained oscillations using phasor measurement unit (PMU) data. Sustained oscillations decrease system performance and introduce potential reliability issues. Timely detection of the oscillations at an early stage provides the opportunity for taking remedial reaction. Using high-speed time-synchronized PMU data, this paper details a self-coherence method for detecting sustained oscillation, even when the oscillation amplitude is lower than ambient noise. Simulation and field measurement data are used to evaluate the proposed method’s performance. It is shown that the proposed method can detect sustained oscillations and estimate oscillation frequencies with a low signal-to-noise ratio.more » Comparison with a power spectral density method also shows that the proposed self-coherence method performs better. Index Terms—coherence, power spectral density, phasor measurement unit (PMU), oscillations, power system dynamics« less

A new method for detection and discrimination of Pepino mosaic virus isolates using high resolution melting analysis of the triple gene block 3.

PubMed

Hasiów-Jaroszewska, Beata; Komorowska, Beata

2013-10-01

Diagnostic methods distinguished different Pepino mosaic virus (PepMV) genotypes but the methods do not detect sequence variation in particular gene segments. The necrotic and non-necrotic isolates (pathotypes) of PepMV share a 99% sequence similarity. These isolates differ from each other at one nucleotide site in the triple gene block 3. In this study, a combination of real-time reverse transcription polymerase chain reaction and high resolution melting curve analysis of triple gene block 3 was developed for simultaneous detection and differentiation of PepMV pathotypes. The triple gene block 3 region carrying a transition A → G was amplified using two primer pairs from twelve virus isolates, and was subjected to high resolution melting curve analysis. The results showed two distinct melting curve profiles related to each pathotype. The results also indicated that the high resolution melting method could readily differentiate between necrotic and non-necrotic PepMV pathotypes. Copyright © 2013 Elsevier B.V. All rights reserved.

Correlation matching method for high-precision position detection of optical vortex using Shack-Hartmann wavefront sensor.

PubMed

Huang, Chenxi; Huang, Hongxin; Toyoda, Haruyoshi; Inoue, Takashi; Liu, Huafeng

2012-11-19

We propose a new method for realizing high-spatial-resolution detection of singularity points in optical vortex beams. The method uses a Shack-Hartmann wavefront sensor (SHWS) to record a Hartmanngram. A map of evaluation values related to phase slope is then calculated from the Hartmanngram. The position of an optical vortex is determined by comparing the map with reference maps that are calculated from numerically created spiral phases having various positions. Optical experiments were carried out to verify the method. We displayed various spiral phase distribution patterns on a phase-only spatial light modulator and measured the resulting singularity point using the proposed method. The results showed good linearity in detecting the position of singularity points. The RMS error of the measured position of the singularity point was approximately 0.056, in units normalized to the lens size of the lenslet array used in the SHWS.

Evaluation of a new ultrasensitive assay for cardiac troponin I.

PubMed

Casals, Gregori; Filella, Xavier; Bedini, Josep Lluis

2007-12-01

We evaluated the analytical and clinical performance of a new ultrasensitive cardiac troponin I assay (cTnI) on the ADVIA Centaur system (TnI-Ultra). The evaluation included the determination of detection limit, within-assay and between-assay variation and comparison with two other non-ultrasensitive methods. Moreover, cTnI was determined in 120 patients with acute chest pain with three methods. To evaluate the ability of the new method to detect MI earlier, it was assayed in 8 MI patients who first tested negative then positive by the other methods. The detection limit was 0.009 microg/L and imprecision was <10% at all concentrations evaluated. In comparison with two other methods, 10% of the anginas diagnosed were recategorized to MI. The ADVIA Centaur TnI-Ultra assay presented high reproducibility and high sensitivity. The use of the recommended lower cutpoint (0.044 microg/L) implied an increased and earlier identification of MI.

High-speed shaking of frozen blood clots for extraction of human and malaria parasite DNA.

PubMed

Lundblom, Klara; Macharia, Alex; Lebbad, Marianne; Mohammed, Adan; Färnert, Anna

2011-08-08

Frozen blood clots remaining after serum collection is an often disregarded source of host and pathogen DNA due to troublesome handling and suboptimal outcome. High-speed shaking of clot samples in a cell disruptor manufactured for homogenization of tissue and faecal specimens was evaluated for processing frozen blood clots for DNA extraction. The method was compared to two commercial clot protocols based on a chemical kit and centrifugation through a plastic sieve, followed by the same DNA extraction protocol. Blood clots with different levels of parasitaemia (1-1,000 p/μl) were prepared from parasite cultures to assess sensitivity of PCR detection. In addition, clots retrieved from serum samples collected within two epidemiological studies in Kenya (n = 630) were processed by high speed shaking and analysed by PCR for detection of malaria parasites and the human α-thalassaemia gene. High speed shaking succeeded in fully dispersing the clots and the method generated the highest DNA yield. The level of PCR detection of P. falciparum parasites and the human thalassaemia gene was the same as samples optimally collected with an anticoagulant. The commercial clot protocol and centrifugation through a sieve failed to fully dissolve the clots and resulted in lower sensitivity of PCR detection. High speed shaking was a simple and efficacious method for homogenizing frozen blood clots before DNA purification and resulted in PCR templates of high quality both from humans and malaria parasites. This novel method enables genetic studies from stored blood clots.

Detection of β-Lactams and Chloramphenicol Residues in Raw Milk-Development and Application of an HPLC-DAD Method in Comparison with Microbial Inhibition Assays.

PubMed

Karageorgou, Eftychia; Christoforidou, Sofia; Ioannidou, Maria; Psomas, Evdoxios; Samouris, Georgios

2018-06-01

The present study was carried out to assess the detection sensitivity of four microbial inhibition assays (MIAs) in comparison with the results obtained by the High Performance Liquid Chromatography with Diode-Array Detection (HPLC-DAD) method for antibiotics of the β-lactam group and chloramphenicol in fortified raw milk samples. MIAs presented fairly good results when detecting β-lactams, whereas none were able to detect chloramphenicol at or above the permissible limits. HPLC analysis revealed high recoveries of examined compounds, whereas all detection limits observed were lower than their respective maximum residue limits (MRL) values. The extraction and clean-up procedure of antibiotics was performed by a modified matrix solid phase dispersion procedure using a mixture of Plexa by Agilent and QuEChERS as a sorbent. The HPLC method developed was validated, determining the accuracy, precision, linearity, decision limit, and detection capability. Both methods were used to monitor raw milk samples of several cows and sheep, obtained from producers in different regions of Greece, for the presence of examined antibiotic residues. Results obtained showed that MIAs could be used effectively and routinely to detect antibiotic residues in several milk types. However, in some cases, spoilage of milk samples revealed that the kits' sensitivity could be strongly affected, whereas this fact does not affect the effectiveness of HPLC-DAD analysis.

A tree canopy height delineation method based on Morphological Reconstruction—Open Crown Decomposition

NASA Astrophysics Data System (ADS)

Liu, Q.; Jing, L.; Li, Y.; Tang, Y.; Li, H.; Lin, Q.

2016-04-01

For the purpose of forest management, high resolution LIDAR and optical remote sensing imageries are used for treetop detection, tree crown delineation, and classification. The purpose of this study is to develop a self-adjusted dominant scales calculation method and a new crown horizontal cutting method of tree canopy height model (CHM) to detect and delineate tree crowns from LIDAR, under the hypothesis that a treetop is radiometric or altitudinal maximum and tree crowns consist of multi-scale branches. The major concept of the method is to develop an automatic selecting strategy of feature scale on CHM, and a multi-scale morphological reconstruction-open crown decomposition (MRCD) to get morphological multi-scale features of CHM by: cutting CHM from treetop to the ground; analysing and refining the dominant multiple scales with differential horizontal profiles to get treetops; segmenting LiDAR CHM using watershed a segmentation approach marked with MRCD treetops. This method has solved the problems of false detection of CHM side-surface extracted by the traditional morphological opening canopy segment (MOCS) method. The novel MRCD delineates more accurate and quantitative multi-scale features of CHM, and enables more accurate detection and segmentation of treetops and crown. Besides, the MRCD method can also be extended to high optical remote sensing tree crown extraction. In an experiment on aerial LiDAR CHM of a forest of multi-scale tree crowns, the proposed method yielded high-quality tree crown maps.

A photometric high-throughput method for identification of electrochemically active bacteria using a WO3 nanocluster probe.

PubMed

Yuan, Shi-Jie; He, Hui; Sheng, Guo-Ping; Chen, Jie-Jie; Tong, Zhong-Hua; Cheng, Yuan-Yuan; Li, Wen-Wei; Lin, Zhi-Qi; Zhang, Feng; Yu, Han-Qing

2013-01-01

Electrochemically active bacteria (EAB) are ubiquitous in environment and have important application in the fields of biogeochemistry, environment, microbiology and bioenergy. However, rapid and sensitive methods for EAB identification and evaluation of their extracellular electron transfer ability are still lacking. Herein we report a novel photometric method for visual detection of EAB by using an electrochromic material, WO(3) nanoclusters, as the probe. This method allowed a rapid identification of EAB within 5 min and a quantitative evaluation of their extracellular electron transfer abilities. In addition, it was also successfully applied for isolation of EAB from environmental samples. Attributed to its rapidness, high reliability, easy operation and low cost, this method has high potential for practical implementation of EAB detection and investigations.

Potential Landslide Early Detection Near Wenchuan by a Qualitatively Multi-Baseline Dinsar Method

NASA Astrophysics Data System (ADS)

Dai, K.; Chen, G.; Xu, Q.; Li, Z.; Qu, T.; Hu, L.; Lu, H.

2018-04-01

Early detection of landslides is important for disaster prevention, which was still very hard work with traditional surveying methods. Interferometric Synthetic Aperture Radar (InSAR) technology provided us the ability to monitor displacements along the slope with wide coverage and high accuracy. In this paper, we proposed a qualitatively multi-baseline DInSAR method to early detect and map the potential landslides. Two sections of China National Highway 317 and 213 were selected as study area. With this method 10 potential landslide areas were early detected and mapped in a quick and effective way. One of them (i.e. Shidaguan landslide) collapsed on August 2017, which was coincident with our results, suggesting that this method could become an effective way to acquire the landslide early detection map to assist the future disaster prevention work.

Detection of monohydroxylated polycyclic aromatic hydrocarbons in urine and particulate matter using LC separations coupled with integrated SPE and fluorescence detection or coupled with high-resolution time-of-flight mass spectrometry.

PubMed

Lintelmann, Jutta; Wu, Xiao; Kuhn, Evelyn; Ritter, Sebastian; Schmidt, Claudia; Zimmermann, Ralf

2018-05-01

A high-performance liquid chromatographic (HPLC) method with integrated solid-phase extraction for the determination of 1-hydroxypyrene and 1-, 2-, 3-, 4- and 9-hydroxyphenanthrene in urine was developed and validated. After enzymatic treatment and centrifugation of 500 μL urine, 100 μL of the sample was directly injected into the HPLC system. Integrated solid-phase extraction was performed on a selective, copper phthalocyanine modified packing material. Subsequent chromatographic separation was achieved on a pentafluorophenyl core-shell column using a methanol gradient. For quantification, time-programmed fluorescence detection was used. Matrix-dependent recoveries were between 94.8 and 102.4%, repeatability and reproducibility ranged from 2.2 to 17.9% and detection limits lay between 2.6 and 13.6 ng/L urine. A set of 16 samples from normally exposed adults was analyzed using this HPLC-fluorescence detection method. Results were comparable with those reported in other studies. The chromatographic separation of the method was transferred to an ultra-high-performance liquid chromatography pentafluorophenyl core-shell column and coupled to a high-resolution time-of-flight mass spectrometer (HR-TOF-MS). The resulting method was used to demonstrate the applicability of LC-HR-TOF-MS for simultaneous target and suspect screening of monohydroxylated polycyclic aromatic hydrocarbons in extracts of urine and particulate matter. Copyright © 2018 John Wiley & Sons, Ltd.

MPAI (mass probes aided ionization) method for total analysis of biomolecules by mass spectrometry.

PubMed

Honda, Aki; Hayashi, Shinichiro; Hifumi, Hiroki; Honma, Yuya; Tanji, Noriyuki; Iwasawa, Naoko; Suzuki, Yoshio; Suzuki, Koji

2007-01-01

We have designed and synthesized various mass probes, which enable us to effectively ionize various molecules to be detected with mass spectrometry. We call the ionization method using mass probes the "MPAI (mass probes aided ionization)" method. We aim at the sensitive detection of various biological molecules, and also the detection of bio-molecules by a single mass spectrometry serially without changing the mechanical settings. Here, we review mass probes for small molecules with various functional groups and mass probes for proteins. Further, we introduce newly developed mass probes for proteins for highly sensitive detection.

Rapid electrochemical detection of polyaniline-labeled Escherichia coli O157:H7.

PubMed

Setterington, Emma B; Alocilja, Evangelyn C

2011-01-15

There is a high demand for rapid, sensitive, and field-ready detection methods for Escherichia coli O157:H7, a highly infectious and potentially fatal food and water borne pathogen. In this study, E. coli O157:H7 cells are isolated via immunomagnetic separation (IMS) and labeled with biofunctionalized electroactive polyaniline (immuno-PANI). Labeled cell complexes are deposited onto a disposable screen-printed carbon electrode (SPCE) sensor and pulled to the electrode surface by an external magnetic field, to amplify the electrochemical signal generated by the polyaniline. Cyclic voltammetry is used to detect polyaniline and signal magnitude indicates the presence or absence of E. coli O157:H7. As few as 7CFU of E. coli O157:H7 (corresponding to an original concentration of 70 CFU/ml) were successfully detected on the SPCE sensor. The assay requires 70 min from sampling to detection, giving it a major advantage over standard culture methods in applications requiring high-throughput screening of samples and rapid results. The method can be performed with portable, handheld instrumentation and no biological modification of the sensor surface is required. Potential applications include field-based pathogen detection for food and water safety, environmental monitoring, healthcare, and biodefense. Copyright © 2010 Elsevier B.V. All rights reserved.

Multi-capillary based optical sensors for highly sensitive protein detection

NASA Astrophysics Data System (ADS)

Okuyama, Yasuhira; Katagiri, Takashi; Matsuura, Yuji

2017-04-01

A fluorescence measuring method based on glass multi-capillary for detecting trace amounts of proteins is proposed. It promises enhancement of sensitivity due to effects of the adsorption area expansion and the longitudinal excitation. The sensitivity behavior of this method was investigated by using biotin-streptavidin binding. According to experimental examinations, it was found that the sensitivity was improved by a factor of 70 from common glass wells. We also confirmed our measuring system could detect 1 pg/mL of streptavidin. These results suggest that multi-capillary has a potential as a high-sensitive biosensor.

Automated grain extraction and classification by combining improved region growing segmentation and shape descriptors in electromagnetic mill classification system

NASA Astrophysics Data System (ADS)

Budzan, Sebastian

2018-04-01

In this paper, the automatic method of grain detection and classification has been presented. As input, it uses a single digital image obtained from milling process of the copper ore with an high-quality digital camera. The grinding process is an extremely energy and cost consuming process, thus granularity evaluation process should be performed with high efficiency and time consumption. The method proposed in this paper is based on the three-stage image processing. First, using Seeded Region Growing (SRG) segmentation with proposed adaptive thresholding based on the calculation of Relative Standard Deviation (RSD) all grains are detected. In the next step results of the detection are improved using information about the shape of the detected grains using distance map. Finally, each grain in the sample is classified into one of the predefined granularity class. The quality of the proposed method has been obtained by using nominal granularity samples, also with a comparison to the other methods.

Field Demonstration of a Multiplexed Point-of-Care Diagnostic Platform for Plant Pathogens.

PubMed

Lau, Han Yih; Wang, Yuling; Wee, Eugene J H; Botella, Jose R; Trau, Matt

2016-08-16

Effective disease management strategies to prevent catastrophic crop losses require rapid, sensitive, and multiplexed detection methods for timely decision making. To address this need, a rapid, highly specific and sensitive point-of-care method for multiplex detection of plant pathogens was developed by taking advantage of surface-enhanced Raman scattering (SERS) labeled nanotags and recombinase polymerase amplification (RPA), which is a rapid isothermal amplification method with high specificity. In this study, three agriculturally important plant pathogens (Botrytis cinerea, Pseudomonas syringae, and Fusarium oxysporum) were used to demonstrate potential translation into the field. The RPA-SERS method was faster, more sensitive than polymerase chain reaction, and could detect as little as 2 copies of B. cinerea DNA. Furthermore, multiplex detection of the three pathogens was demonstrated for complex systems such as the Arabidopsis thaliana plant and commercial tomato crops. To demonstrate the potential for on-site field applications, a rapid single-tube RPA/SERS assay was further developed and successfully performed for a specific target outside of a laboratory setting.

Active Semi-Supervised Community Detection Based on Must-Link and Cannot-Link Constraints

PubMed Central

Cheng, Jianjun; Leng, Mingwei; Li, Longjie; Zhou, Hanhai; Chen, Xiaoyun

2014-01-01

Community structure detection is of great importance because it can help in discovering the relationship between the function and the topology structure of a network. Many community detection algorithms have been proposed, but how to incorporate the prior knowledge in the detection process remains a challenging problem. In this paper, we propose a semi-supervised community detection algorithm, which makes full utilization of the must-link and cannot-link constraints to guide the process of community detection and thereby extracts high-quality community structures from networks. To acquire the high-quality must-link and cannot-link constraints, we also propose a semi-supervised component generation algorithm based on active learning, which actively selects nodes with maximum utility for the proposed semi-supervised community detection algorithm step by step, and then generates the must-link and cannot-link constraints by accessing a noiseless oracle. Extensive experiments were carried out, and the experimental results show that the introduction of active learning into the problem of community detection makes a success. Our proposed method can extract high-quality community structures from networks, and significantly outperforms other comparison methods. PMID:25329660

A validated high-performance liquid chromatography method with diode array detection for simultaneous determination of nine flavonoids in Senecio cannabifolius Less.

PubMed

Niu, Tian-Zeng; Zhang, Yu-Wei; Bao, Yong-Li; Wu, Yin; Yu, Chun-Lei; Sun, Lu-Guo; Yi, Jing-Wen; Huang, Yan-Xin; Li, Yu-Xin

2013-03-25

A reversed phase high performance liquid chromatography method coupled with a diode array detector (HPLC-DAD) was developed for the first time for the simultaneous determination of 9 flavonoids in Senecio cannabifolius, a traditional Chinese medicinal herb. Agilent Zorbax SB-C18 column was used at room temperature and the mobile phase was a mixture of acetonitrile and 0.5% formic acid (v/v) in water in the gradient elution mode at a flow-rate of 1.0mlmin(-1), detected at 360nm. Validation of this method was performed to verify the linearity, precision, limits of detection and quantification, intra- and inter-day variabilities, reproducibility and recovery. The calibration curves showed good linearities (R(2)>0.9995) within the test ranges. The relative standard deviation (RSD) of the method was less than 3.0% for intra- and inter-day assays. The samples were stable for at least 96h, and the average recoveries were between 90.6% and 102.5%. High sensitivity was demonstrated with detection limits of 0.028-0.085μg/ml for flavonoids. The newly established HPLC method represents a powerful technique for the quality assurance of S. cannabifolius. Copyright © 2012 Elsevier B.V. All rights reserved.

Selective detection of cavitation bubbles by triplet pulse sequence in high-intensity focused ultrasound treatment

NASA Astrophysics Data System (ADS)

Iwasaki, Ryosuke; Nagaoka, Ryo; Yoshizawa, Shin; Umemura, Shin-ichiro

2018-07-01

Acoustic cavitation bubbles are known to enhance the heating effect in high-intensity focused ultrasound (HIFU) treatment. The detection of cavitation bubbles with high sensitivity and selectivity is required to predict the therapeutic and side effects of cavitation, and ensure the efficacy and safety of the treatment. A pulse inversion (PI) technique has been widely used for imaging microbubbles through enhancing the second-harmonic component of echo signals. However, it has difficulty in separating the nonlinear response of microbubbles from that due to nonlinear propagation. In this study, a triplet pulse (3P) method was investigated to specifically image cavitation bubbles by extracting the 1.5th fractional harmonic component. The proposed 3P method depicted cavitation bubbles with a contrast ratio significantly higher than those in conventional imaging methods with and without PI. The results suggest that the 3P method is effective for specifically detecting microbubbles in cavitation-enhanced HIFU treatment.

Change Detection of Remote Sensing Images by Dt-Cwt and Mrf

NASA Astrophysics Data System (ADS)

Ouyang, S.; Fan, K.; Wang, H.; Wang, Z.

2017-05-01

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

Comparative evaluation of methods for the detection of 2-alkylcyclobutanones as indicators for irradiation treatment of cashew nuts and nutmeg.

PubMed

Breidbach, Andreas; Ulberth, Franz

2016-06-15

Irradiation of food products and ingredients must be indicated by proper labeling. This study evaluated the appropriateness of the European Standard EN 1785:2003 for the detection of 2-alkylcyclobutanones, which are radiolysis products of fatty acids, in cashew nuts and nutmeg and confirmed its suitability to detect irradiation of cashew nut samples at average absorbed doses of 1 kGy and above. An alternative method was developed, which is based on matrix solid phase dispersion and subsequent separation and detection of oxime derivatives of 2-alkylcyclobutanones by high performance-high resolution mass spectrometry. It is more rapid, less resource consuming, and more sensitive than EN 1785:2003. This method allowed detection of 2-alkylcyclobutanones in cashew nuts irradiated at 100 Gray and in nutmeg irradiated at 400 Gray. None of the 26 cashew nut and 14 nutmeg samples purchased in different EU Member States contained traces of 2-alkylcyclobutanones. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Determination of some aldehydes by using solid-phase microextraction and high-performance liquid chromatography with UV detection.

PubMed

Kumar, Ashwini; Singh, Baldev; Malik, Ashok Kumar; Tiwary, Dhananjay K

2007-01-01

A new approach has been developed for the extraction and determination of aldehydes such as veratraldehyde, m-nitrobenzaldehyde, cinnamaldehyde, benzaldehyde, and p-chlorobenzaldehyde by using solid-phase microextraction (SPME) and high-performance liquid chromatography with UV detection (HPLC/UV). The method involves adsorption of the aldehydes on polydimethylsiloxane/divinylbenzene-coated fiber, followed by desorption in the desorption chamber of the SPME-HPLC interface, using acetonitrile-water (70 + 30) as the mobile phase; UV detection was at 254 nm. A good separation of 5 aldehydes was obtained on a C18 column. The detection limits of veratraldehyde, m-nitrobenzaldehyde, cinnamaldehyde, benzaldehyde, and p-chlorobenzaldehyde are 25, 41, 13, 12, and 11 pg/mL, respectively, which are about 100 times better than the detection limits for other SPME methods using gas chromatography. The proposed method was validated by determining benzaldehyde in bitter almonds and cinnamaldehyde in cinnamon bark. The recoveries of the 5 analytes were determined by analysis of spiked drinking water.

Detection of enteropathogenic Escherichia coli by microchip capillary electrophoresis.

PubMed

Law, Wai S; Li, Sam F Y; Kricka, Larry J

2009-01-01

There is always a need to detect the presence of microorganisms, either as contaminants in food and pharmaceutical industries or bioindicators for disease diagnosis. Hence, it is important to develop efficient, rapid, and simple methods to detect microorganisms. Traditional culturing method is unsatisfactory due to its long incubation time. Molecular methods, although capable of providing a high degree of specificity, are not always useful in providing quick tests of presence or absence of microorganisms. Microchip elec-trophoresis has been recently employed to address problems associated with the detection of microorganisms due to its high versatility, selectivity, sensitivity, and short analysis times. In this work, the potential of PDMS-based microchip electrophoresis in the identification and characterization of microorganism was evaluated. Enteropathogenic E. coli (EPEC) was selected as the model microorganism. To obtain repeat-able separations, sample pretreatment was found to be essential. Microchip electrophoresis with laser-induced fluorescence detection could potentially revolutionize certain aspects of microbiology involving diagnosis, profiling of pathogens, environmental analysis, and many others areas of study.

The PneuCarriage Project: A Multi-Centre Comparative Study to Identify the Best Serotyping Methods for Examining Pneumococcal Carriage in Vaccine Evaluation Studies

PubMed Central

Satzke, Catherine; Dunne, Eileen M.; Porter, Barbara D.; Klugman, Keith P.; Mulholland, E. Kim

2015-01-01

Background The pneumococcus is a diverse pathogen whose primary niche is the nasopharynx. Over 90 different serotypes exist, and nasopharyngeal carriage of multiple serotypes is common. Understanding pneumococcal carriage is essential for evaluating the impact of pneumococcal vaccines. Traditional serotyping methods are cumbersome and insufficient for detecting multiple serotype carriage, and there are few data comparing the new methods that have been developed over the past decade. We established the PneuCarriage project, a large, international multi-centre study dedicated to the identification of the best pneumococcal serotyping methods for carriage studies. Methods and Findings Reference sample sets were distributed to 15 research groups for blinded testing. Twenty pneumococcal serotyping methods were used to test 81 laboratory-prepared (spiked) samples. The five top-performing methods were used to test 260 nasopharyngeal (field) samples collected from children in six high-burden countries. Sensitivity and positive predictive value (PPV) were determined for the test methods and the reference method (traditional serotyping of >100 colonies from each sample). For the alternate serotyping methods, the overall sensitivity ranged from 1% to 99% (reference method 98%), and PPV from 8% to 100% (reference method 100%), when testing the spiked samples. Fifteen methods had ≥70% sensitivity to detect the dominant (major) serotype, whilst only eight methods had ≥70% sensitivity to detect minor serotypes. For the field samples, the overall sensitivity ranged from 74.2% to 95.8% (reference method 93.8%), and PPV from 82.2% to 96.4% (reference method 99.6%). The microarray had the highest sensitivity (95.8%) and high PPV (93.7%). The major limitation of this study is that not all of the available alternative serotyping methods were included. Conclusions Most methods were able to detect the dominant serotype in a sample, but many performed poorly in detecting the minor serotype populations. Microarray with a culture amplification step was the top-performing method. Results from this comprehensive evaluation will inform future vaccine evaluation and impact studies, particularly in low-income settings, where pneumococcal disease burden remains high. PMID:26575033

Coupling corona discharge for ambient extractive ionization mass spectrometry.

PubMed

Hu, Bin; Zhang, Xinglei; Li, Ming; Peng, Xuejiao; Han, Jing; Yang, Shuiping; Ouyang, Yongzhong; Chen, Huanwen

2011-12-07

Unlike the extractive electrospray ionization (EESI) technique described elsewhere, a corona discharge instead of electrospray ionization has been utilized to charge a neutral solvent spray under ambient conditions for the generation of highly charged microdroplets, which impact a neutral sample plume for the extractive ionization of the analytes in raw samples without any sample pretreatment. Using the positive ion mode, molecular radical cations were easily generated for the detection of non-polar compounds (e.g., benzene, cyclohexane, etc.), while protonated molecular ions of polar compounds (e.g., acetonitrile, acetic ether) were readily produced for the detection. By dispensing the matrix in a relatively large space, this method tolerates highly complex matrices. For a given sample such as lily fragrances, more compounds were detected by the method established here than the EESI technique. An acceptable relative standard deviation (RSD 8.9%, n = 11) was obtained for the direct measurement of explosives (10 ppb) in waste water samples. The experimental data demonstrate that this method could simultaneously detect both polar and non-polar analytes with high sensitivity, showing promising applications for the rapid detection of a wide variety of compounds present in complex matrices.

Nanotechnology: a promising method for oral cancer detection and diagnosis.

PubMed

Chen, Xiao-Jie; Zhang, Xue-Qiong; Liu, Qi; Zhang, Jing; Zhou, Gang

2018-06-11

Oral cancer is a common and aggressive cancer with high morbidity, mortality, and recurrence rate globally. Early detection is of utmost importance for cancer prevention and disease management. Currently, tissue biopsy remains the gold standard for oral cancer diagnosis, but it is invasive, which may cause patient discomfort. The application of traditional noninvasive methods-such as vital staining, exfoliative cytology, and molecular imaging-is limited by insufficient sensitivity and specificity. Thus, there is an urgent need for exploring noninvasive, highly sensitive, and specific diagnostic techniques. Nano detection systems are known as new emerging noninvasive strategies that bring the detection sensitivity of biomarkers to nano-scale. Moreover, compared to current imaging contrast agents, nanoparticles are more biocompatible, easier to synthesize, and able to target specific surface molecules. Nanoparticles generate localized surface plasmon resonances at near-infrared wavelengths, providing higher image contrast and resolution. Therefore, using nano-based techniques can help clinicians to detect and better monitor diseases during different phases of oral malignancy. Here, we review the progress of nanotechnology-based methods in oral cancer detection and diagnosis.

Development of a technique using MCNPX code for determination of nitrogen content of explosive materials using prompt gamma neutron activation analysis method

NASA Astrophysics Data System (ADS)

Nasrabadi, M. N.; Bakhshi, F.; Jalali, M.; Mohammadi, A.

2011-12-01

Nuclear-based explosive detection methods can detect explosives by identifying their elemental components, especially nitrogen. Thermal neutron capture reactions have been used for detecting prompt gamma 10.8 MeV following radioactive neutron capture by 14N nuclei. We aimed to study the feasibility of using field-portable prompt gamma neutron activation analysis (PGNAA) along with improved nuclear equipment to detect and identify explosives, illicit substances or landmines. A 252Cf radio-isotopic source was embedded in a cylinder made of high-density polyethylene (HDPE) and the cylinder was then placed in another cylindrical container filled with water. Measurements were performed on high nitrogen content compounds such as melamine (C3H6N6). Melamine powder in a HDPE bottle was placed underneath the vessel containing water and the neutron source. Gamma rays were detected using two NaI(Tl) crystals. The results were simulated with MCNP4c code calculations. The theoretical calculations and experimental measurements were in good agreement indicating that this method can be used for detection of explosives and illicit drugs.

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Enzyme-free detection and quantification of double-stranded nucleic acids.

PubMed

Feuillie, Cécile; Merheb, Maxime Mohamad; Gillet, Benjamin; Montagnac, Gilles; Hänni, Catherine; Daniel, Isabelle

2012-08-01

We have developed a fully enzyme-free SERRS hybridization assay for specific detection of double-stranded DNA sequences. Although all DNA detection methods ranging from PCR to high-throughput sequencing rely on enzymes, this method is unique for being totally non-enzymatic. The efficiency of enzymatic processes is affected by alterations, modifications, and/or quality of DNA. For instance, a limitation of most DNA polymerases is their inability to process DNA damaged by blocking lesions. As a result, enzymatic amplification and sequencing of degraded DNA often fail. In this study we succeeded in detecting and quantifying, within a mixture, relative amounts of closely related double-stranded DNA sequences from Rupicapra rupicapra (chamois) and Capra hircus (goat). The non-enzymatic SERRS assay presented here is the corner stone of a promising approach to overcome the failure of DNA polymerase when DNA is too degraded or when the concentration of polymerase inhibitors is too high. It is the first time double-stranded DNA has been detected with a truly non-enzymatic SERRS-based method. This non-enzymatic, inexpensive, rapid assay is therefore a breakthrough in nucleic acid detection.

Visual and light scattering spectrometric method for the detection of melamine using uracil 5‧-triphosphate sodium modified gold nanoparticles

NASA Astrophysics Data System (ADS)

Liang, Lijiao; Zhen, Shujun; Huang, Chengzhi

2017-02-01

A highly selective method was presented for colorimetric determination of melamine using uracil 5‧-triphosphate sodium modified gold nanoparticles (UTP-Au NPs) in this paper. Specific hydrogen-bonding interaction between uracil base (U) and melamine resulted in the aggregation of AuNPs, displaying variations of localized surface plasmon resonance (LSPR) features such as color change from red to blue and enhanced localized surface plasmon resonance light scattering (LSPR-LS) signals. Accordingly, the concentration of melamine could be quantified based on naked eye or a spectrometric method. This method was simple, inexpensive, environmental friendly and highly selective, which has been successfully used for the detection of melamine in pretreated liquid milk products with high recoveries.

Graphene oxide-coated stir bar sorptive extraction of trace aflatoxins from soy milk followed by high performance liquid chromatography-laser-induced fluorescence detection.

PubMed

Ma, Haiyan; Ran, Congcong; Li, Mengjiao; Gao, Jinglin; Wang, Xinyu; Zhang, Lina; Bian, Jing; Li, Junmei; Jiang, Ye

2018-04-01

Mycotoxins are potential food pollutants produced by fungi. Among them, aflatoxins (AFs) are the most toxic. Therefore, AFs were selected as models, and a sensitive, simple and green graphene oxide (GO)-based stir bar sorptive extraction (SBSE) method was developed for extraction and determination of AFs with high performance liquid chromatography-laser-induced fluorescence detector (HPLC-LIF). This method improved the sensitivity of AFs detection and solved the deposition difficulty of the direct use of GO as adsorbent. Several parameters including a spiked amount of NaCl, stirring rate, extraction time and desorption time were investigated. Under optimal conditions, the quantitative method had low limits of detection of 2.4-8.0 pg/mL, which were better than some reported AFs analytical methods. The developed method has been applied to soy milk samples with good recoveries ranging from 80.5 to 102.3%. The prepared GO-based SBSE can be used as a sensitive screening technique for detecting AFs in soy milk.

Highly specific and cost-efficient detection of Salmonella Paratyphi A combining aptamers with single-walled carbon nanotubes.

PubMed

Yang, Ming; Peng, Zhihui; Ning, Yi; Chen, Yongzhe; Zhou, Qin; Deng, Le

2013-05-22

In this paper, a panel of single-stranded DNA aptamers with high affinity and specificity against Salmonella Paratyphi A was selected from an enriched oligonucleotide pool by a whole-cell-Systematic Evolution of Ligands by Exponential Enrichment (SELEX) procedure, during which four other Salmonella serovars were used as counter-selection targets. It was determined through a fluorescence assay that the selected aptamers had high binding ability and specificity to this pathogen. The dissociation constant of these aptamers were up to nanomolar range, and aptamer Apt22 with the lowest Kd (47 ± 3 nM) was used in cell imaging experiments. To detect this bacteria with high specificity and cost-efficiently, a novel useful detection method was also constructed based on the noncovalent self-assembly of single-walled carbon nanotubes (SWNTs) and DNAzyme-labeled aptamer detection probes. The amounts of target bacteria could be quantified by exploiting chemoluminescence intensity changes at 420 nm and the detection limit of the method was 103 cfu/mL. This study demonstrated the applicability of Salmonella specific aptamers and their potential for use in the detection of Salmonella in food, clinical and environmental samples.

A Review of Transmission Diagnostics Research at NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Zakajsek, James J.

1994-01-01

This paper presents a summary of the transmission diagnostics research work conducted at NASA Lewis Research Center over the last four years. In 1990, the Transmission Health and Usage Monitoring Research Team at NASA Lewis conducted a survey to determine the critical needs of the diagnostics community. Survey results indicated that experimental verification of gear and bearing fault detection methods, improved fault detection in planetary systems, and damage magnitude assessment and prognostics research were all critical to a highly reliable health and usage monitoring system. In response to this, a variety of transmission fault detection methods were applied to experimentally obtained fatigue data. Failure modes of the fatigue data include a variety of gear pitting failures, tooth wear, tooth fracture, and bearing spalling failures. Overall results indicate that, of the gear fault detection techniques, no one method can successfully detect all possible failure modes. The more successful methods need to be integrated into a single more reliable detection technique. A recently developed method, NA4, in addition to being one of the more successful gear fault detection methods, was also found to exhibit damage magnitude estimation capabilities.

The PneuCarriage Project: A Multi-Centre Comparative Study to Identify the Best Serotyping Methods for Examining Pneumococcal Carriage in Vaccine Evaluation Studies.

PubMed

Satzke, Catherine; Dunne, Eileen M; Porter, Barbara D; Klugman, Keith P; Mulholland, E Kim

2015-11-01

The pneumococcus is a diverse pathogen whose primary niche is the nasopharynx. Over 90 different serotypes exist, and nasopharyngeal carriage of multiple serotypes is common. Understanding pneumococcal carriage is essential for evaluating the impact of pneumococcal vaccines. Traditional serotyping methods are cumbersome and insufficient for detecting multiple serotype carriage, and there are few data comparing the new methods that have been developed over the past decade. We established the PneuCarriage project, a large, international multi-centre study dedicated to the identification of the best pneumococcal serotyping methods for carriage studies. Reference sample sets were distributed to 15 research groups for blinded testing. Twenty pneumococcal serotyping methods were used to test 81 laboratory-prepared (spiked) samples. The five top-performing methods were used to test 260 nasopharyngeal (field) samples collected from children in six high-burden countries. Sensitivity and positive predictive value (PPV) were determined for the test methods and the reference method (traditional serotyping of >100 colonies from each sample). For the alternate serotyping methods, the overall sensitivity ranged from 1% to 99% (reference method 98%), and PPV from 8% to 100% (reference method 100%), when testing the spiked samples. Fifteen methods had ≥70% sensitivity to detect the dominant (major) serotype, whilst only eight methods had ≥70% sensitivity to detect minor serotypes. For the field samples, the overall sensitivity ranged from 74.2% to 95.8% (reference method 93.8%), and PPV from 82.2% to 96.4% (reference method 99.6%). The microarray had the highest sensitivity (95.8%) and high PPV (93.7%). The major limitation of this study is that not all of the available alternative serotyping methods were included. Most methods were able to detect the dominant serotype in a sample, but many performed poorly in detecting the minor serotype populations. Microarray with a culture amplification step was the top-performing method. Results from this comprehensive evaluation will inform future vaccine evaluation and impact studies, particularly in low-income settings, where pneumococcal disease burden remains high.

Determination of dapsone in serum and saliva using reversed-phase high-performance liquid chromatography with ultraviolet or electrochemical detection.

PubMed

Moncrieff, J

1994-03-18

A simple, extractionless method for the determination of dapsone in serum and saliva is described. Reversed-phase high-performance liquid chromatography is used with UV detection at 295 nm or electrochemical detection at 0.7 V. Diazoxide in buffer is the internal standard for UV detection and practolol for electrochemical detection. Sample preparation is minimal with protein precipitation of serum samples whilst saliva samples are simply diluted with addition of an internal standard. Low-level serum and saliva samples are front-cut on-line with a 3 cm laboratory-made precolumn in the loop position on a standard Valco injection valve. Isocratic separation is achieved on a 250 mm x 4.6 mm I.D. stainless-steel Spherisorb S5 ODS-1 column. The mobile phase for high levels of dapsone is acetonitrile-elution buffer (12:88, v/v) at 2 ml/min and a column temperature of 40 degrees C for both serum and saliva separations. For the low-level assays using electrochemical detection and solid-phase clean-up, the mobile phase is acetonitrile-methanol-elution buffer (9:4:87, v/v/v). The UV and electrochemical detection limits are 25 ng/ml and 200 pg/ml, respectively, in both serum and saliva. This simple method is applicable to the routine monitoring of dapsone levels in serum from leprotic patients and electrochemical detection gives a simple, reliable method for the monitoring of trough values in subjects on anti-malarial prophylaxis.

Visual and highly sensitive detection of cancer cells by a colorimetric aptasensor based on cell-triggered cyclic enzymatic signal amplification.

PubMed

Zhang, Xianxia; Xiao, Kunyi; Cheng, Liwei; Chen, Hui; Liu, Baohong; Zhang, Song; Kong, Jilie

2014-06-03

Rapid and efficient detection of cancer cells at their earliest stages is one of the central challenges in cancer diagnostics. We developed a simple, cost-effective, and highly sensitive colorimetric method for visually detecting rare cancer cells based on cell-triggered cyclic enzymatic signal amplification (CTCESA). In the absence of target cells, hairpin aptamer probes (HAPs) and linker DNAs stably coexist in solution, and the linker DNA assembles DNA-AuNPs, producing a purple solution. In the presence of target cells, the specific binding of HAPs to the target cells triggers a conformational switch that results in linker DNA hybridization and cleavage by nicking endonuclease-strand scission cycles. Consequently, the cleaved fragments of linker DNA can no longer assemble into DNA-AuNPs, resulting in a red color. UV-vis spectrometry and photograph analyses demonstrated that this CTCESA-based method exhibited selective and sensitive colorimetric responses to the presence of target CCRF-CEM cells, which could be detected by the naked eye. The linear response for CCRF-CEM cells in a concentration range from 10(2) to 10(4) cells was obtained with a detection limit of 40 cells, which is approximately 20 times lower than the detection limit of normal AuNP-based methods without amplification. Given the high specificity and sensitivity of CTCESA, this colorimetric method provides a sensitive, label-free, and cost-effective approach for early cancer diagnosis and point-to-care applications.

Develop guidelines for new vehicle detectors at high-speed signalized intersections : project summary.

DOT National Transportation Integrated Search

2017-01-01

The traditional vehicle detection method that has been used by the Texas Department of Transportation (TxDOT) on high-speed signalized intersection approaches for many years involved multiple detection points, with inductive loops being the early fav...

Detection of ricin contamination in ground beef by electrochemiluminescence immunosorbent assay.

PubMed

Brandon, David L

2011-04-01

Ricin is a highly toxic protein present in the seeds of Ricinus communis (castor), grown principally as a source of high quality industrial lubricant and as an ornamental. Because ricin has been used for intentional poisoning in the past and could be used to contaminate food, there is a need for analytical methodology to detect ricin in food matrices. A monoclonal antibody-based method was developed for detecting and quantifying ricin in ground beef, a complex, fatty matrix. The limit of detection was 0.5 ng/g for the electrochemiluminescence (ECL) method and 1.5 ng/g for enzyme-linked immunosorbent assay (ELISA). The detection of nanogram per gram quantities of ricin spiked into retail samples of ground beef provides approximately 10,000-fold greater sensitivity than required to detect a toxic dose of ricin (>1 mg) in a 100 g sample.

Detection of Ricin Contamination in Ground Beef by Electrochemiluminescence Immunosorbent Assay

PubMed Central

Brandon, David L.

2011-01-01

Ricin is a highly toxic protein present in the seeds of Ricinus communis (castor), grown principally as a source of high quality industrial lubricant and as an ornamental. Because ricin has been used for intentional poisoning in the past and could be used to contaminate food, there is a need for analytical methodology to detect ricin in food matrices. A monoclonal antibody-based method was developed for detecting and quantifying ricin in ground beef, a complex, fatty matrix. The limit of detection was 0.5 ng/g for the electrochemiluminescence (ECL) method and 1.5 ng/g for enzyme-linked immunosorbent assay (ELISA). The detection of nanogram per gram quantities of ricin spiked into retail samples of ground beef provides approximately 10,000-fold greater sensitivity than required to detect a toxic dose of ricin (>1 mg) in a 100 g sample. PMID:22069715

Affinity Biosensors for Detection of Mycotoxins in Food.

PubMed

Evtugyn, Gennady; Subjakova, Veronika; Melikishvili, Sopio; Hianik, Tibor

2018-01-01

This chapter reviews recent achievements in methods of detection of mycotoxins in food. Special focus is on the biosensor technology that utilizes antibodies and nucleic acid aptamers as receptors. Development of biosensors is based on the immobilization of antibodies or aptamers onto various conventional supports like gold layer, but also on nanomaterials such as graphene oxide, carbon nanotubes, and quantum dots that provide an effective platform for achieving high sensitivity of detection using various physical methods, including electrochemical, mass sensitive, and optical. The biosensors developed so far demonstrate high sensitivity typically in subnanomolar limit of detection. Several biosensors have been validated in real samples. The sensitivity of biosensors is similar and, in some cases, even better than traditional analytical methods such as ELISA or chromatography. We believe that future trends will be focused on improving biosensor properties toward practical application in food industry. © 2018 Elsevier Inc. All rights reserved.

Automated Solar Flare Detection and Feature Extraction in High-Resolution and Full-Disk Hα Images

NASA Astrophysics Data System (ADS)

Yang, Meng; Tian, Yu; Liu, Yangyi; Rao, Changhui

2018-05-01

In this article, an automated solar flare detection method applied to both full-disk and local high-resolution Hα images is proposed. An adaptive gray threshold and an area threshold are used to segment the flare region. Features of each detected flare event are extracted, e.g. the start, peak, and end time, the importance class, and the brightness class. Experimental results have verified that the proposed method can obtain more stable and accurate segmentation results than previous works on full-disk images from Big Bear Solar Observatory (BBSO) and Kanzelhöhe Observatory for Solar and Environmental Research (KSO), and satisfying segmentation results on high-resolution images from the Goode Solar Telescope (GST). Moreover, the extracted flare features correlate well with the data given by KSO. The method may be able to implement a more complicated statistical analysis of Hα solar flares.

Voltage Based Detection Method for High Impedance Fault in a Distribution System

NASA Astrophysics Data System (ADS)

Thomas, Mini Shaji; Bhaskar, Namrata; Prakash, Anupama

2016-09-01

High-impedance faults (HIFs) on distribution feeders cannot be detected by conventional protection schemes, as HIFs are characterized by their low fault current level and waveform distortion due to the nonlinearity of the ground return path. This paper proposes a method to identify the HIFs in distribution system and isolate the faulty section, to reduce downtime. This method is based on voltage measurements along the distribution feeder and utilizes the sequence components of the voltages. Three models of high impedance faults have been considered and source side and load side breaking of the conductor have been studied in this work to capture a wide range of scenarios. The effect of neutral grounding of the source side transformer is also accounted in this study. The results show that the algorithm detects the HIFs accurately and rapidly. Thus, the faulty section can be isolated and service can be restored to the rest of the consumers.

A high-throughput method for the detection of homoeologous gene deletions in hexaploid wheat

PubMed Central

2010-01-01

Background Mutational inactivation of plant genes is an essential tool in gene function studies. Plants with inactivated or deleted genes may also be exploited for crop improvement if such mutations/deletions produce a desirable agronomical and/or quality phenotype. However, the use of mutational gene inactivation/deletion has been impeded in polyploid plant species by genetic redundancy, as polyploids contain multiple copies of the same genes (homoeologous genes) encoded by each of the ancestral genomes. Similar to many other crop plants, bread wheat (Triticum aestivum L.) is polyploid; specifically allohexaploid possessing three progenitor genomes designated as 'A', 'B', and 'D'. Recently modified TILLING protocols have been developed specifically for mutation detection in wheat. Whilst extremely powerful in detecting single nucleotide changes and small deletions, these methods are not suitable for detecting whole gene deletions. Therefore, high-throughput methods for screening of candidate homoeologous gene deletions are needed for application to wheat populations generated by the use of certain mutagenic agents (e.g. heavy ion irradiation) that frequently generate whole-gene deletions. Results To facilitate the screening for specific homoeologous gene deletions in hexaploid wheat, we have developed a TaqMan qPCR-based method that allows high-throughput detection of deletions in homoeologous copies of any gene of interest, provided that sufficient polymorphism (as little as a single nucleotide difference) amongst homoeologues exists for specific probe design. We used this method to identify deletions of individual TaPFT1 homoeologues, a wheat orthologue of the disease susceptibility and flowering regulatory gene PFT1 in Arabidopsis. This method was applied to wheat nullisomic-tetrasomic lines as well as other chromosomal deletion lines to locate the TaPFT1 gene to the long arm of chromosome 5. By screening of individual DNA samples from 4500 M2 mutant wheat lines generated by heavy ion irradiation, we detected multiple mutants with deletions of each TaPFT1 homoeologue, and confirmed these deletions using a CAPS method. We have subsequently designed, optimized, and applied this method for the screening of homoeologous deletions of three additional wheat genes putatively involved in plant disease resistance. Conclusions We have developed a method for automated, high-throughput screening to identify deletions of individual homoeologues of a wheat gene. This method is also potentially applicable to other polyploidy plants. PMID:21114819

Detection of alpha-fetoprotein in magnetic immunoassay of thin channels using biofunctional nanoparticles

NASA Astrophysics Data System (ADS)

Tsai, H. Y.; Gao, B. Z.; Yang, S. F.; Li, C. S.; Fuh, C. Bor

2014-01-01

This paper presents the use of fluorescent biofunctional nanoparticles (10-30 nm) to detect alpha-fetoprotein (AFP) in a thin-channel magnetic immunoassay. We used an AFP model biomarker and s-shaped deposition zones to test the proposed detection method. The results show that the detection using fluorescent biofunctional nanoparticle has a higher throughput than that of functional microparticle used in previous experiments on affinity reactions. The proposed method takes about 3 min (versus 150 min of previous method) to detect 100 samples. The proposed method is useful for screening biomarkers in clinical applications, and can reduce the run time for sandwich immunoassays to less than 20 min. The detection limits (0.06 pg/ml) and linear ranges (0.068 pg/ml-0.68 ng/ml) of AFP using fluorescent biofunctional nanoparticles are the same as those of using functional microparticles within experimental errors. This detection limit is substantially lower and the linear range is considerably wider than those of enzyme-linked immunosorbent assay (ELISA) and other methods in sandwich immunoassay methods. The differences between this method and an ELISA in AFP measurements of serum samples were less than 12 %. The proposed method provides simple, fast, and sensitive detection with a high throughput for biomarkers.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-05-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Infrared small target detection technology based on OpenCV

NASA Astrophysics Data System (ADS)

Liu, Lei; Huang, Zhijian

2013-09-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

[Rapid detection of four antipertensive chemicals adulterated in traditional Chinese medicine for hypertension using TLC-SERS].

PubMed

Zhu, Qing-Xia; Cao, Yong-Bing; Cao, Ying-Ying; Lu, Feng

2014-04-01

A novel facile method for on-site detection of antipertensive chemicals (e. g. nicardipine hydrochloride, doxazosin mesylate, propranolol hydrochloride, and hydrochlorothiazide) adulterated in traditional Chinese medicine for hypertension using thin layer chromatography (TLC) combined with surface enhanced Raman spectroscopy (SERS) was reported in the present paper. Analytes and pharmaceutical matrices was separated by TLC, then SERS method was used to complete qualitative identification of trace substances on TLC plate. By optimizing colloidal silver concentration and developing solvent, as well as exploring the optimal limits of detection (LOD), the initially established TLC-SERS method was used to detect real hypertension Chinese pharmaceuticals. The results showed that this method had good specificity for the four chemicals and high sensitivity with a limit of detection as lower as to 0.005 microg. Finally, two of the ten antipertensive drugs were detected to be adulterated with chemicals. This simple and fast method can realize rapid detection of chemicals illegally for doping in antipertensive Chinese pharmaceuticals, and would have good prospects in on-site detection of chemicals for doping in Chinese pharmaceuticals.

Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil

PubMed Central

Chen, Bin; Wang, Yanan; Yan, Zhaoli

2018-01-01

Large-volume cubic high-pressure apparatus is commonly used to produce synthetic diamond. Due to the high pressure, high temperature and alternative stresses in practical production, cracks often occur in the carbide anvil, thereby resulting in significant economic losses or even casualties. Conventional methods are unsuitable for crack detection of the carbide anvil. This paper is concerned with acoustic emission-based crack detection of carbide anvils, regarded as a pattern recognition problem; this is achieved using a microphone, with methods including sound pulse detection, feature extraction, feature optimization and classifier design. Through analyzing the characteristics of background noise, the cracked sound pulses are separated accurately from the originally continuous signal. Subsequently, three different kinds of features including a zero-crossing rate, sound pressure levels, and linear prediction cepstrum coefficients are presented for characterizing the cracked sound pulses. The original high-dimensional features are adaptively optimized using principal component analysis. A hybrid framework of a support vector machine with k nearest neighbors is designed to recognize the cracked sound pulses. Finally, experiments are conducted in a practical diamond workshop to validate the feasibility and efficiency of the proposed method. PMID:29382144

Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil.

PubMed

Chen, Bin; Wang, Yanan; Yan, Zhaoli

2018-01-29

Large-volume cubic high-pressure apparatus is commonly used to produce synthetic diamond. Due to the high pressure, high temperature and alternative stresses in practical production, cracks often occur in the carbide anvil, thereby resulting in significant economic losses or even casualties. Conventional methods are unsuitable for crack detection of the carbide anvil. This paper is concerned with acoustic emission-based crack detection of carbide anvils, regarded as a pattern recognition problem; this is achieved using a microphone, with methods including sound pulse detection, feature extraction, feature optimization and classifier design. Through analyzing the characteristics of background noise, the cracked sound pulses are separated accurately from the originally continuous signal. Subsequently, three different kinds of features including a zero-crossing rate, sound pressure levels, and linear prediction cepstrum coefficients are presented for characterizing the cracked sound pulses. The original high-dimensional features are adaptively optimized using principal component analysis. A hybrid framework of a support vector machine with k nearest neighbors is designed to recognize the cracked sound pulses. Finally, experiments are conducted in a practical diamond workshop to validate the feasibility and efficiency of the proposed method.

Disposable amperometric biosensor based on nanostructured bacteriophages for glucose detection

NASA Astrophysics Data System (ADS)

Kang, Yu Ri; Hwang, Kyung Hoon; Kim, Ju Hwan; Nam, Chang Hoon; Kim, Soo Won

2010-10-01

The selection of electrode material profoundly influences biosensor science and engineering, as it heavily influences biosensor sensitivity. Here we propose a novel electrochemical detection method using a working electrode consisting of bio-nanowires from genetically modified filamentous phages and nanoparticles. fd-tet p8MMM filamentous phages displaying a three-methionine (MMM) peptide on the major coat protein pVIII (designated p8MMM phages) were immobilized on the active area of an electrochemical sensor through physical adsorption and chemical bonding. Bio-nanowires composed of p8MMM phages and silver nanoparticles facilitated sensitive, rapid and selective detection of particular molecules. We explored whether the composite electrode with bio-nanowires was an effective platform to detect the glucose oxidase. The current response of the bio-nanowire sensor was high at various glucose concentrations (0.1 µm-0.1 mM). This method provides a considerable advantage to demonstrate analyte detection over low concentration ranges. Especially, phage-enabled bio-nanowires can serve as receptors with high affinity and specificity for the detection of particular biomolecules and provide a convenient platform for designing site-directed multifunctional scaffolds based on bacteriophages and may serve as a simple method for label-free detection.

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

A Highly Selective and Strong Anti-Interference Host-Guest Complex as Fluorescent Probe for Detection of Amantadine by Indicator Displacement Assay.

PubMed

Zhu, Linzhao; Zhao, Zhiyong; Zhang, Xiongzhi; Zhang, Haijun; Liang, Feng; Liu, Simin

2018-04-18

Amantadine (AMA) and its derivatives are illicit veterinary drugs that are hard to detect at very low concentrations. Developing a fast, simple and highly sensitive method for the detection of AMA is highly in demand. Here, we designed an anthracyclic compound (ABAM) that binds to a cucurbit[7]uril (CB[7]) host with a high association constant of up to 8.7 × 10⁸ M −1 . The host-guest complex was then used as a fluorescent probe for the detection of AMA. Competition by AMA for occupying the cavity of CB[7] allows ABAM to release from the CB[7]-ABAM complex, causing significant fluorescence quenching of ABAM (indicator displacement assay, IDA). The linear range of the method is from 0.000188 to 0.375 μg/mL, and the detection limit can be as low as 6.5 × 10 −5 μg/mL (0.35 nM). Most importantly, due to the high binding affinity between CB[7] and ABAM, this fluorescence host-guest system shows great anti-interference capacity. Thus, we are able to accurately determine the concentration of AMA in various samples, including pharmaceutical formulations.

Multimodal imaging system for dental caries detection

NASA Astrophysics Data System (ADS)

Liang, Rongguang; Wong, Victor; Marcus, Michael; Burns, Peter; McLaughlin, Paul

2007-02-01

Dental caries is a disease in which minerals of the tooth are dissolved by surrounding bacterial plaques. A caries process present for some time may result in a caries lesion. However, if it is detected early enough, the dentist and dental professionals can implement measures to reverse and control caries. Several optical, nonionized methods have been investigated and used to detect dental caries in early stages. However, there is not a method that can singly detect the caries process with both high sensitivity and high specificity. In this paper, we present a multimodal imaging system that combines visible reflectance, fluorescence, and Optical Coherence Tomography (OCT) imaging. This imaging system is designed to obtain one or more two-dimensional images of the tooth (reflectance and fluorescence images) and a three-dimensional OCT image providing depth and size information of the caries. The combination of two- and three-dimensional images of the tooth has the potential for highly sensitive and specific detection of dental caries.

[High resolution melting analysis for detecting of JAK2V617F mutation in patients with myeloproliferative neoplasms].

PubMed

Chen, Hai-Hua; Yang, Ji-Long; Lu, Hui-Fang; Zhou, Wei-Jun; Yao, Fei; Deng, Lan

2014-02-01

This study was purposed to investigate the feasibility of high resolution melting (HRM) in the detection of JAK2V617F mutation in patients with myeloproliferative neoplasm (MPN). The 29 marrow samples randomly selected from patients with clinically diagnosed MPN from January 2008 to January 2011 were detected by HRM method. The results of HRM analysis were compared with that detected by allele specific polymerase chain reaction (AS-PCR) and DNA direct sequencing. The results showed that the JAK2V617F mutations were detected in 11 (37.9%, 11/29) cases by HRM, and its comparability with the direct sequencing result was 100%. While the consistency of AS-PCR with the direct sequencing was moderate (Kappa = 0.179, P = 0.316). It is concluded that the HRM analysis may be an optimal method for clinical screening of JAK2V617F mutation due to its simplicity and promptness with a high specificity.

Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors.

PubMed

Kim, Jong Hyun; Hong, Hyung Gil; Park, Kang Ryoung

2017-05-08

Because intelligent surveillance systems have recently undergone rapid growth, research on accurately detecting humans in videos captured at a long distance is growing in importance. The existing research using visible light cameras has mainly focused on methods of human detection for daytime hours when there is outside light, but human detection during nighttime hours when there is no outside light is difficult. Thus, methods that employ additional near-infrared (NIR) illuminators and NIR cameras or thermal cameras have been used. However, in the case of NIR illuminators, there are limitations in terms of the illumination angle and distance. There are also difficulties because the illuminator power must be adaptively adjusted depending on whether the object is close or far away. In the case of thermal cameras, their cost is still high, which makes it difficult to install and use them in a variety of places. Because of this, research has been conducted on nighttime human detection using visible light cameras, but this has focused on objects at a short distance in an indoor environment or the use of video-based methods to capture multiple images and process them, which causes problems related to the increase in the processing time. To resolve these problems, this paper presents a method that uses a single image captured at night on a visible light camera to detect humans in a variety of environments based on a convolutional neural network. Experimental results using a self-constructed Dongguk night-time human detection database (DNHD-DB1) and two open databases (Korea advanced institute of science and technology (KAIST) and computer vision center (CVC) databases), as well as high-accuracy human detection in a variety of environments, show that the method has excellent performance compared to existing methods.

A new method of inshore ship detection in high-resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Hu, Qifeng; Du, Yaling; Jiang, Yunqiu; Ming, Delie

2015-10-01

Ship as an important military target and water transportation, of which the detection has great significance. In the military field, the automatic detection of ships can be used to monitor ship dynamic in the harbor and maritime of enemy, and then analyze the enemy naval power. In civilian field, the automatic detection of ships can be used in monitoring transportation of harbor and illegal behaviors such as illegal fishing, smuggling and pirates, etc. In recent years, research of ship detection is mainly concentrated in three categories: forward-looking infrared images, downward-looking SAR image, and optical remote sensing images with sea background. Little research has been done into ship detection of optical remote sensing images with harbor background, as the gray-scale and texture features of ships are similar to the coast in high-resolution optical remote sensing images. In this paper, we put forward an effective harbor ship target detection method. First of all, in order to overcome the shortage of the traditional difference method in obtaining histogram valley as the segmentation threshold, we propose an iterative histogram valley segmentation method which separates the harbor and ships from the water quite well. Secondly, as landing ships in optical remote sensing images usually lead to discontinuous harbor edges, we use Hough Transform method to extract harbor edges. First, lines are detected by Hough Transform. Then, lines that have similar slope are connected into a new line, thus we access continuous harbor edges. Secondary segmentation on the result of the land-and-sea separation, we eventually get the ships. At last, we calculate the aspect ratio of the ROIs, thereby remove those targets which are not ship. The experiment results show that our method has good robustness and can tolerate a certain degree of noise and occlusion.

A cloud shadow detection method combined with cloud height iteration and spectral analysis for Landsat 8 OLI data

NASA Astrophysics Data System (ADS)

Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying

2018-04-01

Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct accuracy exceeding 80%, approximately 5% of the areas were wrongly identified, and approximately 10% of the cloud shadow areas were missing. The accuracy of this method is obviously higher than the recognition accuracy of Fmask, which has correct accuracy lower than 60%, and the missing recognition is approximately 40%.

Aptamer-Functionalized Fluorescent Silica Nanoparticles for Highly Sensitive Detection of Leukemia Cells

NASA Astrophysics Data System (ADS)

Tan, Juntao; Yang, Nuo; Hu, Zixi; Su, Jing; Zhong, Jianhong; Yang, Yang; Yu, Yating; Zhu, Jianmeng; Xue, Dabin; Huang, Yingying; Lai, Zongqiang; Huang, Yong; Lu, Xiaoling; Zhao, Yongxiang

2016-06-01

A simple, highly sensitive method to detect leukemia cells has been developed based on aptamer-modified fluorescent silica nanoparticles (FSNPs). In this strategy, the amine-labeled Sgc8 aptamer was conjugated to carboxyl-modified FSNPs via amide coupling between amino and carboxyl groups. Sensitivity and specificity of Sgc8-FSNPs were assessed using flow cytometry and fluorescence microscopy. These results showed that Sgc8-FSNPs detected leukemia cells with high sensitivity and specificity. Aptamer-modified FSNPs hold promise for sensitive and specific detection of leukemia cells. Changing the aptamer may allow the FSNPs to detect other types of cancer cells.

Gastric cancer screening of a high-risk population in Japan using serum pepsinogen and barium digital radiography.

PubMed

Ohata, Hiroshi; Oka, Masashi; Yanaoka, Kimihiko; Shimizu, Yasuhito; Mukoubayashi, Chizu; Mugitani, Kouichi; Iwane, Masataka; Nakamura, Hideya; Tamai, Hideyuki; Arii, Kenji; Nakata, Hiroya; Yoshimura, Noriko; Takeshita, Tetsuya; Miki, Kazumasa; Mohara, Osamu; Ichinose, Masao

2005-10-01

With the aim of developing more efficient gastric cancer screening programs for use in Japan, we studied a new screening program that combines serum pepsinogen (PG) testing and barium digital radiography (DR). A total of 17 647 middle-aged male subjects underwent workplace screening over a 7-year period using a combination of PG testing and DR. This program's effectiveness, as well as other characteristics of the program, was analyzed. Forty-nine cases of gastric cancer were detected (comprising 88% early cancer cases). The detection rate was 0.28%, and the positive predictive value was 0.85%. The PG test detected 63.3% of cases, DR detected 69.4% of cases, and both tests were positive in 32.7% of cancer cases. The two methods were almost equally effective, and were considerably more effective than conventional screening using photofluorography. Each screening method detected a distinct gastric cancer subgroup; the PG test efficiently detected asymptomatic small early cancer with intestinal type histology, while DR was efficient at detecting cancers with depressed or ulcerated morphology and diffuse type histology. The cost for the detection of a single cancer was much less than that for conventional screening. In fact, it is possible to further reduce the cost of detecting a single cancer to a cost comparable to that of surgically resecting a single gastric cancer. Thus, it is probable that a highly efficient gastric cancer screening system can be implemented by combining the two screening methods. Such a screening program would be beneficial in a population at high risk for gastric cancer.

Microelectrode array recordings of cardiac action potentials as a high throughput method to evaluate pesticide toxicity.

PubMed

Natarajan, A; Molnar, P; Sieverdes, K; Jamshidi, A; Hickman, J J

2006-04-01

The threat of environmental pollution, biological warfare agent dissemination and new diseases in recent decades has increased research into cell-based biosensors. The creation of this class of sensors could specifically aid the detection of toxic chemicals and their effects in the environment, such as pyrethroid pesticides. Pyrethroids are synthetic pesticides that have been used increasingly over the last decade to replace other pesticides like DDT. In this study we used a high-throughput method to detect pyrethroids by using multielectrode extracellular recordings from cardiac cells. The data from this cell-electrode hybrid system was compared to published results obtained with patch-clamp electrophysiology and also used as an alternative method to further understand pyrethroid effects. Our biosensor consisted of a confluent monolayer of cardiac myocytes cultured on microelectrode arrays (MEA) composed of 60 substrate-integrated electrodes. Spontaneous activity of these beating cells produced extracellular field potentials in the range of 100 microV to nearly 1200 microV with a beating frequency of 0.5-4 Hz. All of the tested pyrethroids; alpha-Cypermethrin, Tetramethrin and Tefluthrin, produced similar changes in the electrophysiological properties of the cardiac myocytes, namely reduced beating frequency and amplitude. The sensitivity of our toxin detection method was comparable to earlier patch-clamp studies, which indicates that, in specific applications, high-throughput extracellular methods can replace single-cell studies. Moreover, the similar effect of all three pyrethroids on the measured parameters suggests, that not only detection of the toxins but, their classification might also be possible with this method. Overall our results support the idea that whole cell biosensors might be viable alternatives when compared to current toxin detection methods.

Occurrence of Organic Wastewater Contaminants, Pharmaceuticals, and Personal Care Products in Selected Water Supplies, Cape Cod, Massachusetts, June 2004

DTIC Science & Technology

2005-01-01

previously detected high nitrate concen- trations. (Phenol and d- limonene , detected in equipment blanks at unacceptably high concentrations, are not...both tables, were not counted twice. (Phenol and d- limonene , detected in equipment blanks at unaccept- ably high concentrations, are not included in...The surrogate recoveries (not included in table 2) for the PPCP method were 101 and 102 percent. Three compounds, d- limonene , phenol, and

Advances in ultra-high performance liquid chromatography coupled to tandem mass spectrometry for sensitive detection of several food allergens in complex and processed foodstuffs.

PubMed

Planque, M; Arnould, T; Dieu, M; Delahaut, P; Renard, P; Gillard, N

2016-09-16

Sensitive detection of food allergens is affected by food processing and foodstuff complexity. It is therefore a challenge to detect cross-contamination in food production that could endanger an allergic customer's life. Here we used ultra-high performance liquid chromatography coupled to tandem mass spectrometry for simultaneous detection of traces of milk (casein, whey protein), egg (yolk, white), soybean, and peanut allergens in different complex and/or heat-processed foodstuffs. The method is based on a single protocol (extraction, trypsin digestion, and purification) applicable to the different tested foodstuffs: chocolate, ice cream, tomato sauce, and processed cookies. The determined limits of quantitation, expressed in total milk, egg, peanut, or soy proteins (and not soluble proteins) per kilogram of food, are: 0.5mg/kg for milk (detection of caseins), 5mg/kg for milk (detection of whey), 2.5mg/kg for peanut, 5mg/kg for soy, 3.4mg/kg for egg (detection of egg white), and 30.8mg/kg for egg (detection of egg yolk). The main advantage is the ability of the method to detect four major food allergens simultaneously in processed and complex matrices with very high sensitivity and specificity. Copyright © 2016 Elsevier B.V. All rights reserved.

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT.

PubMed

Lopez-Martin, Manuel; Carro, Belen; Sanchez-Esguevillas, Antonio; Lloret, Jaime

2017-08-26

The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host's network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery.

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT

PubMed Central

Carro, Belen; Sanchez-Esguevillas, Antonio

2017-01-01

The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery. PMID:28846608

Quantitation of acrylamide in foods by high-resolution mass spectrometry.

PubMed

Troise, Antonio Dario; Fiore, Alberto; Fogliano, Vincenzo

2014-01-08

Acrylamide detection still represents one of the hottest topics in food chemistry. Solid phase cleanup coupled to liquid chromatography separation and tandem mass spectrometry detection along with GC-MS detection are nowadays the gold standard procedure for acrylamide quantitation thanks to high reproducibility, good recovery, and low relative standard deviation. High-resolution mass spectrometry (HRMS) is particularly suitable for the detection of low molecular weight amides, and it can provide some analytical advantages over other MS techniques. In this paper a liquid chromatography (LC) method for acrylamide determination using HRMS detection was developed and compared to LC coupled to tandem mass spectrometry. The procedure applied a simplified extraction, no cleanup steps, and a 4 min chromatography. It proved to be solid and robust with an acrylamide mass accuracy of 0.7 ppm, a limit of detection of 2.65 ppb, and a limit of quantitation of 5 ppb. The method was tested on four acrylamide-containing foods: cookies, French fries, ground coffee, and brewed coffee. Results were perfectly in line with those obtained by LC-MS/MS.

Application of the desulfurization of phenothiazines for a sensitive detection method by high-performance liquid chromatography.

PubMed

Shimada, K; Mino, T; Nakajima, M; Wakabayashi, H; Yamato, S

1994-11-04

A simple and sensitive high-performance liquid chromatographic (HPLC) method for the determination of phenothiazine (PHE) is described. PHE is converted to diphenylamine (DIP) by desulfurization with Raney nickel catalyst. DIP is highly sensitive to electrochemical detection. The calibration graph for PHE quantification after desulfurization was linear between 0.1 and 2.0 ng per injection. The detection limit (signal-to-noise ratio = 3) of PHE after desulfurization was 10 pg, which is twenty times higher than that of the parent compound PHE. The proposed desulfurization technique was applied to other PHE-related compounds. The structural confirmation of the desulfurized product of PHE was carried out by LC-MS using atmospheric pressure chemical ionization.

Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.

PubMed

Galletto Pregliasco, A; Collin, A; Guéguen, A; Metten, M A; Aboab, J; Deschamps, R; Gout, O; Duron, L; Sadik, J C; Savatovsky, J; Lecler, A

2018-06-07

MR imaging is the key examination in the follow-up of patients with MS, by identification of new high-signal T2 brain lesions. However, identifying new lesions when scrolling through 2 follow-up MR images can be difficult and time-consuming. Our aim was to compare an automated coregistration-fusion reading approach with the standard approach by identifying new high-signal T2 brain lesions in patients with multiple sclerosis during follow-up MR imaging. This prospective monocenter study included 94 patients (mean age, 38.9 years) treated for MS with dimethyl fumarate from January 2014 to August 2016. One senior neuroradiologist and 1 junior radiologist checked for new high-signal T2 brain lesions, independently analyzing blinded image datasets with automated coregistration-fusion or the standard scroll-through approach with a 3-week delay between the 2 readings. A consensus reading with a second senior neuroradiologist served as a criterion standard for analyses. A Poisson regression and logistic and γ regressions were used to compare the 2 methods. Intra- and interobserver agreement was assessed by the κ coefficient. There were significantly more new high-signal T2 lesions per patient detected with the coregistration-fusion method (7 versus 4, P < .001). The coregistration-fusion method detected significantly more patients with at least 1 new high-signal T2 lesion (59% versus 46%, P = .02) and was associated with significantly faster overall reading time (86 seconds faster, P < .001) and higher reader confidence (91% versus 40%, P < 1 × 10 -4 ). Inter- and intraobserver agreement was excellent for counting new high-signal T2 lesions. Our study showed that an automated coregistration-fusion method was more sensitive for detecting new high-signal T2 lesions in patients with MS and reducing reading time. This method could help to improve follow-up care. © 2018 by American Journal of Neuroradiology.

Efficient IDUA Gene Mutation Detection with Combined Use of dHPLC and Dried Blood Samples

PubMed Central

Duarte, Ana Joana; Vieira, Luis

2013-01-01

Objectives. Development of a simple mutation directed method in order to allow lowering the cost of mutation testing using an easily obtainable biological material. Assessment of the feasibility of such method was tested using a GC-rich amplicon. Design and Methods. A method of denaturing high-performance liquid chromatography (dHPLC) was improved and implemented as a technique for the detection of variants in exon 9 of the IDUA gene. The optimized method was tested in 500 genomic DNA samples obtained from dried blood spots (DBS). Results. With this dHPLC approach it was possible to detect different variants, including the common p.Trp402Ter mutation in the IDUA gene. The high GC content did not interfere with the resolution and reliability of this technique, and discrimination of G-C transversions was also achieved. Conclusion. This PCR-based dHPLC method is proved to be a rapid, a sensitive, and an excellent option for screening numerous samples obtained from DBS. Furthermore, it resulted in the consistent detection of clearly distinguishable profiles of the common p.Trp402Ter IDUA mutation with an advantageous balance of cost and technical requirements. PMID:27335677

Verification of the new detection method for irradiated spices based on microbial survival by collaborative blind trial

NASA Astrophysics Data System (ADS)

Miyahara, M.; Furuta, M.; Takekawa, T.; Oda, S.; Koshikawa, T.; Akiba, T.; Mori, T.; Mimura, T.; Sawada, C.; Yamaguchi, T.; Nishioka, S.; Tada, M.

2009-07-01

An irradiation detection method using the difference of the radiation sensitivity of the heat-treated microorganisms was developed as one of the microbiological detection methods of the irradiated foods. This detection method is based on the difference of the viable cell count before and after heat treatment (70 °C and 10 min). The verification by collaborative blind trial of this method was done by nine inspecting agencies in Japan. The samples used for this trial were five kinds of spices consisting of non-irradiated, 5 kGy irradiated, and 7 kGy irradiated black pepper, allspice, oregano, sage, and paprika, respectively. As a result of this collaboration, a high percentage (80%) of the correct answers was obtained for irradiated black pepper and allspice. However, the method was less successful for irradiated oregano, sage, and paprika. It might be possible to use this detection method for preliminary screening of the irradiated foods but further work is necessary to confirm these findings.

Detection of fatigue cracks by nondestructive testing methods

NASA Technical Reports Server (NTRS)

Anderson, R. T.; Delacy, T. J.; Stewart, R. C.

1973-01-01

The effectiveness was assessed of various NDT methods to detect small tight cracks by randomly introducing fatigue cracks into aluminum sheets. The study included optimizing NDT methods calibrating NDT equipment with fatigue cracked standards, and evaluating a number of cracked specimens by the optimized NDT methods. The evaluations were conducted by highly trained personnel, provided with detailed procedures, in order to minimize the effects of human variability. These personnel performed the NDT on the test specimens without knowledge of the flaw locations and reported on the flaws detected. The performance of these tests was measured by comparing the flaws detected against the flaws present. The principal NDT methods utilized were radiographic, ultrasonic, penetrant, and eddy current. Holographic interferometry, acoustic emission monitoring, and replication methods were also applied on a reduced number of specimens. Generally, the best performance was shown by eddy current, ultrasonic, penetrant and holographic tests. Etching provided no measurable improvement, while proof loading improved flaw detectability. Data are shown that quantify the performances of the NDT methods applied.

Simultaneous determination of four 5-hydroxy polymethoxyflavones by reversed-phase high performance liquid chromatography with electrochemical detection.

PubMed

Dong, Ping; Qiu, Peiju; Zhu, Yi; Li, Shiming; Ho, Chi-Tang; McClements, David Julian; Xiao, Hang

2010-01-29

Accumulating evidence has suggested the potential health-promoting effects of 5-hydroxy polymethoxyflavones (5-OH-PMFs) naturally existing in citrus genus. However, research efforts are hampered by the lack of reliable and sensitive methods for their determination in plant materials and biological samples. Using reversed-phase high performance liquid chromatography (HPLC) equipped with electrochemical (EC) detection, we have developed a fast and highly sensitive method for quantification of four 5-OH-PMFs, namely 5-hydroxy-6,7,8,3',4'-pentamethoxyflavone, 5-hydroxy-3,6,7,8,3',4'-hexamethoxyflavone, 5-hydroxy-6,7,4'-trimethoxyflavone, and 5-hydroxy-6,7,8,4'-tetramethoxyflavone. The method was fully validated in terms of linearity, accuracy and precision. The limit of detection (LOD) was determined as being between 0.65 and 1.8ng/mL (ppb), demonstrating an over 160 times higher sensitivity in comparison with the previously reported method using UV detection. The recovery rate of the method was between 96.17% and 110.82%, and the precision for the retention times and peak areas was all below 13%. The method was successfully used to quantify 5-OH-PMFs with a wide range of abundance in the citrus products and preparations, such as orange juice, citrus peel, and dried tangerine peel. The quantification method for 5-OH-PMFs developed herein could be useful for the nutritional and pharmacological studies of these compounds in future. Copyright (c) 2009 Elsevier B.V. All rights reserved.

RAMA casein zymography: Time-saving and highly sensitive casein zymography for MMP7 and trypsin.

PubMed

Yasumitsu, Hidetaro; Ozeki, Yasuhiro; Kanaly, Robert A

2016-11-01

To detect metalloproteinase-7 (MMP7), zymography is conducted using a casein substrate and conventional CBB stain. It has disadvantages because it is time consuming and has low sensitivity. Previously, a sensitive method to detect MMP7 up to 30 pg was reported, however it required special substrates and complicated handlings. RAMA casein zymography described herein is rapid, sensitive, and reproducible. By applying high-sensitivity staining with low substrate conditions, the staining process is completed within 1 h and sensitivity was increased 100-fold. The method can detect 10 pg MMP7 by using commercially available casein without complicated handlings. Moreover, it increases detection sensitivity for trypsin. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detecting gear tooth fracture in a high contact ratio face gear mesh

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.; Handschuh, Robert F.; Lewicki, David G.; Decker, Harry J.

1995-01-01

This paper summarized the results of a study in which three different vibration diagnostic methods were used to detect gear tooth fracture in a high contact ratio face gear mesh. The NASA spiral bevel gear fatigue test rig was used to produce unseeded fault, natural failures of four face gear specimens. During the fatigue tests, which were run to determine load capacity and primary failure mechanisms for face gears, vibration signals were monitored and recorded for gear diagnostic purposes. Gear tooth bending fatigue and surface pitting were the primary failure modes found in the tests. The damage ranged from partial tooth fracture on a single tooth in one test to heavy wear, severe pitting, and complete tooth fracture of several teeth on another test. Three gear fault detection techniques, FM4, NA4*, and NB4, were applied to the experimental data. These methods use the signal average in both the time and frequency domain. Method NA4* was able to conclusively detect the gear tooth fractures in three out of the four fatigue tests, along with gear tooth surface pitting and heavy wear. For multiple tooth fractures, all of the methods gave a clear indication of the damage. It was also found that due to the high contact ratio of the face gear mesh, single tooth fractures did not significantly affect the vibration signal, making this type of failure difficult to detect.

On-line high-speed rail defect detection : part II.

DOT National Transportation Integrated Search

2012-03-01

The objectives of this project were (1) to improve the defect detection reliability and (2) to improve the inspection speed of conventional rail defect detection methods. The prototype developed in this work uses noncontact transducers, ultrasonic gu...

Detection of dopamine in dopaminergic cell using nanoparticles-based barcode DNA analysis.

PubMed

An, Jeung Hee; Kim, Tae-Hyung; Oh, Byung-Keun; Choi, Jeong Woo

2012-01-01

Nanotechnology-based bio-barcode-amplification analysis may be an innovative approach to dopamine detection. In this study, we evaluated the efficacy of this bio-barcode DNA method in detecting dopamine from dopaminergic cells. Herein, a combination DNA barcode and bead-based immunoassay for neurotransmitter detection with PCR-like sensitivity is described. This method relies on magnetic nanoparticles with antibodies and nanoparticles that are encoded with DNA, and antibodies that can sandwich the target protein captured by the nanoparticle-bound antibodies. The aggregate sandwich structures are magnetically separated from solution, and treated in order to remove the conjugated barcode DNA. The DNA barcodes were then identified via PCR analysis. The dopamine concentration in dopaminergic cells can be readily and rapidly detected via the bio-barcode assay method. The bio-barcode assay method is, therefore, a rapid and high-throughput screening tool for the detection of neurotransmitters such as dopamine.

An interlaboratory study on efficient detection of Shiga toxin-producing Escherichia coli O26, O103, O111, O121, O145, and O157 in food using real-time PCR assay and chromogenic agar.

PubMed

Hara-Kudo, Yukiko; Konishi, Noriko; Ohtsuka, Kayoko; Iwabuchi, Kaori; Kikuchi, Rie; Isobe, Junko; Yamazaki, Takumiko; Suzuki, Fumie; Nagai, Yuhki; Yamada, Hiroko; Tanouchi, Atsuko; Mori, Tetsuya; Nakagawa, Hiroshi; Ueda, Yasufumi; Terajima, Jun

2016-08-02

To establish an efficient detection method for Shiga toxin (Stx)-producing Escherichia coli (STEC) O26, O103, O111, O121, O145, and O157 in food, an interlaboratory study using all the serogroups of detection targets was firstly conducted. We employed a series of tests including enrichment, real-time PCR assays, and concentration by immunomagnetic separation, followed by plating onto selective agar media (IMS-plating methods). This study was particularly focused on the efficiencies of real-time PCR assays in detecting stx and O-antigen genes of the six serogroups and of IMS-plating methods onto selective agar media including chromogenic agar. Ground beef and radish sprouts samples were inoculated with the six STEC serogroups either at 4-6CFU/25g (low levels) or at 22-29CFU/25g (high levels). The sensitivity of stx detection in ground beef at both levels of inoculation with all six STEC serogroups was 100%. The sensitivity of stx detection was also 100% in radish sprouts at high levels of inoculation with all six STEC serogroups, and 66.7%-91.7% at low levels of inoculation. The sensitivity of detection of O-antigen genes was 100% in both ground beef and radish sprouts at high inoculation levels, while at low inoculation levels, it was 95.8%-100% in ground beef and 66.7%-91.7% in radish sprouts. The sensitivity of detection with IMS-plating was either the same or lower than those of the real-time PCR assays targeting stx and O-antigen genes. The relationship between the results of IMS-plating methods and Ct values of real-time PCR assays were firstly analyzed in detail. Ct values in most samples that tested negative in the IMS-plating method were higher than the maximum Ct values in samples that tested positive in the IMS-plating method. This study indicates that all six STEC serogroups in food contaminated with more than 29CFU/25g were detected by real-time PCR assays targeting stx and O-antigen genes and IMS-plating onto selective agar media. Therefore, screening of stx and O-antigen genes followed by isolation of STECs by IMS-plating methods may be an efficient method to detect the six STEC serogroups. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of Non-Culture-Based Methods for Detection of Systemic Fungal Infections, with an Emphasis on Invasive Candida Infections

PubMed Central

White, P. Lewis; Archer, Alice E.; Barnes, Rosemary A.

2005-01-01

The accepted limitations associated with classic culture techniques for the diagnosis of invasive fungal infections have lead to the emergence of many non-culture-based methods. With superior sensitivities and quicker turnaround times, non-culture-based methods may aid the diagnosis of invasive fungal infections. In this review of the diagnostic service, we assessed the performances of two antigen detection techniques (enzyme-linked immunosorbent assay [ELISA] and latex agglutination) with a molecular method for the detection of invasive Candida infection and invasive aspergillosis. The specificities for all three assays were high (≥97%), although the Candida PCR method had enhanced sensitivity over both ELISA and latex agglutination with values of 95%, 75%, and 25%, respectively. However, calculating significant sensitivity values for the Aspergillus detection methods was not feasible due to a low number of proven/probable cases. Despite enhanced sensitivity, the PCR method failed to detect nucleic acid in a probable case of invasive Candida infection that was detected by ELISA. In conclusion, both PCR and ELISA techniques should be used in unison to aid the detection of invasive fungal infections. PMID:15872239

The Need and Potential of Biosensors to Detect Dioxins and Dioxin-Like Polychlorinated Biphenyls along the Milk, Eggs and Meat Food Chain

PubMed Central

Chobtang, Jeerasak; de Boer, Imke J. M.; Hoogenboom, Ron L. A. P.; Haasnoot, Willem; Kijlstra, Aize; Meerburg, Bastiaan G.

2011-01-01

Dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) are hazardous toxic, ubiquitous and persistent chemical compounds, which can enter the food chain and accumulate up to higher trophic levels. Their determination requires sophisticated methods, expensive facilities and instruments, well-trained personnel and expensive chemical reagents. Ideally, real-time monitoring using rapid detection methods should be applied to detect possible contamination along the food chain in order to prevent human exposure. Sensor technology may be promising in this respect. This review gives the state of the art for detecting possible contamination with dioxins and DL-PCBs along the food chain of animal-source foods. The main detection methods applied (i.e., high resolution gas-chromatography combined with high resolution mass-spectrometry (HRGC/HRMS) and the chemical activated luciferase gene expression method (CALUX bioassay)), each have their limitations. Biosensors for detecting dioxins and related compounds, although still under development, show potential to overcome these limitations. Immunosensors and biomimetic-based biosensors potentially offer increased selectivity and sensitivity for dioxin and DL-PCB detection, while whole cell-based biosensors present interpretable biological results. The main shortcoming of current biosensors, however, is their detection level: this may be insufficient as limits for dioxins and DL-PCBs for food and feedstuffs are in pg per gram level. In addition, these contaminants are normally present in fat, a difficult matrix for biosensor detection. Therefore, simple and efficient extraction and clean-up procedures are required which may enable biosensors to detect dioxins and DL-PCBs contamination along the food chain. PMID:22247688

The need and potential of biosensors to detect dioxins and dioxin-like polychlorinated biphenyls along the milk, eggs and meat food chain.

PubMed

Chobtang, Jeerasak; de Boer, Imke J M; Hoogenboom, Ron L A P; Haasnoot, Willem; Kijlstra, Aize; Meerburg, Bastiaan G

2011-01-01

Dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) are hazardous toxic, ubiquitous and persistent chemical compounds, which can enter the food chain and accumulate up to higher trophic levels. Their determination requires sophisticated methods, expensive facilities and instruments, well-trained personnel and expensive chemical reagents. Ideally, real-time monitoring using rapid detection methods should be applied to detect possible contamination along the food chain in order to prevent human exposure. Sensor technology may be promising in this respect. This review gives the state of the art for detecting possible contamination with dioxins and DL-PCBs along the food chain of animal-source foods. The main detection methods applied (i.e., high resolution gas-chromatography combined with high resolution mass-spectrometry (HRGC/HRMS) and the chemical activated luciferase gene expression method (CALUX bioassay)), each have their limitations. Biosensors for detecting dioxins and related compounds, although still under development, show potential to overcome these limitations. Immunosensors and biomimetic-based biosensors potentially offer increased selectivity and sensitivity for dioxin and DL-PCB detection, while whole cell-based biosensors present interpretable biological results. The main shortcoming of current biosensors, however, is their detection level: this may be insufficient as limits for dioxins and DL-PCBs for food and feedstuffs are in pg per gram level. In addition, these contaminants are normally present in fat, a difficult matrix for biosensor detection. Therefore, simple and efficient extraction and clean-up procedures are required which may enable biosensors to detect dioxins and DL-PCBs contamination along the food chain.

Convenient, Sensitive and High-Throughput Method for Screening Botanic Origin

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Jiang, Chao; Liu, Libing; Yu, Shulin; Cui, Zhanhu; Chen, Min; Lin, Shufang; Wang, Shu; Huang, Luqi

2014-06-01

In this work, a rapid (within 4-5 h), sensitive and visible new method for assessing botanic origin is developed by combining loop-mediated isothermal amplification with cationic conjugated polymers. The two Chinese medicinal materials (Jin-Yin-Hua and Shan-Yin-Hua) with similar morphology and chemical composition were clearly distinguished by gene SNP genotyping assays. The identification of plant species in Patented Chinese drugs containing Lonicera buds is successfully performed using this detection system. The method is also robust enough to be used in high-throughput screening. This new method is very helpful to identify herbal materials, and is beneficial for detecting safety and quality of botanic products.

Analysis of selected herbicide metabolites in surface and ground water of the United States

USGS Publications Warehouse

Scribner, E.A.; Thurman, E.M.; Zimmerman, L.R.

2000-01-01

One of the primary goals of the US Geological Survey (USGS) Laboratory in Lawrence, Kansas, is to develop analytical methods for the analysis of herbicide metabolites in surface and ground water that are vital to the study of herbicide fate and degradation pathways in the environment. Methods to measure metabolite concentrations from three major classes of herbicides - triazine, chloroacetanilide and phenyl-urea - have been developed. Methods for triazine metabolite detection cover nine compounds: six compounds are detected by gas chromatography/mass spectrometry; one is detected by high-performance liquid chromatography with diode-array detection; and eight are detected by liquid chromatography/mass spectrometry. Two metabolites of the chloroacetanilide herbicides - ethane sulfonic acid and oxanilic acid - are detected by high-performance liquid chromatography with diode-array detection and liquid chromatography/mass spectrometry. Alachlor ethane sulfonic acid also has been detected by solid-phase extraction and enzyme-linked immunosorbent assay. Six phenylurea metabolites are all detected by liquid chromatography/mass spectrometry; four of the six metabolites also are detected by gas chromatography/mass spectrometry. Additionally, surveys of herbicides and their metabolites in surface water, ground water, lakes, reservoirs, and rainfall have been conducted through the USGS laboratory in Lawrence. These surveys have been useful in determining herbicide and metabolite occurrence and temporal distribution and have shown that metabolites may be useful in evaluation of non-point-source contamination. Copyright (C) 2000 Elsevier Science B.V.

High-order optical vortex position detection using a Shack-Hartmann wavefront sensor.

PubMed

Luo, Jia; Huang, Hongxin; Matsui, Yoshinori; Toyoda, Haruyoshi; Inoue, Takashi; Bai, Jian

2015-04-06

Optical vortex (OV) beams have null-intensity singular points, and the intensities in the region surrounding the singular point are quite low. This low intensity region influences the position detection accuracy of phase singular point, especially for high-order OV beam. In this paper, we propose a new method for solving this problem, called the phase-slope-combining correlation matching method. A Shack-Hartmann wavefront sensor (SH-WFS) is used to measure phase slope vectors at lenslet positions of the SH-WFS. Several phase slope vectors are combined into one to reduce the influence of low-intensity regions around the singular point, and the combined phase slope vectors are used to determine the OV position with the aid of correlation matching with a pre-calculated database. Experimental results showed that the proposed method works with high accuracy, even when detecting an OV beam with a topological charge larger than six. The estimated precision was about 0.15 in units of lenslet size when detecting an OV beam with a topological charge of up to 20.

Blinded study determination of high sensitivity and specificity microchip electrophoresis–SSCP/HA to detect mutations in the p53 gene

PubMed Central

Hestekin, Christa N.; Lin, Jennifer S.; Senderowicz, Lionel; Jakupciak, John P.; O’Connell, Catherine; Rademaker, Alfred; Barron, Annelise E.

2012-01-01

Knowledge of the genetic changes that lead to disease has grown and continues to grow at a rapid pace. However, there is a need for clinical devices that can be used routinely to translate this knowledge into the treatment of patients. Use in a clinical setting requires high sensitivity and specificity (>97%) in order to prevent misdiagnoses. Single strand conformational polymorphism (SSCP) and heteroduplex analysis (HA) are two DNA-based, complementary methods for mutation detection that are inexpensive and relatively easy to implement. However, both methods are most commonly detected by slab gel electrophoresis, which can be labor-intensive, time-consuming, and often the methods are unable to produce high sensitivity and specificity without the use of multiple analysis conditions. Here we demonstrate the first blinded study using microchip electrophoresis-SSCP/HA. We demonstrate the ability of microchip electrophoresis-SSCP/HA to detect with 98% sensitivity and specificity >100 samples from the p53 gene exons 5–9 in a blinded study in an analysis time of less than 10 minutes. PMID:22002021

A novel method to detect shadows on multispectral images

NASA Astrophysics Data System (ADS)

Daǧlayan Sevim, Hazan; Yardımcı ćetin, Yasemin; Özışık Başkurt, Didem

2016-10-01

Shadowing occurs when the direct light coming from a light source is obstructed by high human made structures, mountains or clouds. Since shadow regions are illuminated only by scattered light, true spectral properties of the objects are not observed in such regions. Therefore, many object classification and change detection problems utilize shadow detection as a preprocessing step. Besides, shadows are useful for obtaining 3D information of the objects such as estimating the height of buildings. With pervasiveness of remote sensing images, shadow detection is ever more important. This study aims to develop a shadow detection method on multispectral images based on the transformation of C1C2C3 space and contribution of NIR bands. The proposed method is tested on Worldview-2 images covering Ankara, Turkey at different times. The new index is used on these 8-band multispectral images with two NIR bands. The method is compared with methods in the literature.

Highly sensitive protein detection by biospecific AFM-based fishing with pulsed electrical stimulation.

PubMed

Pleshakova, Tatyana O; Malsagova, Kristina A; Kaysheva, Anna L; Kopylov, Arthur T; Tatur, Vadim Yu; Ziborov, Vadim S; Kanashenko, Sergey L; Galiullin, Rafael A; Ivanov, Yuri D

2017-08-01

We report here the highly sensitive detection of protein in solution at concentrations from 10 -15 to 10 -18 m using the combination of atomic force microscopy (AFM) and mass spectrometry. Biospecific detection of biotinylated bovine serum albumin was carried out by fishing out the protein onto the surface of AFM chips with immobilized avidin, which determined the specificity of the analysis. Electrical stimulation was applied to enhance the fishing efficiency. A high sensitivity of detection was achieved by application of nanosecond electric pulses to highly oriented pyrolytic graphite placed under the AFM chip. A peristaltic pump-based flow system, which is widely used in routine bioanalytical assays, was employed throughout the analysis. These results hold promise for the development of highly sensitive protein detection methods using nanosensor devices.

Modeling seasonal detection patterns for burrowing owl surveys

Treesearch

Quresh S. Latif; Kathleen D. Fleming; Cameron Barrows; John T. Rotenberry

2012-01-01

To guide monitoring of burrowing owls (Athene cunicularia) in the Coachella Valley, California, USA, we analyzed survey-method-specific seasonal variation in detectability. Point-based call-broadcast surveys yielded high early season detectability that then declined through time, whereas detectability on driving surveys increased through the season. Point surveys...

Meat authentication: a new HPLC-MS/MS based method for the fast and sensitive detection of horse and pork in highly processed food.

PubMed

von Bargen, Christoph; Brockmeyer, Jens; Humpf, Hans-Ulrich

2014-10-01

Fraudulent blending of food products with meat from undeclared species is a problem on a global scale, as exemplified by the European horse meat scandal in 2013. Routinely used methods such as ELISA and PCR can suffer from limited sensitivity or specificity when processed food samples are analyzed. In this study, we have developed an optimized method for the detection of horse and pork in different processed food matrices using MRM and MRM(3) detection of species-specific tryptic marker peptides. Identified marker peptides were sufficiently stable to resist thermal processing of different meat products and thus allow the sensitive and specific detection of pork or horse in processed food down to 0.24% in a beef matrix system. In addition, we were able to establish a rapid 2-min extraction protocol for the efficient protein extraction from processed food using high molar urea and thiourea buffers. Together, we present here the specific and sensitive detection of horse and pork meat in different processed food matrices using MRM-based detection of marker peptides. Notably, prefractionation of proteins using 2D-PAGE or off-gel fractionation is not necessary. The presented method is therefore easily applicable in analytical routine laboratories without dedicated proteomics background.

Rapid detection of potyviruses from crude plant extracts.

PubMed

Silva, Gonçalo; Oyekanmi, Joshua; Nkere, Chukwuemeka K; Bömer, Moritz; Kumar, P Lava; Seal, Susan E

2018-04-01

Potyviruses (genus Potyvirus; family Potyviridae) are widely distributed and represent one of the most economically important genera of plant viruses. Therefore, their accurate detection is a key factor in developing efficient control strategies. However, this can sometimes be problematic particularly in plant species containing high amounts of polysaccharides and polyphenols such as yam (Dioscorea spp.). Here, we report the development of a reliable, rapid and cost-effective detection method for the two most important potyviruses infecting yam based on reverse transcription-recombinase polymerase amplification (RT-RPA). The developed method, named 'Direct RT-RPA', detects each target virus directly from plant leaf extracts prepared with a simple and inexpensive extraction method avoiding laborious extraction of high-quality RNA. Direct RT-RPA enables the detection of virus-positive samples in under 30 min at a single low operation temperature (37 °C) without the need for any expensive instrumentation. The Direct RT-RPA tests constitute robust, accurate, sensitive and quick methods for detection of potyviruses from recalcitrant plant species. The minimal sample preparation requirements and the possibility of storing RPA reagents without cold chain storage, allow Direct RT-RPA to be adopted in minimally equipped laboratories and with potential use in plant clinic laboratories and seed certification facilities worldwide. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Development of a real-time PCR assay with an internal amplification control for detection of Gram-negative histamine-producing bacteria in fish.

PubMed

Bjornsdottir-Butler, Kristin; Jones, Jessica L; Benner, Ronald; Burkhardt, William

2011-05-01

Prompt detection of bacteria that contribute to scombrotoxin (histamine) fish poisoning can aid in the detection of potentially toxic fish products and prevent the occurrence of illness. We report development of the first real-time PCR method for rapid detection of Gram-negative histamine-producing bacteria (HPB) in fish. The real-time PCR assay was 100% inclusive for detecting high-histamine producing isolates and did not detect any of the low- or non-histamine producing isolates. The efficiency of the assay with/without internal amplification control ranged from 96-104% and in the presence of background flora and inhibitory matrices was 92/100% and 73-96%, respectively. This assay was used to detect HPB from naturally contaminated yellowfin tuna, bluefish, and false albacore samples. Photobacterium damselae (8), Plesiomonas shigelloides (2), Shewanella sp. (1), and Morganella morganii (1) were subsequently isolated from the real-time PCR positive fish samples. These results indicate that the real-time PCR assay developed in this study is a rapid and sensitive method for detecting high-HPB. The assay may be adapted for quantification of HPB, either directly or with an MPN-PCR method. Copyright © 2010. Published by Elsevier Ltd.

Loop-mediated isothermal amplification (LAMP): a versatile technique for detection of micro-organisms.

PubMed

Wong, Y-P; Othman, S; Lau, Y-L; Radu, S; Chee, H-Y

2018-03-01

Loop-mediated isothermal amplification (LAMP) amplifies DNA with high specificity, efficiency and rapidity under isothermal conditions by using a DNA polymerase with high displacement strand activity and a set of specifically designed primers to amplify targeted DNA strands. Following its first discovery by Notomi et al. ( Nucleic Acids Res 28: E63), LAMP was further developed over the years which involved the combination of this technique with other molecular approaches, such as reverse transcription and multiplex amplification for the detection of infectious diseases caused by micro-organisms in humans, livestock and plants. In this review, available types of LAMP techniques will be discussed together with their applications in detection of various micro-organisms. Up to date, there are varieties of LAMP detection methods available including colorimetric and fluorescent detection, real-time monitoring using turbidity metre and detection using lateral flow device which will also be highlighted in this review. Apart from that, commercialization of LAMP technique had also been reported such as lyophilized form of LAMP reagents kit and LAMP primer sets for detection of pathogenic micro-organisms. On top of that, advantages and limitations of this molecular detection method are also described together with its future potential as a diagnostic method for infectious disease. © 2017 The Society for Applied Microbiology.

[Real-time PCR kits for the detection of the African Swine Fever virus].

PubMed

Latyshev, O E; Eliseeva, O V; Grebennikova, T V; Verkhovskiĭ, O A; Tsibezov, V V; Chernykh, O Iu; Dzhailidi, G A; Aliper, T I

2014-01-01

The results obtained using the diagnostic kit based on real-time polymerase chain reaction to detect the DNA of the African Swine Fever in the pathological material, as well as in the culture fluid, are presented. A high sensitivity and specificity for detection of the DNA in the organs and tissues of animals was shown to be useful for detection in the European Union referentiality reagent kits for DNA detection by real time PCR of ASFV. More rapid and effective method of DNA extraction using columns mini spin Quick gDNA(TM) MiniPrep was suggested and compared to the method of DNA isolation on the inorganic sorbent. High correlation of the results of the DNA detection of ASFV by real-time PCR and antigen detection results ASFV by competitive ELISA obtained with the ELISA SEROTEST/INGEZIM COMRAC PPA was demonstrated. The kit can be used in the veterinary services for effective monitoring of ASFV to contain, eliminate and prevent further spread of the disease.

Rapid solid-phase microwave synthesis of highly photoluminescent nitrogen-doped carbon dots for Fe3+ detection and cellular bioimaging

NASA Astrophysics Data System (ADS)

He, Guili; Xu, Minghan; Shu, Mengjun; Li, Xiaolin; Yang, Zhi; Zhang, Liling; Su, Yanjie; Hu, Nantao; Zhang, Yafei

2016-09-01

Recently, carbon dots (CDs) have been playing an increasingly important role in industrial production and biomedical field because of their excellent properties. As such, finding an efficient method to quickly synthesize a large scale of relatively high purity CDs is of great interest. Herein, a facile and novel microwave method has been applied to prepare nitrogen doped CDs (N-doped CDs) within 8 min using L-glutamic acid as the sole reaction precursor in the solid phase condition. The as-prepared N-doped CDs with an average size of 1.64 nm are well dispersed in aqueous solution. The photoluminescence of N-doped CDs is pH-sensitive and excitation-dependent. The N-doped CDs show a strong blue fluorescence with relatively high fluorescent quantum yield of 41.2%, which remains stable even under high ionic strength. Since the surface is rich in oxygen-containing functional groups, N-doped CDs can be applied to selectively detect Fe3+ with the limit of detection of 10-5 M. In addition, they are also used for cellular bioimaging because of their high fluorescent intensity and nearly zero cytotoxicity. The solid-phase microwave method seems to be an effective strategy to rapidly obtain high quality N-doped CDs and expands their applications in ion detection and cellular bioimaging.

High-resolution melting (HRM) re-analysis of a polyposis patients cohort reveals previously undetected heterozygous and mosaic APC gene mutations.

PubMed

Out, Astrid A; van Minderhout, Ivonne J H M; van der Stoep, Nienke; van Bommel, Lysette S R; Kluijt, Irma; Aalfs, Cora; Voorendt, Marsha; Vossen, Rolf H A M; Nielsen, Maartje; Vasen, Hans F A; Morreau, Hans; Devilee, Peter; Tops, Carli M J; Hes, Frederik J

2015-06-01

Familial adenomatous polyposis is most frequently caused by pathogenic variants in either the APC gene or the MUTYH gene. The detection rate of pathogenic variants depends on the severity of the phenotype and sensitivity of the screening method, including sensitivity for mosaic variants. For 171 patients with multiple colorectal polyps without previously detectable pathogenic variant, APC was reanalyzed in leukocyte DNA by one uniform technique: high-resolution melting (HRM) analysis. Serial dilution of heterozygous DNA resulted in a lowest detectable allelic fraction of 6% for the majority of variants. HRM analysis and subsequent sequencing detected pathogenic fully heterozygous APC variants in 10 (6%) of the patients and pathogenic mosaic variants in 2 (1%). All these variants were previously missed by various conventional scanning methods. In parallel, HRM APC scanning was applied to DNA isolated from polyp tissue of two additional patients with apparently sporadic polyposis and without detectable pathogenic APC variant in leukocyte DNA. In both patients a pathogenic mosaic APC variant was present in multiple polyps. The detection of pathogenic APC variants in 7% of the patients, including mosaics, illustrates the usefulness of a complete APC gene reanalysis of previously tested patients, by a supplementary scanning method. HRM is a sensitive and fast pre-screening method for reliable detection of heterozygous and mosaic variants, which can be applied to leukocyte and polyp derived DNA.

Validation of a high-performance liquid chromatographic method with UV detection for the determination of ethopabate residues in poultry liver.

PubMed

Granja, Rodrigo H M M; Niño, Alfredo M Montes; Zucchetti, Roberto A M; Niño, Rosario E Montes; Salerno, Alessandro G

2008-01-01

Ethopabate is frequently used in the prophylaxis and treatment of coccidiosis in poultry. Residues of this drug in food present a potential risk to consumers. A simple, rapid, and sensitive column high-performance liquid chromatographic (HPLC) method with UV detection for determination of ethopabate in poultry liver is presented. The drug is extracted with acetonitrile. After evaporation, the residue is dissolved with an acetone-hexane mixture and cleaned up by solid-phase extraction using Florisil columns. The analyte is then eluted with methanol. LC analysis is carried out on a C18 5 microm Gemini column, 15 cm x 4.6 mm. Ethopabate is quantified by means of UV detection at 270 nm. Parameters such as decision limit, detection capability, precision, recovery, ruggedness, and measurement uncertainty were calculated according to method validation guidelines provided in 2002/657/EC and ISO/IEC 17025:2005. Decision limit and detection capability were determined to be 2 and 3 microg/kg, respectively. Average recoveries from poultry samples fortified with 10, 15, and 20 microg/kg levels of ethopabate were 100-105%. A complete statistical analysis was performed on the results obtained, including an estimation of the method uncertainty. The method is to be implemented into Brazil's residue monitoring and control program for ethopabate.

Automatic detection of Martian dark slope streaks by machine learning using HiRISE images

NASA Astrophysics Data System (ADS)

Wang, Yexin; Di, Kaichang; Xin, Xin; Wan, Wenhui

2017-07-01

Dark slope streaks (DSSs) on the Martian surface are one of the active geologic features that can be observed on Mars nowadays. The detection of DSS is a prerequisite for studying its appearance, morphology, and distribution to reveal its underlying geological mechanisms. In addition, increasingly massive amounts of Mars high resolution data are now available. Hence, an automatic detection method for locating DSSs is highly desirable. In this research, we present an automatic DSS detection method by combining interest region extraction and machine learning techniques. The interest region extraction combines gradient and regional grayscale information. Moreover, a novel recognition strategy is proposed that takes the normalized minimum bounding rectangles (MBRs) of the extracted regions to calculate the Local Binary Pattern (LBP) feature and train a DSS classifier using the Adaboost machine learning algorithm. Comparative experiments using five different feature descriptors and three different machine learning algorithms show the superiority of the proposed method. Experimental results utilizing 888 extracted region samples from 28 HiRISE images show that the overall detection accuracy of our proposed method is 92.4%, with a true positive rate of 79.1% and false positive rate of 3.7%, which in particular indicates great performance of the method at eliminating non-DSS regions.

A New Cloud and Aerosol Layer Detection Method Based on Micropulse Lidar Measurements

NASA Astrophysics Data System (ADS)

Wang, Q.; Zhao, C.; Wang, Y.; Li, Z.; Wang, Z.; Liu, D.

2014-12-01

A new algorithm is developed to detect aerosols and clouds based on micropulse lidar (MPL) measurements. In this method, a semi-discretization processing (SDP) technique is first used to inhibit the impact of increasing noise with distance, then a value distribution equalization (VDE) method is introduced to reduce the magnitude of signal variations with distance. Combined with empirical threshold values, clouds and aerosols are detected and separated. This method can detect clouds and aerosols with high accuracy, although classification of aerosols and clouds is sensitive to the thresholds selected. Compared with the existing Atmospheric Radiation Measurement (ARM) program lidar-based cloud product, the new method detects more high clouds. The algorithm was applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu site. At SGP, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring, and shows bi-modal vertical distributions with maximum frequency at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. By contrast, the cloud frequency at Taihu shows no clear seasonal variation and the maximum frequency is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at SGP.

DuPont Qualicon BAX System polymerase chain reaction assay. Performance Tested Method 100201.

PubMed

Tice, George; Andaloro, Bridget; Fallon, Dawn; Wallace, F Morgan

2009-01-01

A recent outbreak of Salmonella in peanut butter has highlighted the need for validation of rapid detection methods. A multilaboratory study for detecting Salmonella in peanut butter was conducted as part of the AOAC Research Institute Emergency Response Validation program for methods that detect outbreak threats to food safety. Three sites tested spiked samples from the same master mix according to the U.S. Food and Drug Administration's Bacteriological Analytical Manual (FDA-BAM) method and the BAX System method. Salmonella Typhimurium (ATCC 14028) was grown in brain heart infusion for 24 h at 37 degrees C, then diluted to appropriate levels for sample inoculation. Master samples of peanut butter were spiked at high and low target levels, mixed, and allowed to equilibrate at room temperature for 2 weeks. Spike levels were low [1.08 most probable number (MPN)/25 g]; high (11.5 MPN/25 g) and unspiked to serve as negative controls. Each master sample was divided into 25 g portions and coded to blind the samples. Twenty portions of each spiked master sample and five portions of the unspiked sample were tested at each site. At each testing site, samples were blended in 25 g portions with 225 mL prewarmed lactose broth until thoroughly homogenized, then allowed to remain at room temperature for 55-65 min. Samples were adjusted to a pH of 6.8 +/- 0.2, if necessary, and incubated for 22-26 h at 35 degrees C. Across the three reporting laboratories, the BAX System detected Salmonella in 10/60 low-spike samples and 58/60 high-spike samples. The reference FDA-BAM method yielded positive results for 11/60 low-spike and 58/60 high-spike samples. Neither method demonstrated positive results for any of the 15 unspiked samples.

CNV detection method optimized for high-resolution arrayCGH by normality test.

PubMed

Ahn, Jaegyoon; Yoon, Youngmi; Park, Chihyun; Park, Sanghyun

2012-04-01

High-resolution arrayCGH platform makes it possible to detect small gains and losses which previously could not be measured. However, current CNV detection tools fitted to early low-resolution data are not applicable to larger high-resolution data. When CNV detection tools are applied to high-resolution data, they suffer from high false-positives, which increases validation cost. Existing CNV detection tools also require optimal parameter values. In most cases, obtaining these values is a difficult task. This study developed a CNV detection algorithm that is optimized for high-resolution arrayCGH data. This tool operates up to 1500 times faster than existing tools on a high-resolution arrayCGH of whole human chromosomes which has 42 million probes whose average length is 50 bases, while preserving false positive/negative rates. The algorithm also uses a normality test, thereby removing the need for optimal parameters. To our knowledge, this is the first formulation for CNV detecting problems that results in a near-linear empirical overall complexity for real high-resolution data. Copyright © 2012 Elsevier Ltd. All rights reserved.

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads.

PubMed

Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi

2018-03-09

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

A highly sensitive SPRi biosensing strategy for simultaneous detection of multiplex miRNAs based on strand displacement amplification and AuNP signal enhancement.

PubMed

Wei, Xiaotong; Duan, Xiaolei; Zhou, Xiaoyan; Wu, Jiangling; Xu, Hongbing; Min, Xun; Ding, Shijia

2018-06-07

Herein, a dual channel surface plasmon resonance imaging (SPRi) biosensor has been developed for the simultaneous and highly sensitive detection of multiplex miRNAs based on strand displacement amplification (SDA) and DNA-functionalized AuNP signal enhancement. In the presence of target miRNAs (miR-21 or miR-192), the miRNAs could specifically hybridize with the corresponding hairpin probes (H) and initiate the SDA, resulting in massive triggers. Subsequently, the two parts of the released triggers could hybridize with capture probes (CP) and DNA-functionalized AuNPs, assembling DNA sandwiches with great mass on the chip surface. A significantly amplified SPR signal readout was achieved. This established biosensing method was capable of simultaneously detecting multiplex miRNAs with a limit of detection down to 0.15 pM for miR-21 and 0.22 pM for miR-192. This method exhibited good specificity and acceptable reproducibility. Moreover, the developed method was applied to the determination of target miRNAs in a complex matrix. Thus, this developed SPRi biosensing method may present a potential alternative tool for miRNA detection in biomedical research and clinical diagnosis.

Development and validation of a multiplex real-time PCR method to simultaneously detect 47 targets for the identification of genetically modified organisms.

PubMed

Cottenet, Geoffrey; Blancpain, Carine; Sonnard, Véronique; Chuah, Poh Fong

2013-08-01

Considering the increase of the total cultivated land area dedicated to genetically modified organisms (GMO), the consumers' perception toward GMO and the need to comply with various local GMO legislations, efficient and accurate analytical methods are needed for their detection and identification. Considered as the gold standard for GMO analysis, the real-time polymerase chain reaction (RTi-PCR) technology was optimised to produce a high-throughput GMO screening method. Based on simultaneous 24 multiplex RTi-PCR running on a ready-to-use 384-well plate, this new procedure allows the detection and identification of 47 targets on seven samples in duplicate. To comply with GMO analytical quality requirements, a negative and a positive control were analysed in parallel. In addition, an internal positive control was also included in each reaction well for the detection of potential PCR inhibition. Tested on non-GM materials, on different GM events and on proficiency test samples, the method offered high specificity and sensitivity with an absolute limit of detection between 1 and 16 copies depending on the target. Easy to use, fast and cost efficient, this multiplex approach fits the purpose of GMO testing laboratories.

Optical sensing: recognition elements and devices

NASA Astrophysics Data System (ADS)

Gauglitz, Guenter G.

2012-09-01

The requirements in chemical and biochemical sensing with respect to recognition elements, avoiding non-specific interactions, and high loading of the surface for detection of low concentrations as well as optimized detection systems are discussed. Among the many detection principles the optical techniques are classified. Methods using labeled compounds like Total Internal Reflection Fluorescence (TIRF) and direct optical methods like micro reflectometry or refractometry are discussed in comparison. Reflectometric Interference Spectroscopy (RIfS) is presented as a robust simple method for biosensing. As applications, trace analysis of endocrine disruptors in water, hormones in food, detection of viruses and bacteria in food and clinical diagnostics are discussed.

High-Density Droplet Microarray of Individually Addressable Electrochemical Cells.

PubMed

Zhang, Huijie; Oellers, Tobias; Feng, Wenqian; Abdulazim, Tarik; Saw, En Ning; Ludwig, Alfred; Levkin, Pavel A; Plumeré, Nicolas

2017-06-06

Microarray technology has shown great potential for various types of high-throughput screening applications. The main read-out methods of most microarray platforms, however, are based on optical techniques, limiting the scope of potential applications of such powerful screening technology. Electrochemical methods possess numerous complementary advantages over optical detection methods, including its label-free nature, capability of quantitative monitoring of various reporter molecules, and the ability to not only detect but also address compositions of individual compartments. However, application of electrochemical methods for the purpose of high-throughput screening remains very limited. In this work, we develop a high-density individually addressable electrochemical droplet microarray (eDMA). The eDMA allows for the detection of redox-active reporter molecules irrespective of their electrochemical reversibility in individual nanoliter-sized droplets. Orthogonal band microelectrodes are arranged to form at their intersections an array of three-electrode systems for precise control of the applied potential, which enables direct read-out of the current related to analyte detection. The band microelectrode array is covered with a layer of permeable porous polymethacrylate functionalized with a highly hydrophobic-hydrophilic pattern, forming spatially separated nanoliter-sized droplets on top of each electrochemical cell. Electrochemical characterization of single droplets demonstrates that the underlying electrode system is accessible to redox-active molecules through the hydrophilic polymeric pattern and that the nonwettable hydrophobic boundaries can spatially separate neighboring cells effectively. The eDMA technology opens the possibility to combine the high-throughput biochemical or living cell screenings using the droplet microarray platform with the sequential electrochemical read-out of individual droplets.

Ultrafast dark-field surface inspection with hybrid-dispersion laser scanning

NASA Astrophysics Data System (ADS)

Yazaki, Akio; Kim, Chanju; Chan, Jacky; Mahjoubfar, Ata; Goda, Keisuke; Watanabe, Masahiro; Jalali, Bahram

2014-06-01

High-speed surface inspection plays an important role in industrial manufacturing, safety monitoring, and quality control. It is desirable to go beyond the speed limitation of current technologies for reducing manufacturing costs and opening a new window onto a class of applications that require high-throughput sensing. Here, we report a high-speed dark-field surface inspector for detection of micrometer-sized surface defects that can travel at a record high speed as high as a few kilometers per second. This method is based on a modified time-stretch microscope that illuminates temporally and spatially dispersed laser pulses on the surface of a fast-moving object and detects scattered light from defects on the surface with a sensitive photodetector in a dark-field configuration. The inspector's ability to perform ultrafast dark-field surface inspection enables real-time identification of difficult-to-detect features on weakly reflecting surfaces and hence renders the method much more practical than in the previously demonstrated bright-field configuration. Consequently, our inspector provides nearly 1000 times higher scanning speed than conventional inspectors. To show our method's broad utility, we demonstrate real-time inspection of the surface of various objects (a non-reflective black film, transparent flexible film, and reflective hard disk) for detection of 10 μm or smaller defects on a moving target at 20 m/s within a scan width of 25 mm at a scan rate of 90.9 MHz. Our method holds promise for improving the cost and performance of organic light-emitting diode displays for next-generation smart phones, lithium-ion batteries for green electronics, and high-efficiency solar cells.

Development of a highly sensitive immunochromatographic detection kit for H5 influenza virus hemagglutinin using silver amplification.

PubMed

Wada, Atsuhiko; Sakoda, Yoshihiro; Oyamada, Takayoshi; Kida, Hiroshi

2011-12-01

H5N1, a highly pathogenic avian influenza virus (HPAIV), has become a serious epizootic threat to the poultry population in Asia. In addition, significant numbers of human cases of HPAIV infection have been reported to date. To prevent the spread of HPAIV among humans and to allow for timely medical intervention, a rapid and high sensitive method is needed to detect and subtype the causative HPAIVs. In the present study, a silver amplification technique used in photographic development was combined with immunochromatography technologies and a highly sensitive and rapid diagnostic test to detect the hemagglutinin of H5 influenza viruses was developed. The sensitivity of the test kit was increased 500 times by silver amplification. The sensitivity of the method was more than 10 times higher than those of conventional rapid influenza diagnostic tests, which detect viral nucleoproteins. The diagnostic system developed in the present study can therefore provide rapid and highly sensitive results and will be useful for diagnosis of H5 HPAIV infection in humans and animals. Copyright © 2011 Elsevier B.V. All rights reserved.

CNV-TV: a robust method to discover copy number variation from short sequencing reads.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Deng, Hong-Wen; Wang, Yu-Ping

2013-05-02

Copy number variation (CNV) is an important structural variation (SV) in human genome. Various studies have shown that CNVs are associated with complex diseases. Traditional CNV detection methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from low resolution. The next generation sequencing (NGS) technique promises a higher resolution detection of CNVs and several methods were recently proposed for realizing such a promise. However, the performances of these methods are not robust under some conditions, e.g., some of them may fail to detect CNVs of short sizes. There has been a strong demand for reliable detection of CNVs from high resolution NGS data. A novel and robust method to detect CNV from short sequencing reads is proposed in this study. The detection of CNV is modeled as a change-point detection from the read depth (RD) signal derived from the NGS, which is fitted with a total variation (TV) penalized least squares model. The performance (e.g., sensitivity and specificity) of the proposed approach are evaluated by comparison with several recently published methods on both simulated and real data from the 1000 Genomes Project. The experimental results showed that both the true positive rate and false positive rate of the proposed detection method do not change significantly for CNVs with different copy numbers and lengthes, when compared with several existing methods. Therefore, our proposed approach results in a more reliable detection of CNVs than the existing methods.

Study on the Automatic Detection Method and System of Multifunctional Hydrocephalus Shunt

NASA Astrophysics Data System (ADS)

Sun, Xuan; Wang, Guangzhen; Dong, Quancheng; Li, Yuzhong

2017-07-01

Aiming to the difficulty of micro pressure detection and the difficulty of micro flow control in the testing process of hydrocephalus shunt, the principle of the shunt performance detection was analyzed.In this study, the author analyzed the principle of several items of shunt performance detection,and used advanced micro pressure sensor and micro flow peristaltic pump to overcome the micro pressure detection and micro flow control technology.At the same time,This study also puted many common experimental projects integrated, and successfully developed the automatic detection system for a shunt performance detection function, to achieve a test with high precision, high efficiency and automation.

Colorimetric and fluorescent detection of hydrazine with high sensitivity and excellent selectivity

NASA Astrophysics Data System (ADS)

Shi, Bingjie; Qi, Sujie; Yu, Mingming; Liu, Chunxia; Li, Zhanxian; Wei, Liuhe; Ni, Zhonghai

2018-01-01

It is critical to develop probes for rapid, selective, and sensitive detection of the highly toxic hydrazine in both environmental and biological science. In this work, under mild condition, a novel colorimetric and off-on fluorescent probe was synthesized for rapid recognition of hydrazine with excellent selectivity over other various species including some biological species, metal ions and anions. The limit of quantification (LOQ) value was 1.5 × 10- 4 M-3.2 × 10- 3 M (colorimetric method) and 1.5 × 10- 4 M - 3.2 × 10- 3 M (fluorescent method) with as low as detection limit of 46.2 μM.

High-throughput detection and screening of plants modified by gene editing using quantitative real-time polymerase chain reaction.

PubMed

Peng, Cheng; Wang, Hua; Xu, Xiaoli; Wang, Xiaofu; Chen, Xiaoyun; Wei, Wei; Lai, Yongmin; Liu, Guoquan; Godwin, Ian Douglas; Li, Jieqin; Zhang, Ling; Xu, Junfeng

2018-05-15

Gene editing techniques are becoming powerful tools for modifying target genes in organisms. Although several methods have been developed to detect gene-edited organisms, these techniques are time and labour intensive. Meanwhile, few studies have investigated high-throughput detection and screening strategies for plants modified by gene editing. In this study, we developed a simple, sensitive and high-throughput quantitative real-time (qPCR)-based method. The qPCR-based method exploits two differently labelled probes that are placed within one amplicon at the gene editing target site to simultaneously detect the wild-type and a gene-edited mutant. We showed that the qPCR-based method can accurately distinguish CRISPR/Cas9-induced mutants from the wild-type in several different plant species, such as Oryza sativa, Arabidopsis thaliana, Sorghum bicolor, and Zea mays. Moreover, the method can subsequently determine the mutation type by direct sequencing of the qPCR products of mutations due to gene editing. The qPCR-based method is also sufficiently sensitive to distinguish between heterozygous and homozygous mutations in T 0 transgenic plants. In a 384-well plate format, the method enabled the simultaneous analysis of up to 128 samples in three replicates without handling the post-polymerase chain reaction (PCR) products. Thus, we propose that our method is an ideal choice for screening plants modified by gene editing from many candidates in T 0 transgenic plants, which will be widely used in the area of plant gene editing. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Supervised machine learning on a network scale: application to seismic event classification and detection

NASA Astrophysics Data System (ADS)

Reynen, Andrew; Audet, Pascal

2017-09-01

A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Rosen, Mark; Madabhushi, Anant

2008-03-01

Current techniques for localization of prostatic adenocarcinoma (CaP) via blinded trans-rectal ultrasound biopsy are associated with a high false negative detection rate. While high resolution endorectal in vivo Magnetic Resonance (MR) prostate imaging has been shown to have improved contrast and resolution for CaP detection over ultrasound, similarity in intensity characteristics between benign and cancerous regions on MR images contribute to a high false positive detection rate. In this paper, we present a novel unsupervised segmentation method that employs manifold learning via consensus schemes for detection of cancerous regions from high resolution 1.5 Tesla (T) endorectal in vivo prostate MRI. A significant contribution of this paper is a method to combine multiple weak, lower-dimensional representations of high dimensional feature data in a way analogous to classifier ensemble schemes, and hence create a stable and accurate reduced dimensional representation. After correcting for MR image intensity artifacts, such as bias field inhomogeneity and intensity non-standardness, our algorithm extracts over 350 3D texture features at every spatial location in the MR scene at multiple scales and orientations. Non-linear dimensionality reduction schemes such as Locally Linear Embedding (LLE) and Graph Embedding (GE) are employed to create multiple low dimensional data representations of this high dimensional texture feature space. Our novel consensus embedding method is used to average object adjacencies from within the multiple low dimensional projections so that class relationships are preserved. Unsupervised consensus clustering is then used to partition the objects in this consensus embedding space into distinct classes. Quantitative evaluation on 18 1.5 T prostate MR data against corresponding histology obtained from the multi-site ACRIN trials show a sensitivity of 92.65% and a specificity of 82.06%, which suggests that our method is successfully able to detect suspicious regions in the prostate.

a Probabilistic Embedding Clustering Method for Urban Structure Detection

NASA Astrophysics Data System (ADS)

Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

2017-09-01

Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

A novel alignment-free method for detection of lateral genetic transfer based on TF-IDF.

PubMed

Cong, Yingnan; Chan, Yao-Ban; Ragan, Mark A

2016-07-25

Lateral genetic transfer (LGT) plays an important role in the evolution of microbes. Existing computational methods for detecting genomic regions of putative lateral origin scale poorly to large data. Here, we propose a novel method based on TF-IDF (Term Frequency-Inverse Document Frequency) statistics to detect not only regions of lateral origin, but also their origin and direction of transfer, in sets of hierarchically structured nucleotide or protein sequences. This approach is based on the frequency distributions of k-mers in the sequences. If a set of contiguous k-mers appears sufficiently more frequently in another phyletic group than in its own, we infer that they have been transferred from the first group to the second. We performed rigorous tests of TF-IDF using simulated and empirical datasets. With the simulated data, we tested our method under different parameter settings for sequence length, substitution rate between and within groups and post-LGT, deletion rate, length of transferred region and k size, and found that we can detect LGT events with high precision and recall. Our method performs better than an established method, ALFY, which has high recall but low precision. Our method is efficient, with runtime increasing approximately linearly with sequence length.

An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

PubMed

Lu, Alex Xijie; Moses, Alan M

2016-01-01

Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

Detection of food intake from swallowing sequences by supervised and unsupervised methods.

PubMed

Lopez-Meyer, Paulo; Makeyev, Oleksandr; Schuckers, Stephanie; Melanson, Edward L; Neuman, Michael R; Sazonov, Edward

2010-08-01

Studies of food intake and ingestive behavior in free-living conditions most often rely on self-reporting-based methods that can be highly inaccurate. Methods of Monitoring of Ingestive Behavior (MIB) rely on objective measures derived from chewing and swallowing sequences and thus can be used for unbiased study of food intake with free-living conditions. Our previous study demonstrated accurate detection of food intake in simple models relying on observation of both chewing and swallowing. This article investigates methods that achieve comparable accuracy of food intake detection using only the time series of swallows and thus eliminating the need for the chewing sensor. The classification is performed for each individual swallow rather than for previously used time slices and thus will lead to higher accuracy in mass prediction models relying on counts of swallows. Performance of a group model based on a supervised method (SVM) is compared to performance of individual models based on an unsupervised method (K-means) with results indicating better performance of the unsupervised, self-adapting method. Overall, the results demonstrate that highly accurate detection of intake of foods with substantially different physical properties is possible by an unsupervised system that relies on the information provided by the swallowing alone.

Detection of Food Intake from Swallowing Sequences by Supervised and Unsupervised Methods

PubMed Central

Lopez-Meyer, Paulo; Makeyev, Oleksandr; Schuckers, Stephanie; Melanson, Edward L.; Neuman, Michael R.; Sazonov, Edward

2010-01-01

Studies of food intake and ingestive behavior in free-living conditions most often rely on self-reporting-based methods that can be highly inaccurate. Methods of Monitoring of Ingestive Behavior (MIB) rely on objective measures derived from chewing and swallowing sequences and thus can be used for unbiased study of food intake with free-living conditions. Our previous study demonstrated accurate detection of food intake in simple models relying on observation of both chewing and swallowing. This article investigates methods that achieve comparable accuracy of food intake detection using only the time series of swallows and thus eliminating the need for the chewing sensor. The classification is performed for each individual swallow rather than for previously used time slices and thus will lead to higher accuracy in mass prediction models relying on counts of swallows. Performance of a group model based on a supervised method (SVM) is compared to performance of individual models based on an unsupervised method (K-means) with results indicating better performance of the unsupervised, self-adapting method. Overall, the results demonstrate that highly accurate detection of intake of foods with substantially different physical properties is possible by an unsupervised system that relies on the information provided by the swallowing alone. PMID:20352335

A new edge detection algorithm based on Canny idea

NASA Astrophysics Data System (ADS)

Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

Rapid and Highly Sensitive Detection of Lead Ions in Drinking Water Based on a Strip Immunosensor

PubMed Central

Kuang, Hua; Xing, Changrui; Hao, Changlong; Liu, Liqiang; Wang, Libing; Xu, Chuanlai

2013-01-01

In this study, we have first developed a rapid and sensitive strip immunosensor based on two heterogeneously-sized gold nanoparticles (Au NPs) probes for the detection of trace lead ions in drinking water. The sensitivity was 4-fold higher than that of the conventional LFA under the optimized conditions. The visual limit of detection (LOD) of the amplified method for qualitative detection lead ions was 2 ng/mL and the LOD for semi-quantitative detection could go down to 0.19 ng/mL using a scanning reader. The method suffered from no interference from other metal ions and could be used to detect trace lead ions in drinking water without sample enrichment. The recovery of the test samples ranged from 96% to 103%. As the detection method could be accomplished within 15 min, this method could be used as a potential tool for preliminary monitoring of lead contamination in drinking water. PMID:23539028

Joint detection and tracking of size-varying infrared targets based on block-wise sparse decomposition

NASA Astrophysics Data System (ADS)

Li, Miao; Lin, Zaiping; Long, Yunli; An, Wei; Zhou, Yiyu

2016-05-01

The high variability of target size makes small target detection in Infrared Search and Track (IRST) a challenging task. A joint detection and tracking method based on block-wise sparse decomposition is proposed to address this problem. For detection, the infrared image is divided into overlapped blocks, and each block is weighted on the local image complexity and target existence probabilities. Target-background decomposition is solved by block-wise inexact augmented Lagrange multipliers. For tracking, label multi-Bernoulli (LMB) tracker tracks multiple targets taking the result of single-frame detection as input, and provides corresponding target existence probabilities for detection. Unlike fixed-size methods, the proposed method can accommodate size-varying targets, due to no special assumption for the size and shape of small targets. Because of exact decomposition, classical target measurements are extended and additional direction information is provided to improve tracking performance. The experimental results show that the proposed method can effectively suppress background clutters, detect and track size-varying targets in infrared images.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

PubMed

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

Repeat-aware modeling and correction of short read errors.

PubMed

Yang, Xiao; Aluru, Srinivas; Dorman, Karin S

2011-02-15

High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content. We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at "http://aluru-sun.ece.iastate.edu/doku.php?id = redeem". We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors for genomes with high repeat content.

Comparison of ultraviolet detection and charged aerosol detection methods for liquid-chromatographic determination of protoescigenin.

PubMed

Filip, Katarzyna; Grynkiewicz, Grzegorz; Gruza, Mariusz; Jatczak, Kamil; Zagrodzki, Bogdan

2014-01-01

Escin, a complex mixture of pentacyclic triterpene saponins obtained from horse chestnut seeds extract (HCSE; Aesculus hippocastanum L.), constitutes a traditional herbal active substance of preparations (drugs) used for a treatment of chronic venous insufficiency and capillary blood vessel leakage. A new approach to exploitation of pharmacological potential of this saponin complex has been recently proposed, in which the β-escin mixture is perceived as a source of a hitherto unavailable raw material, pentacyclic triterpene aglycone-protoescigenin. Although many liquid chromatography methods are described in the literature for saponins determination, analysis of protoescigenin is barely mentioned. In this work, a new ultra-high performance liquid chromatography (UHPLC) method developed for protoescigenin quantification has been described. CAD (charged aerosol detection), as a relatively new detection method based on aerosol charging, has been applied in this method as an alternative to ultraviolet (UV) detection. The influence of individual parameters on CAD response and sensitivity was studied. The detection was performed using CAD and UV (200 nm) simultaneously and the results were compared with reference to linearity, accuracy, precision and limit of detection.

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

NASA Technical Reports Server (NTRS)

Thompson, David R.; Majid, Walid A.; Reed, Colorado J.; Wagstaff, Kiri L.

2011-01-01

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

Evaluation of a combined triple method to detect causative HPV in oral and oropharyngeal squamous cell carcinomas: p16 Immunohistochemistry, Consensus PCR HPV-DNA, and In Situ Hybridization

PubMed Central

2012-01-01

Background Recent emerging evidences identify Human Papillomavirus (HPV) related Head and Neck squamous cell carcinomas (HN-SCCs) as a separate subgroup among Head and Neck Cancers with different epidemiology, histopathological characteristics, therapeutic response to chemo-radiation treatment and clinical outcome. However, there is not a worldwide consensus on the methods to be used in clinical practice. The endpoint of this study was to demonstrate the reliability of a triple method which combines evaluation of: 1. p16 protein expression by immunohistochemistry (p16-IHC); 2. HPV-DNA genotyping by consensus HPV-DNA PCR methods (Consensus PCR); and 3 viral integration into the host by in situ hybridization method (ISH). This triple method has been applied to HN-SCC originated from oral cavity (OSCC) and oropharynx (OPSCC), the two anatomical sites in which high risk (HR) HPVs have been clearly implicated as etiologic factors. Methylation-Specific PCR (MSP) was performed to study inactivation of p16-CDKN2a locus by epigenetic events. Reliability of multiple methods was measured by Kappa statistics. Results All the HN-SCCs confirmed HPV positive by PCR and/or ISH were also p16 positive by IHC, with the latter showing a very high level of sensitivity as single test (100% in both OSCC and OPSCC) but lower specificity level (74% in OSCC and 93% in OPSCC). Concordance analysis between ISH and Consensus PCR showed a faint agreement in OPSCC (κ = 0.38) and a moderate agreement in OSCC (κ = 0.44). Furthermore, the addition of double positive score (ISHpositive and Consensus PCR positive) increased significantly the specificity of HR-HPV detection on formalin-fixed paraffin embedded (FFPE) samples (100% in OSCC and 78.5% in OPSCC), but reduced the sensitivity (33% in OSCC and 60% in OPSCC). The significant reduction of sensitivity by the double method was compensated by a very high sensitivity of p16-IHC detection in the triple approach. Conclusions Although HR-HPVs detection is of utmost importance in clinical settings for the Head and Neck Cancer patients, there is no consensus on which to consider the 'golden standard' among the numerous detection methods available either as single test or combinations. Until recently, quantitative E6 RNA PCR has been considered the 'golden standard' since it was demonstrated to have very high accuracy level and very high statistical significance associated with prognostic parameters. In contrast, quantitative E6 DNA PCR has proven to have very high level of accuracy but lesser prognostic association with clinical outcome than the HPV E6 oncoprotein RNA PCR. However, although it is theoretically possible to perform quantitative PCR detection methods also on FFPE samples, they reach the maximum of accuracy on fresh frozen tissue. Furthermore, worldwide diagnostic laboratories have not all the same ability to analyze simultaneously both FFPE and fresh tissues with these quantitative molecular detection methods. Therefore, in the current clinical practice a p16-IHC test is considered as sufficient for HPV diagnostic in accordance with the recently published Head and Neck Cancer international guidelines. Although p16-IHC may serve as a good prognostic indicator, our study clearly demonstrated that it is not satisfactory when used exclusively as the only HPV detecting method. Adding ISH, although known as less sensitive than PCR-based detection methods, has the advantage to preserve the morphological context of HPV-DNA signals in FFPE samples and, thus increase the overall specificity of p16/Consensus PCR combination tests. PMID:22376902

[Application of automatic photography in Schistosoma japonicum miracidium hatching experiments].

PubMed

Ming-Li, Zhou; Ai-Ling, Cai; Xue-Feng, Wang

2016-05-20

To explore the value of automatic photography in the observation of results of Schistosoma japonicum miracidium hatching experiments. Some fresh S. japonicum eggs were added into cow feces, and the samples of feces were divided into a low infested experimental group and a high infested group (40 samples each group). In addition, there was a negative control group with 40 samples of cow feces without S. japonicum eggs. The conventional nylon bag S. japonicum miracidium hatching experiments were performed. The process was observed with the method of flashlight and magnifying glass combined with automatic video (automatic photography method), and, at the same time, with the naked eye observation method. The results were compared. In the low infested group, the miracidium positive detection rates were 57.5% and 85.0% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 11.723, P < 0.05). In the high infested group, the positive detection rates were 97.5% and 100% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 1.253, P > 0.05). In the two infested groups, the average positive detection rates were 77.5% and 92.5% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 6.894, P < 0.05). The automatic photography can effectively improve the positive detection rate in the S. japonicum miracidium hatching experiments.

Texture based segmentation method to detect atherosclerotic plaque from optical tomography images

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2013-06-01

Optical coherence tomography (OCT) imaging has been widely employed in assessing cardiovascular disease. Atherosclerosis is one of the major cause cardio vascular diseases. However visual detection of atherosclerotic plaque from OCT images is often limited and further complicated by high frame rates. We developed a texture based segmentation method to automatically detect plaque and non plaque regions from OCT images. To verify our results we compared them to photographs of the vascular tissue with atherosclerotic plaque that we used to generate the OCT images. Our results show a close match with photographs of vascular tissue with atherosclerotic plaque. Our texture based segmentation method for plaque detection could be potentially used in clinical cardiovascular OCT imaging for plaque detection.

A NEW METHOD FOR FINDING POINT SOURCES IN HIGH-ENERGY NEUTRINO DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Ke; Miller, M. Coleman

The IceCube collaboration has reported the first detection of high-energy astrophysical neutrinos, including ∼50 high-energy starting events, but no individual sources have been identified. It is therefore important to develop the most sensitive and efficient possible algorithms to identify the point sources of these neutrinos. The most popular current method works by exploring a dense grid of possible directions to individual sources, and identifying the single direction with the maximum probability of having produced multiple detected neutrinos. This method has numerous strengths, but it is computationally intensive and because it focuses on the single best location for a point source,more » additional point sources are not included in the evidence. We propose a new maximum likelihood method that uses the angular separations between all pairs of neutrinos in the data. Unlike existing autocorrelation methods for this type of analysis, which also use angular separations between neutrino pairs, our method incorporates information about the point-spread function and can identify individual point sources. We find that if the angular resolution is a few degrees or better, then this approach reduces both false positive and false negative errors compared to the current method, and is also more computationally efficient up to, potentially, hundreds of thousands of detected neutrinos.« less

Validation of High Resolution Melting Analysis (HRM) of the Amplified ITS2 Region for the Detection and Identification of Yeasts from Clinical Samples: Comparison with Culture and MALDI-TOF Based Identification.

PubMed

Duyvejonck, Hans; Cools, Piet; Decruyenaere, Johan; Roelens, Kristien; Noens, Lucien; Vermeulen, Stefan; Claeys, Geert; Decat, Ellen; Van Mechelen, Els; Vaneechoutte, Mario

2015-01-01

Candida species are known as opportunistic pathogens, and a possible cause of invasive infections. Because of their species-specific antimycotic resistance patterns, reliable techniques for their detection, quantification and identification are needed. We validated a DNA amplification method for direct detection of Candida spp. from clinical samples, namely the ITS2-High Resolution Melting Analysis (direct method), by comparing it with a culture and MALDI-TOF Mass Spectrometry based method (indirect method) to establish the presence of Candida species in three different types of clinical samples. A total of 347 clinical samples, i.e. throat swabs, rectal swabs and vaginal swabs, were collected from the gynaecology/obstetrics, intensive care and haematology wards at the Ghent University Hospital, Belgium. For the direct method, ITS2-HRM was preceded by NucliSENS easyMAG DNA extraction, directly on the clinical samples. For the indirect method, clinical samples were cultured on Candida ID and individual colonies were identified by MALDI-TOF. For 83.9% of the samples there was complete concordance between both techniques, i.e. the same Candida species were detected in 31.1% of the samples or no Candida species were detected in 52.8% of the samples. In 16.1% of the clinical samples, discrepant results were obtained, of which only 6.01% were considered as major discrepancies. Discrepancies occurred mostly when overall numbers of Candida cells in the samples were low and/or when multiple species were present in the sample. Most of the discrepancies could be decided in the advantage of the direct method. This is due to samples in which no yeast could be cultured whereas low amounts could be detected by the direct method and to samples in which high quantities of Candida robusta according to ITS2-HRM were missed by culture on Candida ID agar. It remains to be decided whether the diagnostic advantages of the direct method compensate for its disadvantages.

High throughput detection of antibody self-interaction by bio-layer interferometry.

PubMed

Sun, Tingwan; Reid, Felicia; Liu, Yuqi; Cao, Yuan; Estep, Patricia; Nauman, Claire; Xu, Yingda

2013-01-01

Self-interaction of an antibody may lead to aggregation, low solubility or high viscosity. Rapid identification of highly developable leads remains challenging, even though progress has been made with the introduction of techniques such as self-interaction chromatography (SIC) and cross-interaction chromatography (CIC). Here, we report a high throughput method to detect antibody clone self-interaction (CSI) using bio-layer interferometry (BLI) technology. Antibodies with strong self-interaction responses in the CSI-BLI assay also show delayed retention times in SIC and CIC. This method allows hundreds of candidates to be screened in a matter of hours with minimal material consumption.

Mean grain size detection of DP590 steel plate using a corrected method with electromagnetic acoustic resonance.

PubMed

Wang, Bin; Wang, Xiaokai; Hua, Lin; Li, Juanjuan; Xiang, Qing

2017-04-01

Electromagnetic acoustic resonance (EMAR) is a considerable method to determine the mean grain size of the metal material with a high precision. The basic ultrasonic attenuation theory used for the mean grain size detection of EMAR is come from the single phase theory. In this paper, the EMAR testing was carried out based on the ultrasonic attenuation theory. The detection results show that the double peaks phenomenon occurs in the EMAR testing of DP590 steel plate. The dual phase structure of DP590 steel is the inducement of the double peaks phenomenon in the EMAR testing. In reaction to the phenomenon, a corrected method with EMAR was put forward to detect the mean grain size of dual phase steel. Compared with the traditional attenuation evaluation method and the uncorrected method with EMAR, the corrected method with EMAR shows great effectiveness and superiority for the mean grain size detection of DP590 steel plate. Copyright © 2016. Published by Elsevier B.V.

Development of high performance liquid chromatography method for miconazole analysis in powder sample

NASA Astrophysics Data System (ADS)

Hermawan, D.; Suwandri; Sulaeman, U.; Istiqomah, A.; Aboul-Enein, H. Y.

2017-02-01

A simple high performance liquid chromatography (HPLC) method has been developed in this study for the analysis of miconazole, an antifungal drug, in powder sample. The optimized HPLC system using C8 column was achieved using mobile phase composition containing methanol:water (85:15, v/v), a flow rate of 0.8 mL/min, and UV detection at 220 nm. The calibration graph was linear in the range from 10 to 50 mg/L with r 2 of 0.9983. The limit of detection (LOD) and limit of quantitation (LOQ) obtained were 2.24 mg/L and 7.47 mg/L, respectively. The present HPLC method is applicable for the determination of miconazole in the powder sample with a recovery of 101.28 % (RSD = 0.96%, n = 3). The developed HPLC method provides short analysis time, high reproducibility and high sensitivity.

Efficient subtle motion detection from high-speed video for sound recovery and vibration analysis using singular value decomposition-based approach

NASA Astrophysics Data System (ADS)

Zhang, Dashan; Guo, Jie; Jin, Yi; Zhu, Chang'an

2017-09-01

High-speed cameras provide full field measurement of structure motions and have been applied in nondestructive testing and noncontact structure monitoring. Recently, a phase-based method has been proposed to extract sound-induced vibrations from phase variations in videos, and this method provides insights into the study of remote sound surveillance and material analysis. An efficient singular value decomposition (SVD)-based approach is introduced to detect sound-induced subtle motions from pixel intensities in silent high-speed videos. A high-speed camera is initially applied to capture a video of the vibrating objects stimulated by sound fluctuations. Then, subimages collected from a small region on the captured video are reshaped into vectors and reconstructed to form a matrix. Orthonormal image bases (OIBs) are obtained from the SVD of the matrix; available vibration signal can then be obtained by projecting subsequent subimages onto specific OIBs. A simulation test is initiated to validate the effectiveness and efficiency of the proposed method. Two experiments are conducted to demonstrate the potential applications in sound recovery and material analysis. Results show that the proposed method efficiently detects subtle motions from the video.

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

Development of an in situ magnetic beads based RT-PCR method for electrochemiluminescent detection of rotavirus

NASA Astrophysics Data System (ADS)

Zhan, Fangfang; Zhou, Xiaoming

2012-12-01

Rotaviruses are double-stranded RNA viruses belonging to the family of enteric pathogens. It is a major cause of diarrhoeal disease in infants and young children worldwide. Consequently, rapid and accurate detection of rotaviruses is of great importance in controlling and preventing food- and waterborne diseases and outbreaks. Reverse transcription-polymerase chain reaction (RT-PCR) is a reliable method that possesses high specificity and sensitivity. It has been widely used to detection of viruses. Electrochemiluminescence (ECL) can be considered as an important and powerful tool in analytical and clinical application with high sensitivity, excellent specificity, and low cost. Here we have developed a method for the detection of rotavirus by combining in situ magnetic beads (MBs) based RT-PCR with ECL. RT of rotavirus RNA was carried out in a traditional way and the resulting cDNA was directly amplified on MBs. Forward primers were covalently bounded to MBs and reverse primers were labeled with tris-(2, 2'-bipyridyl) ruthenium (TBR). During the PCR cycling, the TBR labeled products were directly loaded and enriched on the surface of MBs. Then the MBs-TBR complexes could be analyzed by a magnetic ECL platform without any post-modification or post-incubation which avoid some laborious manual operations and achieve rapid yet sensitive detection. In this study, rotavirus from fecal specimens was successfully detected within 2 h, and the limit of detection was estimated to be 104copies/μL. This novel in situ MBs based RT-PCR with ECL detection method can be used for pathogen detection in food safety field and clinical diagnosis.

Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression studies

PubMed Central

Nilsson, Björn; Håkansson, Petra; Johansson, Mikael; Nelander, Sven; Fioretos, Thoas

2007-01-01

Ontological analysis facilitates the interpretation of microarray data. Here we describe new ontological analysis methods which, unlike existing approaches, are threshold-free and statistically powerful. We perform extensive evaluations and introduce a new concept, detection spectra, to characterize methods. We show that different ontological analysis methods exhibit distinct detection spectra, and that it is critical to account for this diversity. Our results argue strongly against the continued use of existing methods, and provide directions towards an enhanced approach. PMID:17488501

Varying face occlusion detection and iterative recovery for face recognition

NASA Astrophysics Data System (ADS)

Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

2017-05-01

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Nosema ceranae detection by microscopy and antibody tests

USDA-ARS?s Scientific Manuscript database

N. ceranae is now present in a high proportion of American honey bee hives. It has been implicated in colony mortality, especially in conjunction with parasites and other pathogens. PCR is the method of choice to detect light infections and to distinguish between species. It is highly sensitive a...

A novel sulfate-reducing bacteria detection method based on inhibition of cysteine protease activity.

PubMed

Qi, Peng; Zhang, Dun; Wan, Yi

2014-11-01

Sulfate-reducing bacteria (SRB) have been extensively studied in corrosion and environmental science. However, fast enumeration of SRB population is still a difficult task. This work presents a novel specific SRB detection method based on inhibition of cysteine protease activity. The hydrolytic activity of cysteine protease was inhibited by taking advantage of sulfide, the characteristic metabolic product of SRB, to attack active cysteine thiol group in cysteine protease catalytic sites. The active thiol S-sulfhydration process could be used for SRB detection, since the amount of sulfide accumulated in culture medium was highly related with initial bacterial concentration. The working conditions of cysteine protease have been optimized to obtain better detection capability, and the SRB detection performances have been evaluated in this work. The proposed SRB detection method based on inhibition of cysteine protease activity avoided the use of biological recognition elements. In addition, compared with the widely used most probable number (MPN) method which would take up to at least 15days to accomplish whole detection process, the method based on inhibition of papain activity could detect SRB in 2 days, with a detection limit of 5.21×10(2) cfu mL(-1). The detection time for SRB population quantitative analysis was greatly shortened. Copyright © 2014 Elsevier B.V. All rights reserved.

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

High prevalence of Salmonella spp. in wastewater reused for irrigation assessed by molecular methods.

PubMed

Santiago, Paula; Jiménez-Belenguer, Ana; García-Hernández, Jorge; Estellés, Rosa Montes; Hernández Pérez, Manuel; Castillo López, M Angeles; Ferrús, María Antonia; Moreno, Yolanda

2018-01-01

Salmonella spp. is one of the most important causal agents of food-borne illness in developed countries and its presence in irrigation water poses a risk to public health. Its detection in environmental samples is not easy when culture methods are used, and molecular techniques such as PCR or ribosomal rRNA probe hybridization (Fluorescent in situ Hybridization, FISH) are outstanding alternatives. The aim of this work was to determine the environmental risk due to the presence of Salmonella spp. in wastewater by culture, PCR and FISH. A new specific rDNA probe for Salmonella was designed and its efficiency was compared with the rest of methods Serotype and antibiotic resistance of isolated strains were determined. Forty-five wastewater samples (collected from two secondary wastewater treatment plants) were analysed. Salmonella strains were isolated in 24 wastewater samples (53%), two of them after disinfection treatment. Twenty-three Salmonella strains exhibited resistance to one or more antimicrobial agent. Analysis of wastewater samples yielded PCR positive results for Salmonella in 28 out of the 45 wastewater samples (62%). FISH analysis allowed for the detection of Salmonella in 27 (60%) samples. By using molecular methods, Salmonella was detected in four samples after disinfection treatment. These results show the prevalence of Salmonella in reclaimed wastewater even after U.V. disinfection, what is a matter of public health concern, the high rates of resistance to antibiotics and the adequacy of molecular methods for its rapid detection. FISH method, with SA23 probe developed and assayed in this work provides a tool for detecting Salmonella in water within few hours, with a high rate of effectiveness. Copyright © 2017 Elsevier GmbH. All rights reserved.

The development of technology for detection of marijuana intoxication by analysis of body fluids

DOT National Transportation Integrated Search

1975-09-01

A method employing high pressure liquid chromatography plus mass spectrometry was developed for the detection of low concentrations of various marijuana metabolites in body fluids. A new marijuana metabolite was found which could be detected in blood...

Improving surface EMG burst detection in infrahyoid muscles during swallowing using digital filters and discrete wavelet analysis.

PubMed

Restrepo-Agudelo, Sebastian; Roldan-Vasco, Sebastian; Ramirez-Arbelaez, Lina; Cadavid-Arboleda, Santiago; Perez-Giraldo, Estefania; Orozco-Duque, Andres

2017-08-01

The visual inspection is a widely used method for evaluating the surface electromyographic signal (sEMG) during deglutition, a process highly dependent of the examiners expertise. It is desirable to have a less subjective and automated technique to improve the onset detection in swallowing related muscles, which have a low signal-to-noise ratio. In this work, we acquired sEMG measured in infrahyoid muscles with high baseline noise of ten healthy adults during water swallowing tasks. Two methods were applied to find the combination of cutoff frequencies that achieve the most accurate onset detection: discrete wavelet decomposition based method and fixed steps variations of low and high cutoff frequencies of a digital bandpass filter. Teager-Kaiser Energy operator, root mean square and simple threshold method were applied for both techniques. Results show a narrowing of the effective bandwidth vs. the literature recommended parameters for sEMG acquisition. Both level 3 decomposition with mother wavelet db4 and bandpass filter with cutoff frequencies between 130 and 180Hz were optimal for onset detection in infrahyoid muscles. The proposed methodologies recognized the onset time with predictive power above 0.95, that is similar to previous findings but in larger and more superficial muscles in limbs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiplexed transcriptome analysis to detect ALK, ROS1 and RET rearrangements in lung cancer

PubMed Central

Rogers, Toni-Maree; Arnau, Gisela Mir; Ryland, Georgina L.; Huang, Stephen; Lira, Maruja E.; Emmanuel, Yvette; Perez, Omar D.; Irwin, Darryl; Fellowes, Andrew P.; Wong, Stephen Q.; Fox, Stephen B.

2017-01-01

ALK, ROS1 and RET gene fusions are important predictive biomarkers for tyrosine kinase inhibitors in lung cancer. Currently, the gold standard method for gene fusion detection is Fluorescence In Situ Hybridization (FISH) and while highly sensitive and specific, it is also labour intensive, subjective in analysis, and unable to screen a large numbers of gene fusions. Recent developments in high-throughput transcriptome-based methods may provide a suitable alternative to FISH as they are compatible with multiplexing and diagnostic workflows. However, the concordance between these different methods compared with FISH has not been evaluated. In this study we compared the results from three transcriptome-based platforms (Nanostring Elements, Agena LungFusion panel and ThermoFisher NGS fusion panel) to those obtained from ALK, ROS1 and RET FISH on 51 clinical specimens. Overall agreement of results ranged from 86–96% depending on the platform used. While all platforms were highly sensitive, both the Agena panel and Thermo Fisher NGS fusion panel reported minor fusions that were not detectable by FISH. Our proof–of–principle study illustrates that transcriptome-based analyses are sensitive and robust methods for detecting actionable gene fusions in lung cancer and could provide a robust alternative to FISH testing in the diagnostic setting. PMID:28181564

Artificial Neural Network for Probabilistic Feature Recognition in Liquid Chromatography Coupled to High-Resolution Mass Spectrometry.

PubMed

Woldegebriel, Michael; Derks, Eduard

2017-01-17

In this work, a novel probabilistic untargeted feature detection algorithm for liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) using artificial neural network (ANN) is presented. The feature detection process is approached as a pattern recognition problem, and thus, ANN was utilized as an efficient feature recognition tool. Unlike most existing feature detection algorithms, with this approach, any suspected chromatographic profile (i.e., shape of a peak) can easily be incorporated by training the network, avoiding the need to perform computationally expensive regression methods with specific mathematical models. In addition, with this method, we have shown that the high-resolution raw data can be fully utilized without applying any arbitrary thresholds or data reduction, therefore improving the sensitivity of the method for compound identification purposes. Furthermore, opposed to existing deterministic (binary) approaches, this method rather estimates the probability of a feature being present/absent at a given point of interest, thus giving chance for all data points to be propagated down the data analysis pipeline, weighed with their probability. The algorithm was tested with data sets generated from spiked samples in forensic and food safety context and has shown promising results by detecting features for all compounds in a computationally reasonable time.

Salmonella detection from chicken rinsate with surface enhanced Raman spectroscopy and RT-PCR validation

USDA-ARS?s Scientific Manuscript database

Optical detection of bacteria has been approached in recent years as a bacteria detection method that can counter time restraints of traditional plating or the high reoccurring cost of real-time polymerase chain reaction (RT-PCR). The goal of optical detection is to identify bacteria with spectral s...

High-sensitivity assay for monitoring ESR1 mutations in circulating cell-free DNA of breast cancer patients receiving endocrine therapy.

PubMed

Lupini, Laura; Moretti, Anna; Bassi, Cristian; Schirone, Alessio; Pedriali, Massimo; Querzoli, Patrizia; Roncarati, Roberta; Frassoldati, Antonio; Negrini, Massimo

2018-03-12

Approximately 70% of breast cancers (BCs) express estrogen receptor alpha (ERα) and are treated with endocrine therapy. However, the effectiveness of this therapy is limited by innate or acquired resistance in approximately one-third of patients. Activating mutations in the ESR1 gene that encodes ERα promote critical resistance mechanisms. Here, we developed a high sensitivity approach based on enhanced-ice-COLD-PCR for detecting ESR1 mutations. The method produced an enrichment up to 100-fold and allowed the unambiguous detection of ESR1 mutations even when they consisted of only 0.01% of the total ESR1 allelic fraction. After COLD-PCR enrichment, methods based on next-generation sequencing or droplet-digital PCR were employed to detect and quantify ESR1 mutations. We applied the method to detect ESR1 mutations in circulating free DNA from the plasma of 56 patients with metastatic ER-positive BC. Fifteen of these patients were found to have ESR1 mutations at codons 536-538. This study demonstrates the utility of the enhanced-ice-COLD-PCR approach for simplifying and improving the detection of ESR1 tumor mutations in liquid biopsies. Because of its high sensitivity, the approach may potentially be applicable to patients with non-metastatic disease.

Optical detection of metastatic cancer cells using a scanned laser pico-projection system

NASA Astrophysics Data System (ADS)

Huang, Chih-Ling; Chiu, Wen-Tai; Lo, Yu-Lung; Chuang, Chin-Ho; Chen, Yu-Bin; Chang, Shu-Jing; Ke, Tung-Ting; Cheng, Hung-Chi; Wu, Hua-Lin

2015-03-01

Metastasis is responsible for 90% of all cancer-related deaths in humans. As a result, reliable techniques for detecting metastatic cells are urgently required. Although various techniques have been proposed for metastasis detection, they are generally capable of detecting metastatic cells only once migration has already occurred. Accordingly, the present study proposes an optical method for physical characterization of metastatic cancer cells using a scanned laser pico-projection system (SLPP). The validity of the proposed method is demonstrated using five pairs of cancer cell lines and two pairs of non-cancer cell lines treated by IPTG induction in order to mimic normal cells with an overexpression of oncogene. The results show that for all of the considered cell lines, the SLPP speckle contrast of the high-metastatic cells is significantly higher than that of the low-metastatic cells. As a result, the speckle contrast measurement provides a reliable means of distinguishing quantitatively between low- and high-metastatic cells of the same origin. Compared to existing metastasis detection methods, the proposed SLPP approach has many advantages, including a higher throughput, a lower cost, a larger sample size and a more reliable diagnostic performance. As a result, it provides a highly promising solution for physical characterization of metastatic cancer cells in vitro.

Label-free detection of circulating melanoma cells by in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Xiaoling; Yang, Ping; Liu, Rongrong; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2016-03-01

Melanoma is a malignant tumor of melanocytes. Melanoma cells have high light absorption due to melanin highly contained in melanoma cells. This property is employed for the detection of circulating melanoma cell by in vivo photoacoustic flow cytometry (PAFC), which is based on photoacoustic effect. Compared to in vivo flow cytometry based on fluorescence, PAFC can employ high melanin content of melanoma cells as endogenous biomarkers to detect circulating melanoma cells in vivo. We have developed in vitro experiments to prove the ability of PAFC system of detecting photoacoustic signals from melanoma cells. For in vivo experiments, we have constructed a model of melanoma tumor bearing mice by inoculating highly metastatic murine melanoma cancer cells, B16F10 with subcutaneous injection. PA signals are detected in the blood vessels of mouse ears in vivo. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The processing methods have a great potential for analyzing signals accurately and rapidly. By counting circulating melanoma cells termly, we obtain the number variation of circulating melanoma cells as melanoma metastasized. Those results show that PAFC is a noninvasive and label-free method to detect melanoma metastases in blood or lymph circulation.

Nonlinear multi-photon laser wave-mixing optical detection in microarrays and microchips for ultrasensitive detection and separation of biomarkers for cancer and neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Iwabuchi, Manna; Hetu, Marcel; Maxwell, Eric; Pradel, Jean S.; Ramos, Sashary; Tong, William G.

2015-09-01

Multi-photon degenerate four-wave mixing is demonstrated as an ultrasensitive absorption-based optical method for detection, separation and identification of biomarker proteins in the development of early diagnostic methods for HIV- 1, cancer and neurodegenerative diseases using compact, portable microarrays and capillary- or microchip-based chemical separation systems that offer high chemical specificity levels. The wave-mixing signal has a quadratic dependence on concentration, and hence, it allows more reliable monitoring of smaller changes in analyte properties. Our wave-mixing detection sensitivity is comparable or better than those of current methods including enzyme-linked immunoassay for clinical diagnostic and screening. Detection sensitivity is excellent since the wave-mixing signal is a coherent laser-like beam that can be collected with virtually 100% collection efficiency with high S/N. Our analysis time is short (1-15 minutes) for molecular weight-based protein separation as compared to that of a conventional separation technique, e.g., sodium dodecyl sulfate-polyacrylamide gel electrophoresis. When ultrasensitive wavemixing detection is paired with high-resolution capillary- or microchip-based separation systems, biomarkers can be separated and identified at the zepto- and yocto-mole levels for a wide range of analytes. Specific analytes can be captured in a microchannel through the use of antibody-antigen interactions that provide better chemical specificity as compared to size-based separation alone. The technique can also be combined with immune-precipitation and a multichannel capillary array for high-throughput analysis of more complex protein samples. Wave mixing allows the use of chromophores and absorption-modifying tags, in addition to conventional fluorophores, for online detection of immunecomplexes related to cancer.

Highly sensitive surface-scanning detector for the direct bacterial detection using magnetoelastic (ME) biosensors

NASA Astrophysics Data System (ADS)

Liu, Yuzhe; Horikawa, Shin; Chen, I.-Hsuan; Du, Songtao; Wikle, Howard C.; Suh, Sang-Jin; Chin, Bryan A.

2017-05-01

This paper demonstrates a highly sensitive surface-scanning detector used for magnetoelastic (ME) biosensors for the detection of Salmonella on the surface of a polyethylene (PE) food preparation surface. The design and fabrication methods of the new planar spiral coil are introduced. Different concentrations of Salmonella were measured on the surface of a PE board. The efficacy of Salmonella capture and detection is discussed.

A sensitive and efficient method for determination of N-acetylhexosamines and N-acetylneuraminic acid in breast milk and milk-based products by high-performance liquid chromatography via UV detection and mass spectrometry identification.

PubMed

Chuanxiang, Wu; Lian, Xia; Lijie, Liu; Fengli, Qu; Zhiwei, Sun; Xianen, Zhao; Jinmao, You

2016-02-01

A sensitive and efficient method of high performance liquid chromatography using 1-(2-naphthyl)-3-methyl-5-pyrazolone (NMP) as pre-column derivatization reagent coupled with UV detection (HPLC-UV) and online mass spectrometry identification was established for determination of the most common N-Acetylhexosamines (N-acetyl-d-glucosamine (GlcNAc) and N-acetyl-d-galactosamine (GalNAc)) and N-acetylneuraminic acid (Neu5Ac). In order to obtain the highest liberation level of the three monosaccharides without destruction of Neu5Ac or conversion of GlcNAc/GalNAc to GlcN/GalN in the hydrolysis procedure, the pivotal parameters affecting the liberation of N-acetylhexosamines/Neu5Ac from sample were investigated with response surface methodology (RSM). Under the optimized condition, maximum yield was obtained. The effects of key parameters on derivatization, separation and detection were also investigated. At optimized conditions, three monosaccharides were labeled fast and entirely, and all derivatives exhibited a good baseline resolution and high detection sensitivity. The developed method was linear over the calibration range 0.25-12μM, with R(2)>0.9991. The detection limits of the method were between 0.48 and 2.01pmol. Intra- and inter-day precisions for the three monosaccharides (GlcNAc, GalNAc and Neu5Ac) were found to be in the range of 3.07-4.02% and 3.69-4.67%, respectively. Individual monosaccharide recovery from spiked milk was in the range of 81%-97%. The sensitivity of the method, the facility of the derivatization procedure and the reliability of the hydrolysis conditions suggest the proposed method has a high potential for utilization in routine trace N-acetylhexosamines and Neu5Ac analysis in biological samples. Copyright © 2015 Elsevier B.V. All rights reserved.

A Wavelet-based Fast Discrimination of Transformer Magnetizing Inrush Current

NASA Astrophysics Data System (ADS)

Kitayama, Masashi

Recently customers who need electricity of higher quality have been installing co-generation facilities. They can avoid voltage sags and other distribution system related disturbances by supplying electricity to important load from their generators. For another example, FRIENDS, highly reliable distribution system using semiconductor switches or storage devices based on power electronics technology, is proposed. These examples illustrates that the request for high reliability in distribution system is increasing. In order to realize these systems, fast relaying algorithms are indispensable. The author proposes a new method of detecting magnetizing inrush current using discrete wavelet transform (DWT). DWT provides the function of detecting discontinuity of current waveform. Inrush current occurs when transformer core becomes saturated. The proposed method detects spikes of DWT components derived from the discontinuity of the current waveform at both the beginning and the end of inrush current. Wavelet thresholding, one of the wavelet-based statistical modeling, was applied to detect the DWT component spikes. The proposed method is verified using experimental data using single-phase transformer and the proposed method is proved to be effective.

Analysis of glycosaminoglycan-derived disaccharides by capillary electrophoresis using laser-induced fluorescence detection

PubMed Central

Chang, Yuqing; Yang, Bo; Zhao, Xue; Linhardt, Robert J.

2012-01-01

A quantitative and highly sensitive method for the analysis of glycosaminoglycan (GAG)-derived disaccharides is presented that relies on capillary electrophoresis (CE) with laser-induced fluorescence (LIF) detection. This method enables complete separation of seventeen GAG-derived disaccharides in a single run. Unsaturated disaccharides were derivatized with 2-aminoacridone (AMAC) to improve sensitivity. The limit of detection was at the attomole level and about 100-fold more sensitive than traditional CE-ultraviolet detection. A CE separation timetable was developed to achieve complete resolution and shorten analysis time. The RSD of migration time and peak areas at both low and high concentrations of unsaturated disaccharides are all less than 2.7% and 3.2%, respectively, demonstrating that this is a reproducible method. This analysis was successfully applied to cultured Chinese hamster ovary cell samples for determination of GAG disaccharides. The current method simplifies GAG extraction steps, and reduces inaccuracy in calculating ratios of heparin/heparan sulfate to chondroitin sulfate/dermatan sulfate, resulting from the separate analyses of a single sample. PMID:22609076

A simple method of DNA isolation from jute (Corchorus olitorius) seed suitable for PCR-based detection of the pathogen Macrophomina phaseolina (Tassi) Goid.

PubMed

Biswas, C; Dey, P; Satpathy, S; Sarkar, S K; Bera, A; Mahapatra, B S

2013-02-01

A simple method was developed for isolating DNA from jute seed, which contains high amounts of mucilage and secondary metabolites, and a PCR protocol was standardized for detecting the seedborne pathogen Macrophomina phaseolina. The cetyl trimethyl ammonium bromide method was modified with increased salt concentration and a simple sodium acetate treatment to extract genomic as well as fungal DNA directly from infected jute seed. The Miniprep was evaluated along with five other methods of DNA isolation in terms of yield and quality of DNA and number of PCR positive samples. The Miniprep consistently recovered high amounts of DNA with good spectral qualities at A260/A280. The DNA isolated from jute seed was found suitable for PCR amplification. Macrophomina phaseolina could be detected by PCR from artificially inoculated as well as naturally infected jute seeds. The limit of PCR-based detection of M. phaseolina in jute seed was determined to be 0·62 × 10(-7) CFU g(-1) seed. © 2012 The Society for Applied Microbiology.

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

High-Resolution Metabolomics Assessment of Military Personnel: Evaluating Analytical Strategies for Chemical Detection.

PubMed

Liu, Ken H; Walker, Douglas I; Uppal, Karan; Tran, ViLinh; Rohrbeck, Patricia; Mallon, Timothy M; Jones, Dean P

2016-08-01

The aim of this study was to maximize detection of serum metabolites with high-resolution metabolomics (HRM). Department of Defense Serum Repository (DoDSR) samples were analyzed using ultrahigh resolution mass spectrometry with three complementary chromatographic phases and four ionization modes. Chemical coverage was evaluated by number of ions detected and accurate mass matches to a human metabolomics database. Individual HRM platforms provided accurate mass matches for up to 58% of the KEGG metabolite database. Combining two analytical methods increased matches to 72% and included metabolites in most major human metabolic pathways and chemical classes. Detection and feature quality varied by analytical configuration. Dual chromatography HRM with positive and negative electrospray ionization provides an effective generalized method for metabolic assessment of military personnel.

State Recognition of High Voltage Isolation Switch Based on Background Difference and Iterative Search

NASA Astrophysics Data System (ADS)

Xu, Jiayuan; Yu, Chengtao; Bo, Bin; Xue, Yu; Xu, Changfu; Chaminda, P. R. Dushantha; Hu, Chengbo; Peng, Kai

2018-03-01

The automatic recognition of the high voltage isolation switch by remote video monitoring is an effective means to ensure the safety of the personnel and the equipment. The existing methods mainly include two ways: improving monitoring accuracy and adopting target detection technology through equipment transformation. Such a method is often applied to specific scenarios, with limited application scope and high cost. To solve this problem, a high voltage isolation switch state recognition method based on background difference and iterative search is proposed in this paper. The initial position of the switch is detected in real time through the background difference method. When the switch starts to open and close, the target tracking algorithm is used to track the motion trajectory of the switch. The opening and closing state of the switch is determined according to the angle variation of the switch tracking point and the center line. The effectiveness of the method is verified by experiments on different switched video frames of switching states. Compared with the traditional methods, this method is more robust and effective.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

PubMed Central

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

GIS applied to location of fires detection towers in domain area of tropical forest.

PubMed

Eugenio, Fernando Coelho; Rosa Dos Santos, Alexandre; Fiedler, Nilton Cesar; Ribeiro, Guido Assunção; da Silva, Aderbal Gomes; Juvanhol, Ronie Silva; Schettino, Vitor Roberto; Marcatti, Gustavo Eduardo; Domingues, Getúlio Fonseca; Alves Dos Santos, Gleissy Mary Amaral Dino; Pezzopane, José Eduardo Macedo; Pedra, Beatriz Duguy; Banhos, Aureo; Martins, Lima Deleon

2016-08-15

In most countries, the loss of biodiversity caused by the fires is worrying. In this sense, the fires detection towers are crucial for rapid identification of fire outbreaks and can also be used in environmental inspection, biodiversity monitoring, telecommunications mechanisms, telemetry and others. Currently the methodologies for allocating fire detection towers over large areas are numerous, complex and non-standardized by government supervisory agencies. Therefore, this study proposes and evaluates different methodologies to best location of points to install fire detection towers considering the topography, risk areas, conservation units and heat spots. Were used Geographic Information Systems (GIS) techniques and unaligned stratified systematic sampling for implementing and evaluating 9 methods for allocating fire detection towers. Among the methods evaluated, the C3 method was chosen, represented by 140 fire detection towers, with coverage of: a) 67% of the study area, b) 73.97% of the areas with high risk, c) 70.41% of the areas with very high risk, d) 70.42% of the conservation units and e) 84.95% of the heat spots in 2014. The proposed methodology can be adapted to areas of other countries. Copyright © 2016 Elsevier B.V. All rights reserved.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

PubMed

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Detection of Xeljanz enantiomers in diethyl amine active pharmaceutical ingredients and tablets.

PubMed

Wang, Na-Na; Zhang, Dao-Lin; Jiang, Xin-Hui

2015-03-01

A high-performance liquid chromatography (HPLC) method was established to detect Xeljanz enantiomers in active pharmaceutical ingredients (APIs) and tablets. The separation was achieved on a Chiralpak IC column using a mobile phase of hexane-ethanol-diethylamine (65:35:0.1, v/v). The detection wavelength was 289 nm. The peak areas and the enantiomer concentrations in the range of 0.15-2.25 μg•mL(-1) were in high linearity, with correlation coefficients higher than 0.999. The recoveries were 86.44% at the concentrations of 7.5, 18.75, and 37.5 μg•mL(-1) . The limit of detection (LOD) and limit of quantification (LOQ) were 0.042 and 0.14 μg•mL(-1) , respectively. This HPLC method is suitable for detecting the enantiomers of Xeljanz in its APIs and tablets. © 2014 Wiley Periodicals, Inc.

Remote NMR/MRI detection of laser polarized gases

DOEpatents

Pines, Alexander; Saxena, Sunil; Moule, Adam; Spence, Megan; Seeley, Juliette A.; Pierce, Kimberly L.; Han, Song-I; Granwehr, Josef

2006-06-13

An apparatus and method for remote NMR/MRI spectroscopy having an encoding coil with a sample chamber, a supply of signal carriers, preferably hyperpolarized xenon and a detector allowing the spatial and temporal separation of signal preparation and signal detection steps. This separation allows the physical conditions and methods of the encoding and detection steps to be optimized independently. The encoding of the carrier molecules may take place in a high or a low magnetic field and conventional NMR pulse sequences can be split between encoding and detection steps. In one embodiment, the detector is a high magnetic field NMR apparatus. In another embodiment, the detector is a superconducting quantum interference device. A further embodiment uses optical detection of Rb--Xe spin exchange. Another embodiment uses an optical magnetometer using non-linear Faraday rotation. Concentration of the signal carriers in the detector can greatly improve the signal to noise ratio.

Detection and evaluation of weld defects in stainless steel using alternating current field measurement

NASA Astrophysics Data System (ADS)

Wei-Li, Ma, Weiping; Pan-Qi, Wen-jiao, Dou; Yuan, Xin'an; Yin, Xiaokang

2018-04-01

Stainless steel is widely used in nuclear power plants, such as various high-radioactive pool, tools storage and fuel transportation channel, and serves as an important barrier to stop the leakage of high-radioactive material. NonDestructive Evaluation (NDE) methods, eddy current testing (ET), ultrasonic examination (UT), penetration testing (PT) and hybrid detection method, etc., have been introduced into the inspection of a nuclear plant. In this paper, the Alternating Current Field Measurement (ACFM) was fully applied to detect and evaluate the defects in the welds of the stainless steel. Simulations were carried out on different defect types, crack lengths, and orientation to reveal the relationship between the signals and dimensions to determine whether methods could be validated by the experiment. A 3-axis ACFM probe was developed and three plates including 16 defects, which served in nuclear plant before, were examined by automatic detection equipment. The result shows that the minimum detectable crack length on the surface is 2mm and ACFM shows excellent inspection results for a weld in stainless steel and gives an encouraging prospect of broader application.

Nucleic acid in-situ hybridization detection of infectious agents

NASA Astrophysics Data System (ADS)

Thompson, Curtis T.

2000-04-01

Limitations of traditional culture methods and newer polymerase chain reaction (PCR)-based methods for detection and speciation of infectious agents demonstrate the need for more rapid and better diagnostics. Nucleic acid hybridization is a detection technology that has gained wide acceptance in cancer and prenatal cytogenetics. Using a modification of the nucleic acid hybridization technique known as fluorescence in-situ hybridization, infectious agents can be detected in a variety of specimens with high sensitivity and specificity. The specimens derive from all types of human and animal sources including body fluids, tissue aspirates and biopsy material. Nucleic acid hybridization can be performed in less than one hour. The result can be interpreted either using traditional fluorescence microscopy or automated platforms such as micro arrays. This paper demonstrates proof of concept for nucleic acid hybridization detection of different infectious agents. Interpretation within a cytologic and histologic context is possible with fluorescence microscopic analysis, thereby providing confirmatory evidence of hybridization. With careful probe selection, nucleic acid hybridization promises to be a highly sensitive and specific practical diagnostic alternative to culture, traditional staining methods, immunohistochemistry and complicated nucleic acid amplification tests.

A PVC/polypyrrole sensor designed for beef taste detection using electrochemical methods and sensory evaluation.

PubMed

Zhu, Lingtao; Wang, Xiaodan; Han, Yunxiu; Cai, Yingming; Jin, Jiahui; Wang, Hongmei; Xu, Liping; Wu, Ruijia

2018-03-01

An electrochemical sensor for detection of beef taste was designed in this study. This sensor was based on the structure of polyvinyl chloride/polypyrrole (PVC/PPy), which was polymerized onto the surface of a platinum (Pt) electrode to form a Pt-PPy-PVC film. Detecting by electrochemical methods, the sensor was well characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The sensor was applied to detect 10 rib-eye beef samples and the accuracy of the new sensor was validated by sensory evaluation and ion sensor detection. Several cluster analysis methods were used in the study to distinguish the beef samples. According to the obtained results, the designed sensor showed a high degree of association of electrochemical detection and sensory evaluation, which proved a fast and precise sensor for beef taste detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Nakamura, K.

2016-06-01

Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

A source-attractor approach to network detection of radiation sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Qishi; Barry, M. L..; Grieme, M.

Radiation source detection using a network of detectors is an active field of research for homeland security and defense applications. We propose Source-attractor Radiation Detection (SRD) method to aggregate measurements from a network of detectors for radiation source detection. SRD method models a potential radiation source as a magnet -like attractor that pulls in pre-computed virtual points from the detector locations. A detection decision is made if a sufficient level of attraction, quantified by the increase in the clustering of the shifted virtual points, is observed. Compared with traditional methods, SRD has the following advantages: i) it does not requiremore » an accurate estimate of the source location from limited and noise-corrupted sensor readings, unlike the localizationbased methods, and ii) its virtual point shifting and clustering calculation involve simple arithmetic operations based on the number of detectors, avoiding the high computational complexity of grid-based likelihood estimation methods. We evaluate its detection performance using canonical datasets from Domestic Nuclear Detection Office s (DNDO) Intelligence Radiation Sensors Systems (IRSS) tests. SRD achieves both lower false alarm rate and false negative rate compared to three existing algorithms for network source detection.« less

Comprehensive Detection of Gas Plumes from Multibeam Water Column Images with Minimisation of Noise Interferences

PubMed Central

Zhao, Jianhu; Zhang, Hongmei; Wang, Shiqi

2017-01-01

Multibeam echosounder systems (MBES) can record backscatter strengths of gas plumes in the water column (WC) images that may be an indicator of possible occurrence of gas at certain depths. Manual or automatic detection is generally adopted in finding gas plumes, but frequently results in low efficiency and high false detection rates because of WC images that are polluted by noise. To improve the efficiency and reliability of the detection, a comprehensive detection method is proposed in this paper. In the proposed method, the characteristics of WC background noise are first analyzed and given. Then, the mean standard deviation threshold segmentations are respectively used for the denoising of time-angle and depth-angle images, an intersection operation is performed for the two segmented images to further weaken noise in the WC data, and the gas plumes in the WC data are detected from the intersection image by the morphological constraint. The proposed method was tested by conducting shallow-water and deepwater experiments. In these experiments, the detections were conducted automatically and higher correct detection rates than the traditional methods were achieved. The performance of the proposed method is analyzed and discussed. PMID:29186014

Rapid on-site TLC-SERS detection of four antidiabetes drugs used as adulterants in botanical dietary supplements.

PubMed

Zhu, Qingxia; Cao, Yongbing; Cao, Yingying; Chai, Yifeng; Lu, Feng

2014-03-01

A novel facile method has been established for rapid on-site detection of antidiabetes chemicals used to adulterate botanical dietary supplements (BDS) for diabetes. Analytes and components of pharmaceutical matrices were separated by thin-layer chromatography (TLC) then surface-enhanced Raman spectroscopy (SERS) was used for qualitative identification of trace substances on the HPTLC plate. Optimization and standardization of the experimental conditions, for example the method used for preparation of silver colloids, the mobile phase, and the concentration of colloidal silver, resulted in a very robust and highly sensitive method which enabled successful detection when the amount of adulteration was as low as 0.001 % (w/w). The method was also highly selective, enabling successful identification of some chemicals in extremely complex herbal matrices. The established TLC-SERS method was used for analysis of real BDS used to treat diabetes, and the results obtained were verified by liquid chromatography-triple quadrupole mass spectrometry (LC-MS-MS). The study showed that TLC-SERS could be used for effective separation and detection of four chemicals used to adulterate BDS, and would have good prospects for on-site qualitative screening of BDS for adulterants.

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

Detecting special nuclear materials in containers using high-energy gamma rays emitted by fission products

DOEpatents

Norman, Eric B.; Prussin, Stanley G.

2007-10-02

A method and a system for detecting the presence of special nuclear materials in a container. The system and its method include irradiating the container with an energetic beam, so as to induce a fission in the special nuclear materials, detecting the gamma rays that are emitted from the fission products formed by the fission, to produce a detector signal, comparing the detector signal with a threshold value to form a comparison, and detecting the presence of the special nuclear materials using the comparison.

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

PubMed Central

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-01-01

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

PubMed

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-08-24

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

Diagnostic value of DIAGNOdent in detecting caries under composite restorations of primary molars

PubMed Central

Sichani, Ava Vali; Javadinejad, Shahrzad; Ghafari, Roshanak

2016-01-01

Background: Direct observation cannot detect caries under restorations; therefore, the aim of this study was to compare the accuracy of radiographs and DIAGNOdent in detecting caries under restorations in primary teeth using histologic evaluation. Materials and Methods: A total of 74 previously extracted primary molars (37 with occlusal caries and 37 without caries) were used. Class 1 cavity preparations were made on each tooth by a single clinician and then the preparations were filled with composite resin. The accuracy of radiographs and DIAGNOdent in detecting caries was compared using histologic evaluation. The data were analyzed by SPSS version 21 using Chi-square, Mc Namara statistical tests and receiver operating characteristic curve. The significance was set at 0.05. Results: The sensitivity and specificity for DIAGNOdent were 70.97 and 83.72, respectively. Few false negative results were observed, and the positive predictive value was high (+PV = 75.9) and the area under curve was more than 0.70 therefore making DIAGNOdenta great method for detecting caries (P = 0.0001). Two observers evaluated the radiographs and both observers had low sensitivity ( first observer: 48.39) (second observer: 51.61) and high specificity (both observers: 79.07). The +PV was lower than DIAGNOdent and the area under curve for both observers was less than 0.70. However, the difference between the two methods was not significant. Conclusion: DIAGNOdent showed a greater accuracy in detecting secondary caries under primary molar restorations, compared to radiographs. Although DIAGNOdent is an effective method for detecting caries under composite restorations, it is better to be used as an adjunctive method alongside other detecting procedures. PMID:27605990

Comparison of detection methods for cell surface globotriaosylceramide.

PubMed

Kim, Minji; Binnington, Beth; Sakac, Darinka; Fernandes, Kimberly R; Shi, Sheryl P; Lingwood, Clifford A; Branch, Donald R

2011-08-31

The cell surface-expressed glycosphingolipid (GSL), globotriaosylceramide (Gb(3)), is becoming increasingly important and is widely studied in the areas of verotoxin (VT)-mediated cytotoxicity, human immunodeficiency virus (HIV) infection, immunology and cancer. However, despite its diverse roles and implications, an optimized detection method for cell surface Gb(3) has not been determined. GSLs are differentially organized in the plasma membrane which can affect their availability for protein binding. To examine various detection methods for cell surface Gb(3), we compared four reagents for use in flow cytometry analysis. A natural ligand (VT1B) and three different monoclonal antibodies (mAbs) were optimized and tested on various human cell lines for Gb(3) detection. A differential detection pattern of cell surface Gb(3) expression, which was influenced by the choice of reagent, was observed. Two mAb were found to be suboptimal. However, two other methods were found to be useful as defined by their high percentage of positivity and mean fluorescence intensity (MFI) values. Rat IgM anti-Gb(3) mAb (clone 38-13) using phycoerythrin-conjugated secondary antibody was found to be the most specific detection method while the use of VT1B conjugated to Alexa488 fluorochrome was found to be the most sensitive; showing a rare crossreactivity only when Gb(4) expression was highly elevated. The findings of this study demonstrate the variability in detection of Gb(3) depending on the reagent and cell target used and emphasize the importance of selecting an optimal methodology in studies for the detection of cell surface expression of Gb(3). Copyright © 2011 Elsevier B.V. All rights reserved.

Ultra-sensitive high performance liquid chromatography-laser-induced fluorescence based proteomics for clinical applications.

PubMed

Patil, Ajeetkumar; Bhat, Sujatha; Pai, Keerthilatha M; Rai, Lavanya; Kartha, V B; Chidangil, Santhosh

2015-09-08

An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper. In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

Determination of chlorophenols in honey samples using in-situ ionic liquid-dispersive liquid-liquid microextraction as a pretreatment method followed by high-performance liquid chromatography.

PubMed

Fan, Chen; Li, Nai; Cao, Xueli

2015-05-01

In-situ ionic liquid-dispersive liquid-liquid microextraction (IL-DLLME) method was developed as a pretreatment method for the detection of six chlorophenols (CPs) in honey samples. The hydrophobic ionic liquid [C4MIM][NTf2], formed in-situ by the hydrophilic ionic liquid [C4MIM][BF4] and the ion exchange reagent LiNTf2 was used as the microextractant solvent of CPs from honey sample. Then the enriched analytes were back-extracted into 40 μL of 0.14 M NaOH solution and finally subjected to analysis by high-performance liquid chromatography. The method showed low limit of detection of CPs, 0.8-3.2 μg/L and high enrichment factor, 34-65 with the recoveries range from 91.60% to 114.33%. The method is simple, rapid, environmentally friendly and with high extraction efficiency. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Detection method of visible and invisible nipples on digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Chae, Seung-Hoon; Jeong, Ji-Wook; Lee, Sooyeul; Chae, Eun Young; Kim, Hak Hee; Choi, Young-Wook

2015-03-01

Digital Breast Tomosynthesis(DBT) with 3D breast image can improve detection sensitivity of breast cancer more than 2D mammogram on dense breast. The nipple location information is needed to analyze DBT. The nipple location is invaluable information in registration and as a reference point for classifying mass or micro-calcification clusters. Since there are visible nipple and invisible nipple in 2D mammogram or DBT, the nipple detection of breast must be possible to detect visible and invisible nipple of breast. The detection method of visible nipple using shape information of nipple is simple and highly efficient. However, it is difficult to detect invisible nipple because it doesn't have prominent shape. Mammary glands in breast connect nipple, anatomically. The nipple location is detected through analyzing location of mammary glands in breast. In this paper, therefore, we propose a method to detect the nipple on a breast, which has a visible or invisible nipple using changes of breast area and mammary glands, respectively. The result shows that our proposed method has average error of 2.54+/-1.47mm.

Low-Noise Free-Running High-Rate Photon-Counting for Space Communication and Ranging

NASA Technical Reports Server (NTRS)

Lu, Wei; Krainak, Michael A.; Yang, Guangning; Sun, Xiaoli; Merritt, Scott

2016-01-01

We present performance data for low-noise free-running high-rate photon counting method for space optical communication and ranging. NASA GSFC is testing the performance of two types of novel photon-counting detectors 1) a 2x8 mercury cadmium telluride (HgCdTe) avalanche array made by DRS Inc., and a 2) a commercial 2880-element silicon avalanche photodiode (APD) array. We successfully measured real-time communication performance using both the 2 detected-photon threshold and logic AND-gate coincidence methods. Use of these methods allows mitigation of dark count, after-pulsing and background noise effects without using other method of Time Gating The HgCdTe APD array routinely demonstrated very high photon detection efficiencies ((is) greater than 50%) at near infrared wavelength. The commercial silicon APD array exhibited a fast output with rise times of 300 ps and pulse widths of 600 ps. On-chip individually filtered signals from the entire array were multiplexed onto a single fast output. NASA GSFC has tested both detectors for their potential application for space communications and ranging. We developed and compare their performances using both the 2 detected photon threshold and coincidence methods.

Low-Noise Free-Running High-Rate Photon-Counting for Space Communication and Ranging

NASA Technical Reports Server (NTRS)

Lu, Wei; Krainak, Michael A.; Yang, Guan; Sun, Xiaoli; Merritt, Scott

2016-01-01

We present performance data for low-noise free-running high-rate photon counting method for space optical communication and ranging. NASA GSFC is testing the performance of two types of novel photon-counting detectors 1) a 2x8 mercury cadmium telluride (HgCdTe) avalanche array made by DRS Inc., and a 2) a commercial 2880-element silicon avalanche photodiode (APD) array. We successfully measured real-time communication performance using both the 2 detected-photon threshold and logic AND-gate coincidence methods. Use of these methods allows mitigation of dark count, after-pulsing and background noise effects without using other method of Time Gating The HgCdTe APD array routinely demonstrated very high photon detection efficiencies (50) at near infrared wavelength. The commercial silicon APD array exhibited a fast output with rise times of 300 ps and pulse widths of 600 ps. On-chip individually filtered signals from the entire array were multiplexed onto a single fast output. NASA GSFC has tested both detectors for their potential application for space communications and ranging. We developed and compare their performances using both the 2 detected photon threshold and coincidence methods.

Ultrasensitive Detection of Single-Walled Carbon Nanotubes Using Surface Plasmon Resonance.

PubMed

Jang, Daeho; Na, Wonhwi; Kang, Minwook; Kim, Namjoon; Shin, Sehyun

2016-01-05

Because single-walled carbon nanotubes (SWNTs) are known to be a potentially dangerous material, inducing cancers and other diseases, any possible leakage of SWNTs through an aquatic medium such as drinking water will result in a major public threat. To solve this problem, for the present study, a highly sensitive, quantitative detection method of SWNTs in an aqueous solution was developed using surface plasmon resonance (SPR) spectroscopy. For a highly sensitive and specific detection, a strong affinity conjugation with biotin-streptavidin was adopted on an SPR sensing mechanism. During the pretreatment process, the SWNT surface was functionalized and hydrophilized using a thymine-chain based biotinylated single-strand DNA linker (B-ssDNA) and bovine serum albumin (BSA). The pretreated SWNTs were captured on a sensing film, the surface of which was immobilized with streptavidin on biotinylated gold film. The captured SWNTs were measured in real-time using SPR spectroscopy. Specific binding with SWNTs was verified through several validation experiments. The present method using an SPR sensor is capable of detecting SWNTs of as low as 100 fg/mL, which is the lowest level reported thus far for carbon-nanotube detection. In addition, the SPR sensor showed a linear characteristic within the range of 100 pg/mL to 200 ng/mL. These findings imply that the present SPR sensing method can detect an extremely low level of SWNTs in an aquatic environment with high sensitivity and high specificity, and thus any potential leakage of SWNTs into an aquatic environment can be precisely monitored within a couple of hours.

A novel approach to mask defect inspection

NASA Astrophysics Data System (ADS)

Sagiv, Amir; Shirman, Yuri; Mangan, Shmoolik

2008-10-01

Memory chips, now constituting a major part of semiconductor market, posit a special challenge for inspection, as they are generally produced with the smallest half-pitch available with today's technology. This is true, in particular, to photomasks of advanced memory devices, which are at the forefront of the "low-k1" regime. In this paper we present a novel photomask inspection approach, that is particularly suitable for low-k1 layers of advanced memory chips, owing to their typical dense and periodic structure. The method we present can produce a very strong signal for small mask defects, by suppression of the modulation of the pattern's image. Unlike dark-field detection, however, here a single diffraction order associated with the pattern generates a constant "gray" background image, that is used for signal enhancement. We define the theoretical basis for the new detection technique, and show, both analytically and numerically, that it can easily achieve a detection line past the printability spec, and that in cases it is at least as sensitive as high-resolution based detection. We also demonstrate this claim experimentally on a customer mask, using the platform of Applied Material's newly released Aera2TM mask inspection tool. The high sensitivity demonstrates the important and often overlooked concept that resolution is not synonymous with sensitivity. The novel detection method is advantageous in several other aspects, such as the very simple implementation, the high throughput, and the relatively simple pre- and post-processing algorithms required for signal extraction. These features, and in particular the very high sensitivity, make this novel detection method an attractive inspection option for advanced memory devices.

A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang

2017-01-01

The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than -3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated.

Improving prokaryotic transposable elements identification using a combination of de novo and profile HMM methods.

PubMed

Kamoun, Choumouss; Payen, Thibaut; Hua-Van, Aurélie; Filée, Jonathan

2013-10-11

Insertion Sequences (ISs) and their non-autonomous derivatives (MITEs) are important components of prokaryotic genomes inducing duplication, deletion, rearrangement or lateral gene transfers. Although ISs and MITEs are relatively simple and basic genetic elements, their detection remains a difficult task due to their remarkable sequence diversity. With the advent of high-throughput genome and metagenome sequencing technologies, the development of fast, reliable and sensitive methods of ISs and MITEs detection become an important challenge. So far, almost all studies dealing with prokaryotic transposons have used classical BLAST-based detection methods against reference libraries. Here we introduce alternative methods of detection either taking advantages of the structural properties of the elements (de novo methods) or using an additional library-based method using profile HMM searches. In this study, we have developed three different work flows dedicated to ISs and MITEs detection: the first two use de novo methods detecting either repeated sequences or presence of Inverted Repeats; the third one use 28 in-house transposase alignment profiles with HMM search methods. We have compared the respective performances of each method using a reference dataset of 30 archaeal and 30 bacterial genomes in addition to simulated and real metagenomes. Compared to a BLAST-based method using ISFinder as library, de novo methods significantly improve ISs and MITEs detection. For example, in the 30 archaeal genomes, we discovered 30 new elements (+20%) in addition to the 141 multi-copies elements already detected by the BLAST approach. Many of the new elements correspond to ISs belonging to unknown or highly divergent families. The total number of MITEs has even doubled with the discovery of elements displaying very limited sequence similarities with their respective autonomous partners (mainly in the Inverted Repeats of the elements). Concerning metagenomes, with the exception of short reads data (<300 bp) for which both techniques seem equally limited, profile HMM searches considerably ameliorate the detection of transposase encoding genes (up to +50%) generating low level of false positives compare to BLAST-based methods. Compared to classical BLAST-based methods, the sensitivity of de novo and profile HMM methods developed in this study allow a better and more reliable detection of transposons in prokaryotic genomes and metagenomes. We believed that future studies implying ISs and MITEs identification in genomic data should combine at least one de novo and one library-based method, with optimal results obtained by running the two de novo methods in addition to a library-based search. For metagenomic data, profile HMM search should be favored, a BLAST-based step is only useful to the final annotation into groups and families.

Epidermal segmentation in high-definition optical coherence tomography.

PubMed

Li, Annan; Cheng, Jun; Yow, Ai Ping; Wall, Carolin; Wong, Damon Wing Kee; Tey, Hong Liang; Liu, Jiang

2015-01-01

Epidermis segmentation is a crucial step in many dermatological applications. Recently, high-definition optical coherence tomography (HD-OCT) has been developed and applied to imaging subsurface skin tissues. In this paper, a novel epidermis segmentation method using HD-OCT is proposed in which the epidermis is segmented by 3 steps: the weighted least square-based pre-processing, the graph-based skin surface detection and the local integral projection-based dermal-epidermal junction detection respectively. Using a dataset of five 3D volumes, we found that this method correlates well with the conventional method of manually marking out the epidermis. This method can therefore serve to effectively and rapidly delineate the epidermis for study and clinical management of skin diseases.

Convenient, sensitive and high-throughput method for screening botanic origin.

PubMed

Yuan, Yuan; Jiang, Chao; Liu, Libing; Yu, Shulin; Cui, Zhanhu; Chen, Min; Lin, Shufang; Wang, Shu; Huang, Luqi

2014-06-23

In this work, a rapid (within 4-5 h), sensitive and visible new method for assessing botanic origin is developed by combining loop-mediated isothermal amplification with cationic conjugated polymers. The two Chinese medicinal materials (Jin-Yin-Hua and Shan-Yin-Hua) with similar morphology and chemical composition were clearly distinguished by gene SNP genotyping assays. The identification of plant species in Patented Chinese drugs containing Lonicera buds is successfully performed using this detection system. The method is also robust enough to be used in high-throughput screening. This new method is very helpful to identify herbal materials, and is beneficial for detecting safety and quality of botanic products.

An optimized content-aware image retargeting method: toward expanding the perceived visual field of the high-density retinal prosthesis recipients

NASA Astrophysics Data System (ADS)

Li, Heng; Zeng, Yajie; Lu, Zhuofan; Cao, Xiaofei; Su, Xiaofan; Sui, Xiaohong; Wang, Jing; Chai, Xinyu

2018-04-01

Objective. Retinal prosthesis devices have shown great value in restoring some sight for individuals with profoundly impaired vision, but the visual acuity and visual field provided by prostheses greatly limit recipients’ visual experience. In this paper, we employ computer vision approaches to seek to expand the perceptible visual field in patients implanted potentially with a high-density retinal prosthesis while maintaining visual acuity as much as possible. Approach. We propose an optimized content-aware image retargeting method, by introducing salient object detection based on color and intensity-difference contrast, aiming to remap important information of a scene into a small visual field and preserve their original scale as much as possible. It may improve prosthetic recipients’ perceived visual field and aid in performing some visual tasks (e.g. object detection and object recognition). To verify our method, psychophysical experiments, detecting object number and recognizing objects, are conducted under simulated prosthetic vision. As control, we use three other image retargeting techniques, including Cropping, Scaling, and seam-assisted shrinkability. Main results. Results show that our method outperforms in preserving more key features and has significantly higher recognition accuracy in comparison with other three image retargeting methods under the condition of small visual field and low-resolution. Significance. The proposed method is beneficial to expand the perceived visual field of prosthesis recipients and improve their object detection and recognition performance. It suggests that our method may provide an effective option for image processing module in future high-density retinal implants.

Highly specific and efficient primers for in-house multiplex PCR detection of Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum

PubMed Central

2014-01-01

Background Although sophisticated methodologies are available, the use of endpoint polymerase chain reaction (PCR) to detect 16S rDNA genes remains a good approach for estimating the incidence and prevalence of specific infections and for monitoring infections. Considering the importance of the early diagnosis of sexually transmitted infections (STIs), the development of a sensitive and affordable method for identifying pathogens in clinical samples is needed. Highly specific and efficient primers for a multiplex polymerase chain reaction (m-PCR) system were designed in silico to detect the 16S rDNA genes of four bacteria that cause genital infections, and the PCR method was developed. Methods The Genosensor Probe Designer (GPD) (version 1.0a) software was initially used to design highly specific and efficient primers for in-house m-PCR. Single-locus PCR reactions were performed and standardised, and then primers for each locus in turn were added individually in subsequent amplifications until m-PCR was achieved. Amplicons of the expected size were obtained from each of the four bacterial gene fragments. Finally, the analytical specificity and limits of detection were tested. Results Because they did not amplify any product from non-STI tested species, the primers were specific. The detection limits for the Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum primer sets were 5.12 × 105, 3.9 × 103, 61.19 × 106 and 6.37 × 105 copies of a DNA template, respectively. Conclusions The methodology designed and standardised here could be applied satisfactorily for the simultaneous or individual detection of Chlamydia trachomatis, Neisseria gonorrhoeae, Mycoplasma hominis and Ureaplasma urealyticum. This method is at least as efficient as other previously described methods; however, this method is more affordable for low-income countries. PMID:24997675

A highly sensitive and specific method for the screening detection of genetically modified organisms based on digital PCR without pretreatment

PubMed Central

Fu, Wei; Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Du, Zhixin; Tian, Wenying; Wang, Qin; Wang, Huiyu; Xu, Wentao; Zhu, Shuifang

2015-01-01

Digital PCR has developed rapidly since it was first reported in the 1990s. It was recently reported that an improved method facilitated the detection of genetically modified organisms (GMOs). However, to use this improved method, the samples must be pretreated, which could introduce inaccuracy into the results. In our study, we explored a pretreatment-free digital PCR detection method for the screening for GMOs. We chose the CaMV35s promoter and the NOS terminator as the templates in our assay. To determine the specificity of our method, 9 events of GMOs were collected, including MON810, MON863, TC1507, MIR604, MIR162, GA21, T25, NK603 and Bt176. Moreover, the sensitivity, intra-laboratory and inter-laboratory reproducibility of our detection method were assessed. The results showed that the limit of detection of our method was 0.1%, which was lower than the labeling threshold level of the EU. The specificity and stability among the 9 events were consistent, respectively. The intra-laboratory and inter-laboratory reproducibility were both good. Finally, the perfect fitness for the detection of eight double-blind samples indicated the good practicability of our method. In conclusion, the method in our study would allow more sensitive, specific and stable screening detection of the GMO content of international trading products. PMID:26239916

A highly sensitive and specific method for the screening detection of genetically modified organisms based on digital PCR without pretreatment.

PubMed

Fu, Wei; Zhu, Pengyu; Wang, Chenguang; Huang, Kunlun; Du, Zhixin; Tian, Wenying; Wang, Qin; Wang, Huiyu; Xu, Wentao; Zhu, Shuifang

2015-08-04

Digital PCR has developed rapidly since it was first reported in the 1990 s. It was recently reported that an improved method facilitated the detection of genetically modified organisms (GMOs). However, to use this improved method, the samples must be pretreated, which could introduce inaccuracy into the results. In our study, we explored a pretreatment-free digital PCR detection method for the screening for GMOs. We chose the CaMV35s promoter and the NOS terminator as the templates in our assay. To determine the specificity of our method, 9 events of GMOs were collected, including MON810, MON863, TC1507, MIR604, MIR162, GA21, T25, NK603 and Bt176. Moreover, the sensitivity, intra-laboratory and inter-laboratory reproducibility of our detection method were assessed. The results showed that the limit of detection of our method was 0.1%, which was lower than the labeling threshold level of the EU. The specificity and stability among the 9 events were consistent, respectively. The intra-laboratory and inter-laboratory reproducibility were both good. Finally, the perfect fitness for the detection of eight double-blind samples indicated the good practicability of our method. In conclusion, the method in our study would allow more sensitive, specific and stable screening detection of the GMO content of international trading products.

Highly sensitive fluorescence detection of metastatic lymph nodes of gastric cancer with photo-oxidation of protoporphyrin IX.

PubMed

Koizumi, N; Harada, Y; Beika, M; Minamikawa, T; Yamaoka, Y; Dai, P; Murayama, Y; Yanagisawa, A; Otsuji, E; Tanaka, H; Takamatsu, T

2016-08-01

The establishment of a precise and rapid method to detect metastatic lymph nodes (LNs) is essential to perform less invasive surgery with reduced gastrectomy along with reduced lymph node dissection. We herein describe a novel imaging strategy to detect 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence in excised LNs specifically with reduced effects of tissue autofluorescence based on photo-oxidation of PpIX. We applied the method in a clinical setting, and evaluated its feasibility. To reduce the unfavorable effect of autofluorescence, we focused on photo-oxidation of PpIX: Following light irradiation, PpIX changes into another substance, photo-protoporphyrin, via an oxidative process, which has a different spectral peak, at 675 nm, whereas PpIX has its spectral peak at 635 nm. Based on the unique spectral alteration, fluorescence spectral imaging before and after light irradiation and subsequent originally-developed image processing was performed. Following in vitro study, we applied this method to a total of 662 excised LNs obtained from 30 gastric cancer patients administered 5-ALA preoperatively. Specific visualization of PpIX was achieved in in vitro study. The method allowed highly sensitive detection of metastatic LNs, with sensitivity of 91.9% and specificity of 90.8% in the in vivo clinical trial. Receiver operating characteristic analysis indicated high diagnostic accuracy, with the area under the curve of 0.926. We established a highly sensitive and specific 5-ALA-induced fluorescence imaging method applicable in clinical settings. The novel method has a potential to become a useful tool for intraoperative rapid diagnosis of LN metastasis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of digital PCR for detecting low-level EGFR mutations in advanced lung adenocarcinoma patients: a cross-platform comparison study

PubMed Central

Liu, Bing; Li, Lei; Huang, Lixia; Li, Shaoli; Rao, Guanhua; Yu, Yang; Zhou, Yanbin

2017-01-01

Emerging evidence has indicated that circulating tumor DNA (ctDNA) from plasma could be used to analyze EGFR mutation status for NSCLC patients; however, due to the low level of ctDNA in plasma, highly sensitive approaches are required to detect low frequency mutations. In addition, the cutoff for the mutation abundance that can be detected in tumor tissue but cannot be detected in matched ctDNA is still unknown. To assess a highly sensitive method, we evaluated the use of digital PCR in the detection of EGFR mutations in tumor tissue from 47 advanced lung adenocarcinoma patients through comparison with NGS and ARMS. We determined the degree of concordance between tumor tissue DNA and paired ctDNA and analyzed the mutation abundance relationship between them. Digital PCR and Proton had a high sensitivity (96.00% vs. 100%) compared with that of ARMS in the detection of mutations in tumor tissue. Digital PCR outperformed Proton in identifying more low abundance mutations. The ctDNA detection rate of digital PCR was 87.50% in paired tumor tissue with a mutation abundance above 5% and 7.59% in paired tumor tissue with a mutation abundance below 5%. When the DNA mutation abundance of tumor tissue was above 3.81%, it could identify mutations in paired ctDNA with a high sensitivity. Digital PCR will help identify alternative methods for detecting low abundance mutations in tumor tissue DNA and plasma ctDNA. PMID:28978074

Advanced Virus Detection Technologies Interest Group (AVDTIG): Efforts on High Throughput Sequencing (HTS) for Virus Detection.

PubMed

Khan, Arifa S; Vacante, Dominick A; Cassart, Jean-Pol; Ng, Siemon H S; Lambert, Christophe; Charlebois, Robert L; King, Kathryn E

Several nucleic-acid based technologies have recently emerged with capabilities for broad virus detection. One of these, high throughput sequencing, has the potential for novel virus detection because this method does not depend upon prior viral sequence knowledge. However, the use of high throughput sequencing for testing biologicals poses greater challenges as compared to other newly introduced tests due to its technical complexities and big data bioinformatics. Thus, the Advanced Virus Detection Technologies Users Group was formed as a joint effort by regulatory and industry scientists to facilitate discussions and provide a forum for sharing data and experiences using advanced new virus detection technologies, with a focus on high throughput sequencing technologies. The group was initiated as a task force that was coordinated by the Parenteral Drug Association and subsequently became the Advanced Virus Detection Technologies Interest Group to continue efforts for using new technologies for detection of adventitious viruses with broader participation, including international government agencies, academia, and technology service providers. © PDA, Inc. 2016.

Applicability of a Conservative Margin Approach for Assessing NDE Flaw Detectability

NASA Technical Reports Server (NTRS)

Koshti, ajay M.

2007-01-01

Nondestructive Evaluation (NDE) procedures are required to detect flaws in structures with a high percentage detectability and high confidence. Conventional Probability of Detection (POD) methods are statistical in nature and require detection data from a relatively large number of flaw specimens. In many circumstances, due to the high cost and long lead time, it is impractical to build the large set of flaw specimens that is required by the conventional POD methodology. Therefore, in such situations it is desirable to have a flaw detectability estimation approach that allows for a reduced number of flaw specimens but provides a high degree of confidence in establishing the flaw detectability size. This paper presents an alternative approach called the conservative margin approach (CMA). To investigate the applicability of the CMA approach, flaw detectability sizes determined by the CMA and POD approaches have been compared on actual datasets. The results of these comparisons are presented and the applicability of the CMA approach is discussed.

Particle detection for patterned wafers of 100nm design rule by evanescent light illumination: analysis of evanescent light scattering using Finite-Difference Time-Domain (FDTD) method

NASA Astrophysics Data System (ADS)

Yoshioka, Toshie; Miyoshi, Takashi; Takaya, Yasuhiro

2005-12-01

To realize high productivity and reliability of the semiconductor, patterned wafers inspection technology to maintain high yield becomes essential in modern semiconductor manufacturing processes. As circuit feature is scaled below 100nm, the conventional imaging and light scattering methods are impossible to apply to the patterned wafers inspection technique, because of diffraction limit and lower S/N ratio. So, we propose a new particle detection method using annular evanescent light illumination. In this method, a converging annular light used as a light source is incident on a micro-hemispherical lens. When the converging angle is larger than critical angle, annular evanescent light is generated under the bottom surface of the hemispherical lens. Evanescent light is localized near by the bottom surface and decays exponentially away from the bottom surface. So, the evanescent light selectively illuminates the particles on the patterned wafer surface, because it can't illuminate the patterned wafer surface. The proposed method evaluates particles on a patterned wafer surface by detecting scattered evanescent light distribution from particles. To analyze the fundamental characteristics of the proposed method, the computer simulation was performed using FDTD method. The simulation results show that the proposed method is effective for detecting 100nm size particle on patterned wafer of 100nm lines and spaces, particularly under the condition that the evanescent light illumination with p-polarization and parallel incident to the line orientation. Finally, the experiment results suggest that 220nm size particle on patterned wafer of about 200nm lines and spaces can be detected.

Hypergraph-based anomaly detection of high-dimensional co-occurrences.

PubMed

Silva, Jorge; Willett, Rebecca

2009-03-01

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.

Fast detection and characterization of organic and inorganic gunshot residues on the hands of suspects by CMV-GC-MS and LIBS.

PubMed

Tarifa, Anamary; Almirall, José R

2015-05-01

A rapid method for the characterization of both organic and inorganic components of gunshot residues (GSR) is proposed as an alternative tool to facilitate the identification of a suspected shooter. In this study, two fast screening methods were developed and optimized for the detection of organic compounds and inorganic components indicative of GSR presence on the hands of shooters and non-shooters. The proposed methods consist of headspace extraction of volatile organic compounds using a capillary microextraction of volatiles (CMV) device previously reported as a high-efficiency sampler followed by detection by GC-MS. This novel sampling technique has the potential to yield fast results (<2min sampling) and high sensitivity capable of detecting 3ng of diphenylamine (DPA) and 8ng of nitroglycerine (NG). Direct analysis of the headspace of over 50 swabs collected from the hands of suspected shooters (and non-shooters) provides information regarding VOCs present on their hands. In addition, a fast laser induced breakdown spectroscopy (LIBS) screening method for the detection of the inorganic components indicative of the presence of GSR (Sb, Pb and Ba) is described. The sampling method for the inorganics consists of liquid extraction of the target elements from the same cotton swabs (previously analyzed for VOCs) and an additional 30 swab samples followed by spiking 1μL of the extract solution onto a Teflon disk and then analyzed by LIBS. Advantages of LIBS include fast analysis (~12s per sample) and high selectivity and sensitivity, with expected LODs 0.1-18ng for each of the target elements after sampling. The analytical performance of the LIBS method is also compared to previously reported methods (inductively coupled plasma-optical emission spectroscopy). The combination of fast CMV sampling, unambiguous organic compound identification with GC-MS and fast LIBS analysis provides the basis for a new comprehensive screening method for GSR. Copyright © 2015 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

Aptamer-based microspheres for highly sensitive protein detection using fluorescently-labeled DNA nanostructures.

PubMed

Han, Daehoon; Hong, Jinkee; Kim, Hyun Cheol; Sung, Jong Hwan; Lee, Jong Bum

2013-11-01

Many highly sensitive protein detection techniques have been developed and have played an important role in the analysis of proteins. Herein, we report a novel technique that can detect proteins sensitively and effectively using aptamer-based DNA nanostructures. Thrombin was used as a target protein and aptamer was used to capture fluorescent dye-labeled DNA nanobarcodes or thrombin on a microsphere. The captured DNA nanobarcodes were replaced by a thrombin and aptamer interaction. The detection ability of this approach was confirmed by flow cytometry with different concentrations of thrombin. Our detection method has great potential for rapid and simple protein detection with a variety of aptamers.

Sensitive quantification of coixol, a potent insulin secretagogue, in Scoparia dulcis extract using high-performance liquid chromatography combined with tandem mass spectrometry and UV detection.

PubMed

Ali, Arslan; Haq, Faraz Ul; Ul Arfeen, Qamar; Sharma, Khaga Raj; Adhikari, Achyut; Musharraf, Syed Ghulam

2017-10-01

Diabetes is a major global health problem which requires new studies for its prevention and control. Scoparia dulcis, a herbal product, is widely used for treatment of diabetes. Recent studies demonstrate coixol as a potent and nontoxic insulin secretagog from S. dulcis. This study focuses on developing two quantitative methods of coixol in S. dulcis methanol-based extracts. Quantification of coixol was performed using high-performance liquid chromatography-tandem mass spectrometry (method 1) and high-performance liquid chromatography-ultraviolet detection (method 2) with limits of detection of 0.26 and 11.6 pg/μL, respectively, and limits of quantification of 0.78 and 35.5 pg/μL, respectively. S. dulcis is rich in coixol content with values of 255.5 ± 2.1 mg/kg (method 1) and 220.4 ± 2.9 mg/kg (method 2). Excellent linearity with determination coefficients >0.999 was achieved for calibration curves from 10 to 7500 ng/mL (method 1) and from 175 to 7500 ng/mL (method 2). Good accuracy (bias < -8.6%) and precision (RSD < 8.5%) were obtained for both methods. Thus, they can be employed to analyze coixol in plant extracts and herbal formulations. Copyright © 2017 John Wiley & Sons, Ltd.

A new s-adenosylhomocysteine hydrolase-linked method for adenosine detection based on DNA-templated fluorescent Cu/Ag nanoclusters.

PubMed

Ahn, Jun Ki; Kim, Hyo Yong; Baek, Songyi; Park, Hyun Gyu

2017-07-15

We herein describe a novel fluorescent method for the rapid and selective detection of adenosine by utilizing DNA-templated Cu/Ag nanoclusters (NCs) and employing s-adenosylhomocysteine hydrolase (SAHH). SAHH is allowed to promote hydrolysis reaction of s-adenosylhomocysteine (SAH) and consequently produces homocysteine, which would quench the fluorescence signal from DNA-templated Cu/Ag nanoclusters employed as a signaling probe in this study. On the other hand, adenosine significantly inhibits the hydrolysis reaction and prevent the formation of homocysteine. Consequently, highly enhanced fluorescence signal from DNA-Cu/Ag NCs is retained, which could be used to identify the presence of adenosine. By employing this design principle, adenosine was sensitively detected down to 19nM with high specificity over other adenosine analogs such as AMP, ADP, ATP, cAMP, guanosine, cytidine, and urine. Finally, the diagnostic capability of this method was successfully verified by reliably detecting adenosine present in a real human serum sample. Copyright © 2016 Elsevier B.V. All rights reserved.

[Molecular characterization of resistance mechanisms: methicillin resistance Staphylococcus aureus, extended spectrum β-lactamases and carbapenemases].

PubMed

Oteo, Jesús; Belén Aracil, María

2015-07-01

Multi-drug resistance in bacterial pathogens increases morbidity and mortality in infected patients and it is a threat to public health concern by their high capacity to spread. For both reasons, the rapid detection of multi-drug resistant bacteria is critical. Standard microbiological procedures require 48-72 h to provide the antimicrobial susceptibility results, thus there is emerging interest in the development of rapid detection techniques. In recent years, the use of selective and differential culture-based methods has widely spread. However, the capacity for detecting antibiotic resistance genes and their low turnaround times has made molecular methods a reference for diagnosis of multidrug resistance. This review focusses on the molecular methods for detecting some mechanisms of antibiotic resistance with a high clinical and epidemiological impact: a) Enzymatic resistance to broad spectrum β-lactam antibiotics in Enterobacteriaceae, mainly extended spectrum β-lactamases (ESBL) and carbapenemases; and b) methicillin resistance in Staphylococcus aureus. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

[The occurrence of Fusarium varieties and their mycotoxins on silo corn. 1. A method for the determination of zearalenone in corn and corn silage by high performance liquid chromatography (HPLC) with fluorescence detection].

PubMed

Lepom, P

1988-09-01

A method for the determination of zearalenone in maize and maize silage was developed which distinguishes itself by the effective and fast cleaning of the extracts with the help of a silica gel minicolumn. The samples were extracted with chloroform/methanol (9 + 1) and cleaned on a silica gel minicolumn after acid-base partition. The zearalenone was quantitatively determined optionally by means of high-performance liquid chromatography (HPLC) with fluorescence detection (excitation wavelength 236 nm, emission filter 418 nm) or thin-layer chromatography (TLC), p-methoxybenzene diazonium fluoroborate and aluminium chloride were used as detection chemicals. The limits of detection are 0.01 mg/kg (HPLC) and 0.1 mg/kg resp. (TLC), the average recovery is 81%. The method was used for the determination of zearalenone in grain maize, CCM silage and silage from whole maize plants.

Urban Area Detection in Very High Resolution Remote Sensing Images Using Deep Convolutional Neural Networks.

PubMed

Tian, Tian; Li, Chang; Xu, Jinkang; Ma, Jiayi

2018-03-18

Detecting urban areas from very high resolution (VHR) remote sensing images plays an important role in the field of Earth observation. The recently-developed deep convolutional neural networks (DCNNs), which can extract rich features from training data automatically, have achieved outstanding performance on many image classification databases. Motivated by this fact, we propose a new urban area detection method based on DCNNs in this paper. The proposed method mainly includes three steps: (i) a visual dictionary is obtained based on the deep features extracted by pre-trained DCNNs; (ii) urban words are learned from labeled images; (iii) the urban regions are detected in a new image based on the nearest dictionary word criterion. The qualitative and quantitative experiments on different datasets demonstrate that the proposed method can obtain a remarkable overall accuracy (OA) and kappa coefficient. Moreover, it can also strike a good balance between the true positive rate (TPR) and false positive rate (FPR).

Loop-mediated isothermal amplification assay targeting the mpb70 gene for rapid differential detection of Mycobacterium bovis.

PubMed

Zhang, Hui; Wang, Zhen; Cao, Xudong; Wang, Zhengrong; Sheng, Jinliang; Wang, Yong; Zhang, Jing; Li, Zhiqiang; Gu, Xinli; Chen, Chuangfu

2016-11-01

Loop-mediated isothermal amplification (LAMP) is a highly sensitive, rapid, cost-effective nucleic acid amplification method. Tuberculosis (TB) is widely popular in the world and it is difficult to cure. The fundamental treatment is to clear the types of TB pathogens such as Mycobacterium bovis (M. bovis), Mycobacterium tuberculosis (M. tuberculosis). In order to detect and diagnose TB early, we constructed the differential diagnostic method of TB. In this study, we used LAMP for detection of M. bovis, based on amplification of the mpb70 gene which is a unique gene in M. bovis strain. The LAMP assay was able to detect only seven copies of the gene per reaction, whereas for the conventional PCR, it was 70 copies. The LAMP was evaluated for its specificity using six strains of five Mycobacterium species and 18 related non-Mycobacterium microorganism strains as controls. The target three Mycobacterium strains were all amplified, and no cross-reaction was found with 18 non-Mycobacterium microorganism strains. TB was detected by two methods, LAMP and conventional PCR (based on mpb70 gene); the positive rates of the two methods were 9.55 and 7.01 %, respectively. Our results indicate that the LAMP method should be a potential tool with high convenience, rapidity, sensitivity and specificity for the diagnosis of TB caused by M. bovis. Most importance is that the use of LAMP as diagnostic method in association with diagnostic tests based on mpb70 gene would allow the differentiation between M. bovis and other Mycobacterium in humans or animals. The LAMP method is actually in order to detect human TB, and it can be used for differential diagnosis in this paper.

Chemosensors for detection of nitroaromatic compounds (explosives)

NASA Astrophysics Data System (ADS)

Zyryanov, G. V.; Kopchuk, D. S.; Kovalev, I. S.; Nosova, E. V.; Rusinov, V. L.; Chupakhin, O. N.

2014-09-01

The key types of low-molecular-mass chemosensors for the detection of nitroaromatic compounds representing energetic substances (explosives) are analyzed. The coordination and chemical properties of these chemosensors and structural features of their complexes with nitroaromatic compounds are considered. The causes and methods for attaining high selectivity of recognition are demonstrated. The primary attention is paid to the use of low-molecular-mass chemosensors for visual detection of explosives of this class by colorimetric and photometric methods. Examples of using photo- and chemiluminescence for this purpose are described. A separate section is devoted to electrochemical methods of detection of nitroaromatic compounds. Data published from 2000 to 2014 are mainly covered. The bibliography includes 245 references.

Ensemble empirical mode decomposition based fluorescence spectral noise reduction for low concentration PAHs

NASA Astrophysics Data System (ADS)

Wang, Shu-tao; Yang, Xue-ying; Kong, De-ming; Wang, Yu-tian

2017-11-01

A new noise reduction method based on ensemble empirical mode decomposition (EEMD) is proposed to improve the detection effect for fluorescence spectra. Polycyclic aromatic hydrocarbons (PAHs) pollutants, as a kind of important current environmental pollution source, are highly oncogenic. Using the fluorescence spectroscopy method, the PAHs pollutants can be detected. However, instrument will produce noise in the experiment. Weak fluorescent signals can be affected by noise, so we propose a way to denoise and improve the detection effect. Firstly, we use fluorescence spectrometer to detect PAHs to obtain fluorescence spectra. Subsequently, noises are reduced by EEMD algorithm. Finally, the experiment results show the proposed method is feasible.

Rapid and sensitive detection of canine parvovirus type 2 by recombinase polymerase amplification.

PubMed

Wang, Jianchang; Liu, Libing; Li, Ruiwen; Wang, Jinfeng; Fu, Qi; Yuan, Wanzhe

2016-04-01

A novel recombinase polymerase amplification (RPA)-based method for detection of canine parvovirus type 2 (CPV-2) was developed. Sensitivity analysis showed that the detection limit of RPA was 10 copies of CPV-2 genomic DNA. RPA amplified both CPV-2a and -2b DNA but did not amplify the template of other important dog viruses (CCoV, PRV or CDV), demonstrating high specificity. The method was further validated with 57 canine fecal samples. An outstanding advantage of RPA is that it is an isothermal reaction and can be performed in a water bath, making RPA a potential alternative method for CPV-2 detection in resource-limited settings.

Detection of Fungi from an Indoor Environment using Loop-mediated Isothermal Amplification (LAMP) Method.

PubMed

Nakayama, Takako; Yamazaki, Takashi; Yo, Ayaka; Tone, Kazuya; Mahdi Alshahni, Mohamed; Fujisaki, Ryuichi; Makimura, Koichi

2017-01-01

　Loop-mediated isothermal amplification (LAMP) is a useful DNA detection method with high specificity and sensitivity. The LAMP reaction is carried out within a short time at a constant temperature without the need for thermal cycling. We developed a LAMP primer set for detecting a wide range of fungi by aligning the sequences of the large subunit ribosomal RNA gene of Candida albicans (Ascomycota), Cryptococcus neoformans (Basidiomycota), and Mucor racemosus (Mucorales). The threshold of C. albicans rDNA as template with our LAMP primer set was in the range of 10-100 copies per a reaction. In this study, we evaluated the correlation between colony forming units (CFU) and LAMP detection rate using the LAMP method for environmental fungi. The LAMP method should be a useful means of detecting fungi in indoor environments, disaster areas, or even in confined manned spacecraft to prevent allergies or infections caused by fungi.

Dual Low-Rank Pursuit: Learning Salient Features for Saliency Detection.

PubMed

Lang, Congyan; Feng, Jiashi; Feng, Songhe; Wang, Jingdong; Yan, Shuicheng

2016-06-01

Saliency detection is an important procedure for machines to understand visual world as humans do. In this paper, we consider a specific saliency detection problem of predicting human eye fixations when they freely view natural images, and propose a novel dual low-rank pursuit (DLRP) method. DLRP learns saliency-aware feature transformations by utilizing available supervision information and constructs discriminative bases for effectively detecting human fixation points under the popular low-rank and sparsity-pursuit framework. Benefiting from the embedded high-level information in the supervised learning process, DLRP is able to predict fixations accurately without performing the expensive object segmentation as in the previous works. Comprehensive experiments clearly show the superiority of the proposed DLRP method over the established state-of-the-art methods. We also empirically demonstrate that DLRP provides stronger generalization performance across different data sets and inherits the advantages of both the bottom-up- and top-down-based saliency detection methods.

Highly sensitive and selective liquid crystal optical sensor for detection of ammonia.

PubMed

Niu, Xiaofang; Zhong, Yuanbo; Chen, Rui; Wang, Fei; Luo, Dan

2017-06-12

Ammonia detection technologies are very important in environment monitoring. However, most existing technologies are complex and expensive, which limit the useful range of real-time application. Here, we propose a highly sensitive and selective optical sensor for detection of ammonia (NH 3 ) based on liquid crystals (LCs). This optical sensor is realized through the competitive binding between ammonia and liquid crystals on chitosan-Cu 2+ that decorated on glass substrate. We achieve a broad detection range of ammonia from 50 ppm to 1250 ppm, with a low detection limit of 16.6 ppm. This sensor is low-cost, simple, fast, and highly sensitive and selective for detection of ammonia. The proposal LC sensing method can be a sensitive detection platform for other molecule monitors such as proteins, DNAs and other heavy metal ions by modifying sensing molecules.

Quantitation of five organophosphorus nerve agent metabolites in serum using hydrophilic interaction liquid chromatography and tandem mass spectrometry

PubMed Central

Hamelin, Elizabeth I.; Schulze, Nicholas D.; Shaner, Rebecca L.; Coleman, Rebecca M.; Lawrence, Richard J.; Crow, Brian S.; Jakubowski, E. M.; Johnson, Rudolph C.

2015-01-01

Although nerve agent use is prohibited, concerns remain for human exposure to nerve agents during decommissioning, research, and warfare. Exposure can be detected through the analysis of the hydrolysis products in urine as well as blood. An analytical method to detect exposure to five nerve agents, including VX, VR (Russian VX), GB (sarin), GD (soman) and GF (cyclosarin), through the analysis of the hydrolysis products, which are the primary metabolites, in serum has been developed and characterized. This method uses solid phase extraction coupled with high performance liquid chromatography for separation and isotopic dilution tandem mass spectrometry for detection. An uncommon buffer of ammonium fluoride was used to enhance ionization and improve sensitivity when coupled with hydrophilic interaction liquid chromatography resulting in detection limits from 0.3–0.5 ng/mL. The assessment of two quality control samples demonstrated high accuracy (101–105%) and high precision (5–8%) for the detection of these five nerve agent hydrolysis products in serum. PMID:24633507

Development of Loop-Mediated Isothermal Amplification (LAMP) Assay for Rapid Detection of Cannabis sativa.

PubMed

Kitamura, Masashi; Aragane, Masako; Nakamura, Kou; Watanabe, Kazuhito; Sasaki, Yohei

2016-07-01

In many parts of the world, the possession and cultivation of Cannabis sativa L. are restricted by law. As chemical or morphological analyses cannot identify the plant in some cases, a simple yet accurate DNA-based method for identifying C. sativa is desired. We have developed a loop-mediated isothermal amplification (LAMP) assay for the rapid identification of C. sativa. By optimizing the conditions for the LAMP reaction that targets a highly conserved region of tetrahydrocannabinolic acid (THCA) synthase gene, C. sativa was identified within 50 min at 60-66°C. The detection limit was the same as or higher than that of conventional PCR. The LAMP assay detected all 21 specimens of C. sativa, showing high specificity. Using a simple protocol, the identification of C. sativa could be accomplished within 90 min from sample treatment to detection without use of special equipment. A rapid, sensitive, highly specific, and convenient method for detecting and identifying C. sativa has been developed and is applicable to forensic investigations and industrial quality control.

Gold nanoparticle labeling with tyramide signal amplification for highly sensitive detection of alpha fetoprotein in human serum by ICP-MS.

PubMed

Li, Xiaoting; Chen, Beibei; He, Man; Xiao, Guangyang; Hu, Bin

2018-01-01

In this work, we developed an immunoassay based on tyramide signal amplification (TSA) and gold nanoparticles (Au NPs) labeling for highly sensitive detection of alpha fetoprotein (AFP) by inductively coupled plasma mass spectrometry (ICP-MS). AFP was captured by anti-AFP1 coating on the 96-well plate and labeled by anti-AFP2-horseradish peroxidase (HRP), in which the HRP can catalyze the deposition of biotinylated tyramine on the nearby protein. Then the streptavidin (SA)-Au NPs was labeled on the deposited biotinylated tyramine as the intensive signal probe for ICP-MS measurement. Under the optimal experimental conditions, the limit of detection of the developed method for AFP was 1.85pg/mL and the linear range was 0.005-2ng/mL. The relative standard deviation for seven replicate detections of 0.01ng/mL AFP was 5.2%. The proposed method was successfully applied to the detection of AFP in human serum with good recoveries. This strategy is highly sensitive and easy to operate, and can be extended to the sensitive detection of other biomolecules in human serum. Copyright © 2017 Elsevier B.V. All rights reserved.

A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

PubMed

Demidov, German; Simakova, Tamara; Vnuchkova, Julia; Bragin, Anton

2016-10-22

Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

Highly sensitive detection of dipicolinic acid with a water-dispersible terbium-metal organic framework.

PubMed

Bhardwaj, Neha; Bhardwaj, Sanjeev; Mehta, Jyotsana; Kim, Ki-Hyun; Deep, Akash

2016-12-15

The sensitive detection of dipicolinic acid (DPA) is strongly associated with the sensing of bacterial organisms in food and many types of environmental samples. To date, the demand for a sensitive detection method for bacterial toxicity has increased remarkably. Herein, we investigated the DPA detection potential of a water-dispersible terbium-metal organic framework (Tb-MOF) based on the fluorescence quenching mechanism. The Tb-MOF showed a highly sensitive ability to detect DPA at a limit of detection of 0.04nM (linear range of detection: 1nM to 5µM) and also offered enhanced selectivity from other commonly associated organic molecules. The present study provides a basis for the application of Tb-MOF for direct, convenient, highly sensitive, and specific detection of DPA in the actual samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Detecting sulphate aerosol geoengineering with different methods

DOE PAGES

Lo, Y. T. Eunice; Charlton-Perez, Andrew J.; Lott, Fraser C.; ...

2016-12-15

Sulphate aerosol injection has been widely discussed as a possible way to engineer future climate. Monitoring it would require detecting its effects amidst internal variability and in the presence of other external forcings. Here, we investigate how the use of different detection methods and filtering techniques affects the detectability of sulphate aerosol geoengineering in annual-mean global-mean near-surface air temperature. This is done by assuming a future scenario that injects 5 Tg yr -1 of sulphur dioxide into the stratosphere and cross-comparing simulations from 5 climate models. 64% of the studied comparisons would require 25 years or more for detection whenmore » no filter and the multi-variate method that has been extensively used for attributing climate change are used, while 66% of the same comparisons would require fewer than 10 years for detection using a trend-based filter. This then highlights the high sensitivity of sulphate aerosol geoengineering detectability to the choice of filter. With the same trend-based filter but a non-stationary method, 80% of the comparisons would require fewer than 10 years for detection. This does not imply sulphate aerosol geoengineering should be deployed, but suggests that both detection methods could be used for monitoring geoengineering in global, annual mean temperature should it be needed.« less

Development of electrochemical sensors for trace detection of explosives and for the detection of chemical warfare agents

NASA Astrophysics Data System (ADS)

Berger, T.; Ziegler, H.; Krausa, Michael

2000-08-01

A huge number of chemical sensors are based on electrochemical measurement methods. Particularly amperometric sensorsystems are employed for the fast detection of pollutants in industry and environment as well as for analytic systems in the medical diagnosis. The large number of different applications of electrochemical sensors is based on the high sensitivity of electrochemical methods and on the wide of possibilities to enhance the selectivity by variation of electrochemical and chemical parameters. Besides this, electrochemical sensorsystems are frequently simple to operate, transportable and cheap. Up to now the electrochemical method of cyclic voltammetry is used only seldom for sensors. Clearly the efficiency of cyclic voltammetry can be seen at the sensorsystem for the detection of nitro- and aminotoluenes in solids and waters as presented here. The potentiodynamic sensors system can be employed for the fast and easy risk estimation of contaminated areas. Because of the high sensitivity of electrochemical methods the detection of chemical substances with a low vapor pressure is possible also. The vapor pressure of TNT at room temperature is 7 ppb for instances. With a special electrochemical set-up we were able to measure TNT approximately 10 cm above a TNT-sample. In addition we were able to estimate TNT in the gaseous phase approximately 10 cm above a real plastic mine. Therefore it seems to be possible to develop an electrochemical mien detection. Moreover, we present that the electrochemical detection of RDX, HMX and chemical warfare agents is also possible.

Real-time explosive particle detection using a cyclone particle concentrator.

PubMed

Hashimoto, Yuichiro; Nagano, Hisashi; Takada, Yasuaki; Kashima, Hideo; Sugaya, Masakazu; Terada, Koichi; Sakairi, Minoru

2014-06-30

There is a need for more rapid methods for the detection of explosive particles. We have developed a novel real-time analysis technique for explosive particles that uses a cyclone particle concentrator. This technique can analyze sample surfaces for the presence of particles from explosives such as TNT and RDX within 3 s, which is much faster than is possible by conventional methods. Particles are detached from the sample surface with air jet pulses, and then introduced into a cyclone particle concentrator with a high pumping speed of about 80 L/min. A vaporizer placed at the bottom of the cyclone particle concentrator immediately converts the particles into a vapor. The vapor is then ionized in the atmospheric pressure chemical ionization (APCI) source of a linear ion trap mass spectrometer. An online connection between the vaporizer and a mass spectrometer enables high-speed detection within a few seconds, compared with the conventional off-line heating method that takes more than 10 s to raise the temperature of a sample filter unit. Since the configuration enriched the number density of explosive particles by about 80 times compared with that without the concentrator, a sub-ng amount of TNT particles on a surface was detectable. The detection limit of our technique is comparable with that of an explosives trace detector using ion mobility spectrometry. The technique will be beneficial for trace detection in security applications, because it detects explosive particles on the surface more speedily than conventional methods. Copyright © 2014 John Wiley & Sons, Ltd.

A Robust Method to Detect Zero Velocity for Improved 3D Personal Navigation Using Inertial Sensors

PubMed Central

Xu, Zhengyi; Wei, Jianming; Zhang, Bo; Yang, Weijun

2015-01-01

This paper proposes a robust zero velocity (ZV) detector algorithm to accurately calculate stationary periods in a gait cycle. The proposed algorithm adopts an effective gait cycle segmentation method and introduces a Bayesian network (BN) model based on the measurements of inertial sensors and kinesiology knowledge to infer the ZV period. During the detected ZV period, an Extended Kalman Filter (EKF) is used to estimate the error states and calibrate the position error. The experiments reveal that the removal rate of ZV false detections by the proposed method increases 80% compared with traditional method at high walking speed. Furthermore, based on the detected ZV, the Personal Inertial Navigation System (PINS) algorithm aided by EKF performs better, especially in the altitude aspect. PMID:25831086

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Development of a cyclic voltammetry method for the detection of Clostridium novyi in black disease.

PubMed

Liu, L L; Jiang, D N; Xiang, G M; Liu, C; Yu, J C; Pu, X Y

2014-03-17

Black disease is an acute disease of sheep and cattle. The pathogen is the obligate anaerobe, Clostridium novyi. Due to difficulties of anaerobic culturing in the country or disaster sites, a simple, rapid, and sensitive method is required. In this study, an electrochemical method, the cyclic voltammetry method, basing on loop-mediated isothermal amplification (LAMP), electrochemical ion bonding (positive dye, methylene blue), was introduced. DNA extracted from C. novyi specimens was amplified through the LAMP reaction. Then the products combined were with methylene blue, which lead to a reduction in the oxidation peak current (ipA) and the reduction peak current (ipC) of the cyclic voltammetry. The changes of ipA/ipC were real-time measured by special designed electrode, so the DNA was quantitatively detected. The results displayed that this electrochemical detection of C. novyi could be completed in 1-2 h with the lowest bacterial concentration of 10(2) colony forming units/mL, and high accuracy (96.5%), sensitivity (96%), and specificity (97%) compared to polymerase chain reation. The cyclic voltammetry method was a simple and fast method, with high sensitivity and high specificity, and has great potential to be a usable molecular tool for fast diagnosis of Black disease.

Topiramate: A Review of Analytical Approaches for the Drug Substance, Its Impurities and Pharmaceutical Formulations.

PubMed

Pinto, Eduardo Costa; Dolzan, Maressa Danielli; Cabral, Lucio Mendes; Armstrong, Daniel W; de Sousa, Valéria Pereira

2016-02-01

An important step during the development of high-performance liquid chromatography (HPLC) methods for quantitative analysis of drugs is choosing the appropriate detector. High sensitivity, reproducibility, stability, wide linear range, compatibility with gradient elution, non-destructive detection of the analyte and response unaffected by changes in the temperature/flow are some of the ideal characteristics of a universal HPLC detector. Topiramate is an anticonvulsant drug mainly used for the treatment of different types of seizures and prophylactic treatment of migraine. Different analytical approaches to quantify topiramate by HPLC have been described because of the lack of chromophoric moieties on its structure, such as derivatization with fluorescent moieties and UV-absorbing moieties, conductivity detection, evaporative light scattering detection, refractive index detection, chemiluminescent nitrogen detection and MS detection. Some methods for the determination of topiramate by capillary electrophoresis and gas chromatography have also been published. This systematic review provides a description of the main analytical methods presented in the literature to analyze topiramate in the drug substance and in pharmaceutical formulations. Each of these methods is briefly discussed, especially considering the detector used with HPLC. In addition, this article presents a review of the data available regarding topiramate stability, degradation products and impurities. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Highly sensitive electrochemical detection of human telomerase activity based on bio-barcode method.

PubMed

Li, Ying; Liu, Bangwei; Li, Xia; Wei, Qingli

2010-07-15

In the present study, an electrochemical method for highly sensitive detection of human telomerase activity was developed based on bio-barcode amplification assay. Telomerase was extracted from HeLa cells, then the extract was mixed with telomerase substrate (TS) primer to perform extension reaction. The extension product was hybridized with the capture DNA immobilized on the Au electrode and then reacted with the signal DNA on Au nanoparticles to form a sandwich hybridization mode. Electrochemical signals were generated by chronocoulometric interrogation of [Ru(NH(3))(6)](3+) that quantitatively binds to the DNA on Au nanoparticles via electrostatic interaction. This method can detect the telomerase activity from as little as 10 cultured cancer cells without the polymerase chain reaction (PCR) amplification of telomerase extension product. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Detection of Multiple Stationary Humans Using UWB MIMO Radar.

PubMed

Liang, Fulai; Qi, Fugui; An, Qiang; Lv, Hao; Chen, Fuming; Li, Zhao; Wang, Jianqi

2016-11-16

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls.

A novel, sensitive and label-free loop-mediated isothermal amplification detection method for nucleic acids using luminophore dyes.

PubMed

Roy, Sharmili; Wei, Sim Xiao; Ying, Jean Liew Zhi; Safavieh, Mohammadali; Ahmed, Minhaz Uddin

2016-12-15

Electrochemiluminescence (ECL) has been widely rendered for nucleic acid testing. Here, we integrate loop-mediated isothermal amplification (LAMP) with ECL technique for DNA detection and quantification. The target LAMP DNA bound electrostatically with [Ru(bpy)3](+2) on the carbon electrode surface, and an ECL reaction was triggered by tripropylamine (TPrA) to yield luminescence. We illustrated this method as a new and highly sensitive strategy for the detection of sequence-specific DNA from different meat species at picogram levels. The proposed strategy renders the signal amplification capacities of TPrA and combines LAMP with inherently high sensitivity of the ECL technique, to facilitate the detection of low quantities of DNA. By leveraging this technique, target DNA of Sus scrofa (pork) meat was detected as low as 1pg/µL (3.43×10(-1)copies/µL). In addition, the proposed technique was applied for detection of Bacillus subtilis DNA samples and detection limit of 10pg/µL (2.2×10(3)copies/µL) was achieved. The advantages of being isothermal, sensitive and robust with ability for multiplex detection of bio-analytes makes this method a facile and appealing sensing modality in hand-held devices to be used at the point-of-care (POC). Copyright © 2016 Elsevier B.V. All rights reserved.

Detection of Multiple Stationary Humans Using UWB MIMO Radar

PubMed Central

Liang, Fulai; Qi, Fugui; An, Qiang; Lv, Hao; Chen, Fuming; Li, Zhao; Wang, Jianqi

2016-01-01

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls. PMID:27854356

MicroRNA Detection by Whole-Mount In Situ Hybridization in C. elegans.

PubMed

Andachi, Yoshiki; Kohara, Yuji

2018-01-01

MicroRNAs (miRNAs) loaded on argonaute proteins guide RNA-induced silencing complexes to target mRNAs. An excellent method to decipher the spatiotemporal expression patterns of miRNAs is whole-mount in situ hybridization (WISH), which has been successfully used in vertebrate embryos but still remains unavailable for many animal species. Here, we describe a WISH method for miRNA detection in Caenorhabditis elegans at both embryonic and post-embryonic stages. Strategies devised for detection include fixation of animals with carbodiimide at a high temperature and subsequent partial digestion of the fixed animals with an extremely high concentration of proteinase. WISH signals are visualized by staining with a chromogenic substrate or a fluorescent dye.

Serine Protease Zymography: Low-Cost, Rapid, and Highly Sensitive RAMA Casein Zymography.

PubMed

Yasumitsu, Hidetaro

2017-01-01

To detect serine protease activity by zymography, casein and CBB stain have been used as a substrate and a detection procedure, respectively. Casein zymography has been using substrate concentration at 1 mg/mL and employing conventional CBB stain. Although ordinary casein zymography provides reproducible results, it has several disadvantages including time-consuming and relative low sensitivity. Improved casein zymography, RAMA casein zymography, is rapid and highly sensitive. RAMA casein zymography completes the detection process within 1 h after incubation and increases the sensitivity at least by tenfold. In addition to serine protease, the method also detects metalloprotease 7 (MMP7, Matrilysin) with high sensitivity.

Rapid detection of multiple class pharmaceuticals in both municipal wastewater and sludge with ultra high performance liquid chromatography tandem mass spectrometry.

PubMed

Yuan, Xiangjuan; Qiang, Zhimin; Ben, Weiwei; Zhu, Bing; Liu, Junxin

2014-09-01

This work described the development, optimization and validation of an analytical method for rapid detection of multiple-class pharmaceuticals in both municipal wastewater and sludge samples based on ultrasonic solvent extraction, solid-phase extraction, and ultra high performance liquid chromatography-tandem mass spectrometry quantification. The results indicated that the developed method could effectively extract all the target pharmaceuticals (25) in a single process and analyze them within 24min. The recoveries of the target pharmaceuticals were in the range of 69%-131% for wastewater and 54%-130% for sludge at different spiked concentration levels. The method quantification limits in wastewater and sludge ranged from 0.02 to 0.73ng/L and from 0.02 to 1.00μg/kg, respectively. Subsequently, this method was validated and applied for residual pharmaceutical analysis in a wastewater treatment plant located in Beijing, China. All the target pharmaceuticals were detected in the influent samples with concentrations varying from 0.09ng/L (tiamulin) to 15.24μg/L (caffeine); meanwhile, up to 23 pharmaceuticals were detected in sludge samples with concentrations varying from 60ng/kg (sulfamethizole) to 8.55mg/kg (ofloxacin). The developed method demonstrated its selectivity, sensitivity, and reliability for detecting multiple-class pharmaceuticals in complex matrices such as municipal wastewater and sludge. Copyright © 2014. Published by Elsevier B.V.

Deep Whole-Genome Sequencing to Detect Mixed Infection of Mycobacterium tuberculosis

PubMed Central

Gan, Mingyu; Liu, Qingyun; Yang, Chongguang; Gao, Qian; Luo, Tao

2016-01-01

Mixed infection by multiple Mycobacterium tuberculosis (MTB) strains is associated with poor treatment outcome of tuberculosis (TB). Traditional genotyping methods have been used to detect mixed infections of MTB, however, their sensitivity and resolution are limited. Deep whole-genome sequencing (WGS) has been proved highly sensitive and discriminative for studying population heterogeneity of MTB. Here, we developed a phylogenetic-based method to detect MTB mixed infections using WGS data. We collected published WGS data of 782 global MTB strains from public database. We called homogeneous and heterogeneous single nucleotide variations (SNVs) of individual strains by mapping short reads to the ancestral MTB reference genome. We constructed a phylogenomic database based on 68,639 homogeneous SNVs of 652 MTB strains. Mixed infections were determined if multiple evolutionary paths were identified by mapping the SNVs of individual samples to the phylogenomic database. By simulation, our method could specifically detect mixed infections when the sequencing depth of minor strains was as low as 1× coverage, and when the genomic distance of two mixed strains was as small as 16 SNVs. By applying our methods to all 782 samples, we detected 47 mixed infections and 45 of them were caused by locally endemic strains. The results indicate that our method is highly sensitive and discriminative for identifying mixed infections from deep WGS data of MTB isolates. PMID:27391214

Simultaneous detection of perchlorate and bromate using rapid high-performance ion exchange chromatography-tandem mass spectrometry and perchlorate removal in drinking water.

PubMed

West, Danielle M; Mu, Ruipu; Gamagedara, Sanjeewa; Ma, Yinfa; Adams, Craig; Eichholz, Todd; Burken, Joel G; Shi, Honglan

2015-06-01

Perchlorate and bromate occurrence in drinking water causes health concerns due to their effects on thyroid function and carcinogenicity, respectively. The purpose of this study was threefold: (1) to advance a sensitive method for simultaneous rapid detection of perchlorate and bromate in drinking water system, (2) to systematically study the occurrence of these two contaminants in Missouri drinking water treatment systems, and (3) to examine effective sorbents for minimizing perchlorate in drinking water. A rapid high-performance ion exchange chromatography-tandem mass spectrometry (HPIC-MS/MS) method was advanced for simultaneous detection of perchlorate and bromate in drinking water. The HPIC-MS/MS method was rapid, required no preconcentration of the water samples, and had detection limits for perchlorate and bromate of 0.04 and 0.01 μg/L, respectively. The method was applied to determine perchlorate and bromate concentrations in total of 23 selected Missouri drinking water treatment systems during differing seasons. The water systems selected include different source waters: groundwater, lake water, river water, and groundwater influenced by surface water. The concentrations of perchlorate and bromate were lower than or near to method detection limits in most of the drinking water samples monitored. The removal of perchlorate by various adsorbents was studied. A cationic organoclay (TC-99) exhibited effective removal of perchlorate from drinking water matrices.

SuBSENSE: a universal change detection method with local adaptive sensitivity.

PubMed

St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert

2015-01-01

Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online.

Blinded study determination of high sensitivity and specificity microchip electrophoresis-SSCP/HA to detect mutations in the p53 gene.

PubMed

Hestekin, Christa N; Lin, Jennifer S; Senderowicz, Lionel; Jakupciak, John P; O'Connell, Catherine; Rademaker, Alfred; Barron, Annelise E

2011-11-01

Knowledge of the genetic changes that lead to disease has grown and continues to grow at a rapid pace. However, there is a need for clinical devices that can be used routinely to translate this knowledge into the treatment of patients. Use in a clinical setting requires high sensitivity and specificity (>97%) in order to prevent misdiagnoses. Single-strand conformational polymorphism (SSCP) and heteroduplex analysis (HA) are two DNA-based, complementary methods for mutation detection that are inexpensive and relatively easy to implement. However, both methods are most commonly detected by slab gel electrophoresis, which can be labor-intensive, time-consuming, and often the methods are unable to produce high sensitivity and specificity without the use of multiple analysis conditions. Here, we demonstrate the first blinded study using microchip electrophoresis (ME)-SSCP/HA. We demonstrate the ability of ME-SSCP/HA to detect with 98% sensitivity and specificity >100 samples from the p53 gene exons 5-9 in a blinded study in an analysis time of <10 min. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Liquid-phase exfoliated graphene as highly-sensitive sensor for simultaneous determination of endocrine disruptors: diethylstilbestrol and estradiol.

PubMed

Hu, Lintong; Cheng, Qin; Chen, Danchao; Ma, Ming; Wu, Kangbing

2015-01-01

It is quite important to develop convenient and rapid analytical methods for trace levels of endocrine disruptors because they heavily affect health and reproduction of humans and animals. Herein, graphene was easily prepared via one-step exfoliation using N-methyl-2-pyrrolidone as solvent, and then used to construct an electrochemical sensor for highly-sensitive detection of diethylstilbestrol (DES) and estradiol (E2). On the surface of prepared graphene film, two independent and greatly-increased oxidation waves were observed at 0.28V and 0.49V for DES and E2. The remarkable signal enlargements indicated that the detection sensitivity was improved significantly. The influences of pH value, amount of graphene and accumulation time on the oxidation signals of DES and E2 were discussed. As a result, a highly-sensitive and rapid electrochemical method was newly developed for simultaneous detection of DES and E2. The values of detection limit were evaluated to be 10.87 nM and 4.9 nM for DES and E2. Additionally, this new method was successfully used in lake water samples and the accuracy was satisfactory. Copyright © 2014 Elsevier B.V. All rights reserved.

Strong copper(II) species in estuarine and sea waters investigated by a method with high detection window.

PubMed

Alberti, Giancarla; Biesuz, Raffaela; D'Agostino, Girolamo; Scarponi, Giuseppe; Pesavento, Maria

2007-02-15

The distribution of copper(II) in species of different stability in some estuarine and sea water samples (Adriatic Sea) was investigated by a method based on the sorption of the metal ion on a strongly sorbing resin, Chelex 100, whose sorbing properties have been previously characterized. From them, it is possible to predict very high values of detection windows at the considered conditions, for example side reaction coefficient as high as 10(10) at pH 7.5. Strong copper(II) species in equilibrium with Chelex 100 were detected, at concentration 2-20nM, with a reaction coefficient approximately 10(10.6) at pH 7.45 in sea water, strictly depending on the acidity. They represent 50-70% of the total metal ion and are the strongest copper(II) complexes found in sea water. Weak complexes too were detected in all the samples, with reaction coefficient lower than ca. 10(9) at the same pH. The method applied, named resin titration (RT), was described in a previous investigation, and is here modified in order to be carried out on oceanographic boat during a cruise in the Adriatic Sea.

Rapid and sensitive detection of human astrovirus in water samples by loop-mediated isothermal amplification with hydroxynaphthol blue dye.

PubMed

Yang, Bo-Yun; Liu, Xiao-Lu; Wei, Yu-Mei; Wang, Jing-Qi; He, Xiao-Qing; Jin, Yi; Wang, Zi-Jian

2014-02-14

The aim of this paper was to develop a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method for rapid, sensitive and inexpensive detection of astrovirus. The detection limit of LAMP using in vitro RNA transcripts was 3.6 × 10 copies·μL⁻¹, which is as sensitive as the presently used PCR assays. However, the LAMP products could be identified as different colors with the naked eye following staining with hydroxynaphthol blue dye (HNB). No cross-reactivity with other gastroenteric viruses (rotavirus and norovirus) was observed, indicating the relatively high specificity of LAMP. The RT-LAMP method with HNB was used to effectively detect astrovirus in reclaimed water samples. The LAMP technique described in this study is a cheap, sensitive, specific and rapid method for the detection of astrovirus. The RT-LAMP method can be simply applied for the specific detection of astrovirus and has the potential to be utilized in the field as a screening test.

A Support System for Mouse Operations Using Eye-Gaze Input

NASA Astrophysics Data System (ADS)

Abe, Kiyohiko; Nakayama, Yasuhiro; Ohi, Shoichi; Ohyama, Minoru

We have developed an eye-gaze input system for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS) patients. This system utilizes a personal computer and a home video camera to detect eye-gaze under natural light. The system detects both vertical and horizontal eye-gaze by simple image analysis, and does not require special image processing units or sensors. Our conventional eye-gaze input system can detect horizontal eye-gaze with a high degree of accuracy. However, it can only classify vertical eye-gaze into 3 directions (up, middle and down). In this paper, we propose a new method for vertical eye-gaze detection. This method utilizes the limbus tracking method for vertical eye-gaze detection. Therefore our new eye-gaze input system can detect the two-dimension coordinates of user's gazing point. By using this method, we develop a new support system for mouse operation. This system can move the mouse cursor to user's gazing point.

Development of a Sensitive Luciferase-Based Sandwich ELISA System for the Detection of Human Extracellular Matrix 1 Protein.

PubMed

Li, Ya; Li, Yanqing; Zhao, Junli; Zheng, Xiaojing; Mao, Qinwen; Xia, Haibin

2016-12-01

Enzyme-linked immunosorbent assay (ELISA) has been one of the main methods for detecting an antigen in an aqueous sample for more than four decades. Nowadays, one of the biggest concerns for ELISA is still how to improve the sensitivity of the assay, and the luciferase-luciferin reaction system has been noticed as a new detection method with high sensitivity. In this study, a luciferin-luciferase reaction system was used as the detection method for a sandwich ELISA system. It was shown that this new system led to an increase in the detection sensitivity of at least two times when compared with the traditional horseradish peroxidase (HRP) detection method. Lastly, the serum levels of the human extracellular matrix 1 protein of breast cancer patients were determined by the new system, which were overall similar to the HRP chemiluminescent system. Furthermore, this new luciferase reporter can be implemented into other ELISA systems for the purpose of increasing the assay sensitivity.

Next-Generation Genotyping by Digital PCR to Detect and Quantify the BRAF V600E Mutation in Melanoma Biopsies.

PubMed

Lamy, Pierre-Jean; Castan, Florence; Lozano, Nicolas; Montélion, Cécile; Audran, Patricia; Bibeau, Frédéric; Roques, Sylvie; Montels, Frédéric; Laberenne, Anne-Claire

2015-07-01

The detection of the BRAF V600E mutation in melanoma samples is used to select patients who should respond to BRAF inhibitors. Different techniques are routinely used to determine BRAF status in clinical samples. However, low tumor cellularity and tumor heterogeneity can affect the sensitivity of somatic mutation detection. Digital PCR (dPCR) is a next-generation genotyping method that clonally amplifies nucleic acids and allows the detection and quantification of rare mutations. Our aim was to evaluate the clinical routine performance of a new dPCR-based test to detect and quantify BRAF mutation load in 47 paraffin-embedded cutaneous melanoma biopsies. We compared the results obtained by dPCR with high-resolution melting curve analysis and pyrosequencing or with one of the allele-specific PCR methods available on the market. dPCR showed the lowest limit of detection. dPCR and allele-specific amplification detected the highest number of mutated samples. For the BRAF mutation load quantification both dPCR and pyrosequencing gave similar results with strong disparities in allele frequencies in the 47 tumor samples under study (from 0.7% to 79% of BRAF V600E mutations/sample). In conclusion, the four methods showed a high degree of concordance. dPCR was the more-sensitive method to reliably and easily detect mutations. Both pyrosequencing and dPCR could quantify the mutation load in heterogeneous tumor samples. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Diagnostic value of DIAGNOdent in detecting caries under composite restorations of primary molars.

PubMed

Sichani, Ava Vali; Javadinejad, Shahrzad; Ghafari, Roshanak

2016-01-01

Direct observation cannot detect caries under restorations; therefore, the aim of this study was to compare the accuracy of radiographs and DIAGNOdent in detecting caries under restorations in primary teeth using histologic evaluation. A total of 74 previously extracted primary molars (37 with occlusal caries and 37 without caries) were used. Class 1 cavity preparations were made on each tooth by a single clinician and then the preparations were filled with composite resin. The accuracy of radiographs and DIAGNOdent in detecting caries was compared using histologic evaluation. The data were analyzed by SPSS version 21 using Chi-square, Mc Namara statistical tests and receiver operating characteristic curve. The significance was set at 0.05. The sensitivity and specificity for DIAGNOdent were 70.97 and 83.72, respectively. Few false negative results were observed, and the positive predictive value was high (+PV = 75.9) and the area under curve was more than 0.70 therefore making DIAGNOdenta great method for detecting caries (P = 0.0001). Two observers evaluated the radiographs and both observers had low sensitivity ( first observer: 48.39) (second observer: 51.61) and high specificity (both observers: 79.07). The +PV was lower than DIAGNOdent and the area under curve for both observers was less than 0.70. However, the difference between the two methods was not significant. DIAGNOdent showed a greater accuracy in detecting secondary caries under primary molar restorations, compared to radiographs. Although DIAGNOdent is an effective method for detecting caries under composite restorations, it is better to be used as an adjunctive method alongside other detecting procedures.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Bioluminescent bioreporter integrated circuit devices and methods for detecting estrogen

DOEpatents

Simpson, Michael L.; Paulus, Michael J.; Sayler, Gary S.; Applegate, Bruce M.; Ripp, Steven A.

2006-08-15

Bioelectronic devices for the detection of estrogen include a collection of eukaryotic cells which harbor a recombinant lux gene from a high temperature microorganism wherein the gene is operably linked with a heterologous promoter gene. A detectable light-emitting lux gene product is expressed in the presence of the estrogen and detected by the device.

Determination of patulin in apple juice by high-performance liquid chromatography with diode-array detection.

PubMed

Bartolomé, B; Bengoechea, M L; Pérez-Ilzarbe, F J; Hernández, T; Estrella, I; Gómez-Cordovés, C

1994-03-25

A method is described for the detection of patulin in apple juice and the simultaneous determination of the phenolic composition. Spectral data obtained with diode-array detection showed that patulin can be easily distinguished from compounds eluting under the same conditions. The detection limit for patulin was 8.96 micrograms/l.

76 FR 61647 - Receipt of Several Pesticide Petitions Filed for Residues of Pesticide Chemicals in or on Various...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-05

... was required for gas chromatography with mass selective detection (GC/MSD) but not for liquid... detection (LOD = 0.01) and a gas liquid chromatography (GLC) method with a flame photometric detection (LOD... quantification by high performance liquid chromatography with tandem mass spectrometric detection (HPLC/MS/MS...

Detection of reactive oxygen species in mainstream cigarette smoke by a fluorescent probe

NASA Astrophysics Data System (ADS)

Liu, Li; Xu, Shi-jie; Li, Song-zhan

2009-07-01

A mass of reactive oxygen species(ROS) are produced in the process of smoking. Superfluous ROS can induce the oxidative stress in organism, which will cause irreversible damage to cells. Fluorescent probe is taken as a marker of oxidative stress in biology and has been applied to ROS detection in the field of biology and chemistry for high sensitivity, high simplicity of data collection and high resolution. As one type of fluorescent probe, dihydrorhodamine 6G (dR6G) will be oxidized to the fluorescent rhodamine 6G, which could be used to detect ROS in mainstream cigarette smoke. We investigated the action mechanism of ROS on dR6G, built up the standard curve of R6G fluorescence intensity with its content, achieved the variation pattern of R6G fluorescence intensity with ROS content in mainstream cigarette smoke and detected the contents of ROS from the 4 types of cigarettes purchased in market. The result shows that the amount of ROS has close relationship with the types of tobacco and cigarette production technology. Compared with other detecting methods such as electronic spin resonance(ESR), chromatography and mass spectrometry, this detection method by the fluorescent probe has higher efficiency and sensitivity and will have wide applications in the ROS detection field.

Real-time detection of bacterial spores using coherent anti-Stokes Raman spectroscopy

NASA Astrophysics Data System (ADS)

Dogariu, A.; Goltsov, A.; Pestov, D.; Sokolov, A. V.; Scully, M. O.

2008-02-01

We demonstrate a realistic method for detection of anthrax-type spores in real time based on their chemical fingerprints using coherent anti-Stokes Raman scattering. Specifically, we demonstrate that coherent Raman scattering can be used to successfully identify spores with high accuracy and high selectivity in less than 50ms.

Ship detection in panchromatic images: a new method and its DSP implementation

NASA Astrophysics Data System (ADS)

Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Wang, Mengfei; Meng, Gang

2016-03-01

In this paper, a new ship detection method is proposed after analyzing the characteristics of panchromatic remote sensing images and ship targets. Firstly, AdaBoost(Adaptive Boosting) classifiers trained by Haar features are utilized to make coarse detection of ship targets. Then LSD (Line Segment Detector) is adopted to extract the line features in target slices to make fine detection. Experimental results on a dataset of panchromatic remote sensing images with a spatial resolution of 2m show that the proposed algorithm can achieve high detection rate and low false alarm rate. Meanwhile, the algorithm can meet the needs of practical applications on DSP (Digital Signal Processor).

Automated detection of new impact sites on Martian surface from HiRISE images

NASA Astrophysics Data System (ADS)

Xin, Xin; Di, Kaichang; Wang, Yexin; Wan, Wenhui; Yue, Zongyu

2017-10-01

In this study, an automated method for Martian new impact site detection from single images is presented. It first extracts dark areas in full high resolution image, then detects new impact craters within dark areas using a cascade classifier which combines local binary pattern features and Haar-like features trained by an AdaBoost machine learning algorithm. Experimental results using 100 HiRISE images show that the overall detection rate of proposed method is 84.5%, with a true positive rate of 86.9%. The detection rate and true positive rate in the flat regions are 93.0% and 91.5%, respectively.

Depletion of highly abundant proteins in blood plasma by ammonium sulfate precipitation for 2D-PAGE analysis.

PubMed

Mahn, Andrea; Ismail, Maritza

2011-11-15

Ammonium sulfate precipitation (ASP) was explored as a method for depleting some highly abundant proteins from blood plasma, in order to reduce the dynamic range of protein concentration and to improve the detection of low abundance proteins by 2D-PAGE. 40% ammonium sulfate saturation was chosen since it allowed depleting 39% albumin and 82% α-1-antitrypsin. ASP-depletion showed high reproducibility in 2D-PAGE analysis (4.2% variation in relative abundance of albumin), similar to that offered by commercial affinity-depletion columns. Besides, it allowed detecting 59 spots per gel, very close to the number of spots detected in immuno-affinity-depleted plasma. Thus, ASP at 40% saturation is a reliable depletion method that may help in proteomic analysis of blood plasma. Finally, ASP-depletion seems to be complementary to hydrophobic interaction chromatography (HIC)-depletion, and therefore an ASP-step followed by a HIC-step could probably deplete the most highly abundant plasma proteins, thus improving the detection of low abundance proteins by 2D-PAGE. Copyright © 2011 Elsevier B.V. All rights reserved.