Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Function-based classification of carbohydrate-active enzymes by recognition of short, conserved peptide motifs.

PubMed

Busk, Peter Kamp; Lange, Lene

2013-06-01

Functional prediction of carbohydrate-active enzymes is difficult due to low sequence identity. However, similar enzymes often share a few short motifs, e.g., around the active site, even when the overall sequences are very different. To exploit this notion for functional prediction of carbohydrate-active enzymes, we developed a simple algorithm, peptide pattern recognition (PPR), that can divide proteins into groups of sequences that share a set of short conserved sequences. When this method was used on 118 glycoside hydrolase 5 proteins with 9% average pairwise identity and representing four characterized enzymatic functions, 97% of the proteins were sorted into groups correlating with their enzymatic activity. Furthermore, we analyzed 8,138 glycoside hydrolase 13 proteins including 204 experimentally characterized enzymes with 28 different functions. There was a 91% correlation between group and enzyme activity. These results indicate that the function of carbohydrate-active enzymes can be predicted with high precision by finding short, conserved motifs in their sequences. The glycoside hydrolase 61 family is important for fungal biomass conversion, but only a few proteins of this family have been functionally characterized. Interestingly, PPR divided 743 glycoside hydrolase 61 proteins into 16 subfamilies useful for targeted investigation of the function of these proteins and pinpointed three conserved motifs with putative importance for enzyme activity. Furthermore, the conserved sequences were useful for cloning of new, subfamily-specific glycoside hydrolase 61 proteins from 14 fungi. In conclusion, identification of conserved sequence motifs is a new approach to sequence analysis that can predict carbohydrate-active enzyme functions with high precision.

Composite Wavelet Filters for Enhanced Automated Target Recognition

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Target recognition based on convolutional neural network

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

2017-11-01

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Laser range profiling for small target recognition

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Tulldahl, Michael

2016-05-01

The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

Examination of soldier target recognition with direct view optics

NASA Astrophysics Data System (ADS)

Long, Frederick H.; Larkin, Gabriella; Bisordi, Danielle; Dorsey, Shauna; Marianucci, Damien; Goss, Lashawnta; Bastawros, Michael; Misiuda, Paul; Rodgers, Glenn; Mazz, John P.

2017-10-01

Target recognition and identification is a problem of great military and scientific importance. To examine the correlation between target recognition and optical magnification, ten U.S. Army soldiers were tasked with identifying letters on targets at 800 and 1300 meters away. Letters were used since they are a standard method for measuring visual acuity. The letters were approximately 90 cm high, which is the size of a well-known rifle. Four direct view optics with angular magnifications of 1.5x, 4x, 6x, and 9x were used. The goal of this approach was to measure actual probabilities for correct target identification. Previous scientific literature suggests that target recognition can be modeled as a linear response problem in angular frequency space using the established values for the contrast sensitivity function for a healthy human eye and the experimentally measured modulation transfer function of the optic. At the 9x magnification, the soldiers could identify the letters with almost no errors (i.e., 97% probability of correct identification). At lower magnification, errors in letter identification were more frequent. The identification errors were not random but occurred most frequently with a few pairs of letters (e.g., O and Q), which is consistent with the literature for letter recognition. In addition, in the small subject sample of ten soldiers, there was considerable variation in the observer recognition capability at 1.5x and a range of 800 meters. This can be directly attributed to the variation in the observer visual acuity.

Target recognitions in multiple-camera closed-circuit television using color constancy

NASA Astrophysics Data System (ADS)

Soori, Umair; Yuen, Peter; Han, Ji Wen; Ibrahim, Izzati; Chen, Wentao; Hong, Kan; Merfort, Christian; James, David; Richardson, Mark

2013-04-01

People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people's dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

Target recognition and phase acquisition by using incoherent digital holographic imaging

NASA Astrophysics Data System (ADS)

Lee, Munseob; Lee, Byung-Tak

2017-05-01

In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

Emotionally conditioning the target-speech voice enhances recognition of the target speech under "cocktail-party" listening conditions.

PubMed

Lu, Lingxi; Bao, Xiaohan; Chen, Jing; Qu, Tianshu; Wu, Xihong; Li, Liang

2018-05-01

Under a noisy "cocktail-party" listening condition with multiple people talking, listeners can use various perceptual/cognitive unmasking cues to improve recognition of the target speech against informational speech-on-speech masking. One potential unmasking cue is the emotion expressed in a speech voice, by means of certain acoustical features. However, it was unclear whether emotionally conditioning a target-speech voice that has none of the typical acoustical features of emotions (i.e., an emotionally neutral voice) can be used by listeners for enhancing target-speech recognition under speech-on-speech masking conditions. In this study we examined the recognition of target speech against a two-talker speech masker both before and after the emotionally neutral target voice was paired with a loud female screaming sound that has a marked negative emotional valence. The results showed that recognition of the target speech (especially the first keyword in a target sentence) was significantly improved by emotionally conditioning the target speaker's voice. Moreover, the emotional unmasking effect was independent of the unmasking effect of the perceived spatial separation between the target speech and the masker. Also, (skin conductance) electrodermal responses became stronger after emotional learning when the target speech and masker were perceptually co-located, suggesting an increase of listening efforts when the target speech was informationally masked. These results indicate that emotionally conditioning the target speaker's voice does not change the acoustical parameters of the target-speech stimuli, but the emotionally conditioned vocal features can be used as cues for unmasking target speech.

Target Recognition Using Neural Networks for Model Deformation Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hibler, David L.

1999-01-01

Optical measurements provide a non-invasive method for measuring deformation of wind tunnel models. Model deformation systems use targets mounted or painted on the surface of the model to identify known positions, and photogrammetric methods are used to calculate 3-D positions of the targets on the model from digital 2-D images. Under ideal conditions, the reflective targets are placed against a dark background and provide high-contrast images, aiding in target recognition. However, glints of light reflecting from the model surface, or reduced contrast caused by light source or model smoothness constraints, can compromise accurate target determination using current algorithmic methods. This paper describes a technique using a neural network and image processing technologies which increases the reliability of target recognition systems. Unlike algorithmic methods, the neural network can be trained to identify the characteristic patterns that distinguish targets from other objects of similar size and appearance and can adapt to changes in lighting and environmental conditions.

Target recognition of ladar range images using even-order Zernike moments.

PubMed

Liu, Zheng-Jun; Li, Qi; Xia, Zhi-Wei; Wang, Qi

2012-11-01

Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames

Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

Cat-eye effect target recognition with single-pixel detectors

NASA Astrophysics Data System (ADS)

Jian, Weijian; Li, Li; Zhang, Xiaoyue

2015-12-01

A prototype of cat-eye effect target recognition with single-pixel detectors is proposed. Based on the framework of compressive sensing, it is possible to recognize cat-eye effect targets by projecting a series of known random patterns and measuring the backscattered light with three single-pixel detectors in different locations. The prototype only requires simpler, less expensive detectors and extends well beyond the visible spectrum. The simulations are accomplished to evaluate the feasibility of the proposed prototype. We compared our results to that obtained from conventional cat-eye effect target recognition methods using area array sensor. The experimental results show that this method is feasible and superior to the conventional method in dynamic and complicated backgrounds.

Model-based recognition of 3D articulated target using ladar range data.

PubMed

Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

2015-06-10

Ladar is suitable for 3D target recognition because ladar range images can provide rich 3D geometric surface information of targets. In this paper, we propose a part-based 3D model matching technique to recognize articulated ground military vehicles in ladar range images. The key of this approach is to solve the decomposition and pose estimation of articulated parts of targets. The articulated components were decomposed into isolate parts based on 3D geometric properties of targets, such as surface point normals, data histogram distribution, and data distance relationships. The corresponding poses of these separate parts were estimated through the linear characteristics of barrels. According to these pose parameters, all parts of the target were roughly aligned to 3D point cloud models in a library and fine matching was finally performed to accomplish 3D articulated target recognition. The recognition performance was evaluated with 1728 ladar range images of eight different articulated military vehicles with various part types and orientations. Experimental results demonstrated that the proposed approach achieved a high recognition rate.

Endothelial Targeting of Semi-permeable Polymer Nanocarriers for Enzyme Therapies

PubMed Central

Dziubla, Thomas D; Shuvaev, Vladimir V.; Hong, Nan Kang; Hawkins, Brian; Muniswamy, Madesh; Takano, Hajime; Simone, Eric; Nakada, Marian T.; Fisher, Aron; Albelda, Steven M.; Muzykantov, Vladimir R.

2007-01-01

The medical utility of proteins, e.g. therapeutic enzymes, is greatly restricted by their liable nature and inadequate delivery. Most therapeutic enzymes do not accumulate in their targets and are inactivated by proteases. Targeting of enzymes encapsulated into substrate-permeable Polymeric Nano-Carriers (PNC) impermeable for proteases might overcome these limitations. To test this hypothesis, we designed endothelial targeted PNC loaded with catalase, the H2O2-detoxifying enzyme, and tested if this approach protects against vascular oxidative stress, a pathological process implicated in ischemia-reperfusion and other disease conditions. Encapsulation of catalase (MW 240KD), peroxidase (MW 42kD) and xanthine oxidase (XO, MW 300 kD) into ~300nm diameter PNC composed of co-polymers of PEG-PLGA (polyethylene glycol and poly-lactic/poly-glycolic acid) was in the range ~10% for all enzymes. PNC/catalase and PNC/peroxidase were protected from external proteolysis and exerted the enzymatic activity on their PNC diffusible substrates, H2O2 and ortho-phenylendiamine, whereas activity of encapsulated XO was negligible due to polymer impermeability to the substrate. PNC targeted to platelet-endothelial cell adhesion molecule-1 delivered active encapsulated catalase to endothelial cells and protected the endothelium against oxidative stress in cell culture and animal studies. Vascular targeting of PNC-loaded detoxifying enzymes may find wide medical applications including management of oxidative stress and other toxicities. PMID:17950837

Object recognition of real targets using modelled SAR images

NASA Astrophysics Data System (ADS)

Zherdev, D. A.

2017-12-01

In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark; Selinsky, T.

2002-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark

2003-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

A fusion approach for coarse-to-fine target recognition

NASA Astrophysics Data System (ADS)

Folkesson, Martin; Grönwall, Christina; Jungert, Erland

2006-04-01

A fusion approach in a query based information system is presented. The system is designed for querying multimedia data bases, and here applied to target recognition using heterogeneous data sources. The recognition process is coarse-to-fine, with an initial attribute estimation step and a following matching step. Several sensor types and algorithms are involved in each of these two steps. An independence of the matching results, on the origin of the estimation results, is observed. It allows for distribution of data between algorithms in an intermediate fusion step, without risk of data incest. This increases the overall chance of recognising the target. An implementation of the system is described.

A robust recognition and accurate locating method for circular coded diagonal target

NASA Astrophysics Data System (ADS)

Bao, Yunna; Shang, Yang; Sun, Xiaoliang; Zhou, Jiexin

2017-10-01

As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.

Testing Saliency Parameters for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Pandya, Sagar

2012-01-01

A bottom-up visual attention model (the saliency model) is tested to enhance the performance of Automated Target Recognition (ATR). JPL has developed an ATR system that identifies regions of interest (ROI) using a trained OT-MACH filter, and then classifies potential targets as true- or false-positives using machine-learning techniques. In this project, saliency is used as a pre-processing step to reduce the space for performing OT-MACH filtering. Saliency parameters, such as output level and orientation weight, are tuned to detect known target features. Preliminary results are promising and future work entails a rigrous and parameter-based search to gain maximum insight about this method.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

Radioligand Recognition of Insecticide Targets.

PubMed

Casida, John E

2018-04-04

Insecticide radioligands allow the direct recognition and analysis of the targets and mechanisms of toxic action critical to effective and safe pest control. These radioligands are either the insecticides themselves or analogs that bind at the same or coupled sites. Preferred radioligands and their targets, often in both insects and mammals, are trioxabicyclooctanes for the γ-aminobutyric acid (GABA) receptor, avermectin for the glutamate receptor, imidacloprid for the nicotinic receptor, ryanodine and chlorantraniliprole for the ryanodine receptor, and rotenone or pyridaben for NADH + ubiquinone oxidoreductase. Pyrethroids and other Na + channel modulator insecticides are generally poor radioligands due to lipophilicity and high nonspecific binding. For target site validation, the structure-activity relationships competing with the radioligand in the binding assays should be the same as that for insecticidal activity or toxicity except for rapidly detoxified or proinsecticide analogs. Once the radioligand assay is validated for relevance, it will often help define target site modifications on selection of resistant pest strains, selectivity between insects and mammals, and interaction with antidotes and other chemicals at modulator sites. Binding assays also serve for receptor isolation and photoaffinity labeling to characterize the interactions involved.

On-chip learning of hyper-spectral data for real time target recognition

NASA Technical Reports Server (NTRS)

Duong, T. A.; Daud, T.; Thakoor, A.

2000-01-01

As the focus of our present paper, we have used the cascade error projection (CEP) learning algorithm (shown to be hardware-implementable) with on-chip learning (OCL) scheme to obtain three orders of magnitude speed-up in target recognition compared to software-based learning schemes. Thus, it is shown, real time learning as well as data processing for target recognition can be achieved.

Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

NASA Astrophysics Data System (ADS)

Yao, Shoukui; Qin, Xiaojuan

2018-02-01

Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

Single-Molecule View of Small RNA-Guided Target Search and Recognition.

PubMed

Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

2018-05-20

Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

Image-algebraic design of multispectral target recognition algorithms

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.

1994-06-01

In this paper, we discuss methods for multispectral ATR (Automated Target Recognition) of small targets that are sensed under suboptimal conditions, such as haze, smoke, and low light levels. In particular, we discuss our ongoing development of algorithms and software that effect intelligent object recognition by selecting ATR filter parameters according to ambient conditions. Our algorithms are expressed in terms of IA (image algebra), a concise, rigorous notation that unifies linear and nonlinear mathematics in the image processing domain. IA has been implemented on a variety of parallel computers, with preprocessors available for the Ada and FORTRAN languages. An image algebra C++ class library has recently been made available. Thus, our algorithms are both feasible implementationally and portable to numerous machines. Analyses emphasize the aspects of image algebra that aid the design of multispectral vision algorithms, such as parameterized templates that facilitate the flexible specification of ATR filters.

Impact of surfactants on the target recognition of Fab-conjugated PLGA nanoparticles.

PubMed

Kennedy, Patrick J; Perreira, Ines; Ferreira, Daniel; Nestor, Marika; Oliveira, Carla; Granja, Pedro L; Sarmento, Bruno

2018-06-01

Targeted drug delivery with nanoparticles (NPs) requires proper surface ligand presentation and availability. Surfactants are often used as stabilizers in the production of targeted NPs. Here, we evaluated the impact of surfactants on ligand functionalization and downstream molecular recognition. Our model system consisted of fluorescent poly(lactic-co-glycolic acid) (PLGA) NPs that were nanoprecipitated in one of a small panel of commonly-used surfactants followed by equivalent washes and conjugation of an engineered Fab antibody fragment. Size, polydispersity index and zeta potential were determined by dynamic light scattering and laser Doppler anemometry, and Fab presence on the NPs was assessed by enzyme-linked immunosorbent assay. Most importantly, Fab-decorated NP binding to the cell surface receptor was monitored by fluorescence-activated cell sorting. 2% polyvinyl alcohol, 1% sodium cholate, 0.5% Pluronic F127 (F127) and 2% Tween-80 were initially tested. Of the four surfactants tested, PLGA NPs in 0.5% F127 and 2% Tween-80 had the highest cell binding. These two surfactants were then retested in two different concentrations, 0.5% and 2%. The Fab-decorated PLGA NPs in 2% F127 had the highest cell binding. This study highlights the impact of common surfactants and their concentrations on the downstream targeting of ligand-decorated NPs. Similar principles should be applied in the development of future targeted nanosystems where surfactants are employed. Copyright © 2018 Elsevier B.V. All rights reserved.

Anodal tDCS targeting the right orbitofrontal cortex enhances facial expression recognition

PubMed Central

Murphy, Jillian M.; Ridley, Nicole J.; Vercammen, Ans

2015-01-01

The orbitofrontal cortex (OFC) has been implicated in the capacity to accurately recognise facial expressions. The aim of the current study was to determine if anodal transcranial direct current stimulation (tDCS) targeting the right OFC in healthy adults would enhance facial expression recognition, compared with a sham condition. Across two counterbalanced sessions of tDCS (i.e. anodal and sham), 20 undergraduate participants (18 female) completed a facial expression labelling task comprising angry, disgusted, fearful, happy, sad and neutral expressions, and a control (social judgement) task comprising the same expressions. Responses on the labelling task were scored for accuracy, median reaction time and overall efficiency (i.e. combined accuracy and reaction time). Anodal tDCS targeting the right OFC enhanced facial expression recognition, reflected in greater efficiency and speed of recognition across emotions, relative to the sham condition. In contrast, there was no effect of tDCS to responses on the control task. This is the first study to demonstrate that anodal tDCS targeting the right OFC boosts facial expression recognition. This finding provides a solid foundation for future research to examine the efficacy of this technique as a means to treat facial expression recognition deficits, particularly in individuals with OFC damage or dysfunction. PMID:25971602

DNA Looping Facilitates Targeting of a Chromatin Remodeling Enzyme

PubMed Central

Yadon, Adam N; Singh, Badri Nath; Hampsey, Michael; Tsukiyama, Toshio

2013-01-01

Summary ATP-dependent chromatin remodeling enzymes are highly abundant and play pivotal roles regulating DNA-dependent processes. The mechanisms by which they are targeted to specific loci have not been well understood on a genome-wide scale. Here we present evidence that a major targeting mechanism for the Isw2 chromatin remodeling enzyme to specific genomic loci is through sequence-specific transcription factor (TF)-dependent recruitment. Unexpectedly, Isw2 is recruited in a TF-dependent fashion to a large number of loci without TF binding sites. Using the 3C assay, we show that Isw2 can be targeted by Ume6- and TFIIB-dependent DNA looping. These results identify DNA looping as a previously unknown mechanism for the recruitment of a chromatin remodeling enzyme and defines a novel function for DNA looping. We also present evidence suggesting that Ume6-dependent DNA looping is involved in chromatin remodeling and transcriptional repression, revealing a mechanism by which the three-dimensional folding of chromatin affects DNA-dependent processes. PMID:23478442

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

Human β-glucuronidase: structure, function, and application in enzyme replacement therapy.

PubMed

Naz, Huma; Islam, Asimul; Waheed, Abdul; Sly, William S; Ahmad, Faizan; Hassan, Imtaiyaz

2013-10-01

Lysosomal storage diseases occur due to incomplete metabolic degradation of macromolecules by various hydrolytic enzymes in the lysosome. Despite structural differences, most of the lysosomal enzymes share many common features including a lysosomal targeting motif and phosphotransferase recognition sites. β-Glucuronidase (GUSB) is an important lysosomal enzyme involved in the degradation of glucuronate-containing glycosaminoglycan. The deficiency of GUSB causes mucopolysaccharidosis type VII (MPSVII), leading to lysosomal storage in the brain. GUSB is a well-studied protein for its expression, sequence, structure, and function. The purpose of this review is to summarize our current understanding of sequence, structure, function, and evolution of GUSB and its lysosomal enzyme targeting. Enzyme replacement therapy reported for this protein is also discussed.

Protein-targeted corona phase molecular recognition

PubMed Central

Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

2016-01-01

Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

An automatic target recognition system based on SAR image

NASA Astrophysics Data System (ADS)

Li, Qinfu; Wang, Jinquan; Zhao, Bo; Luo, Furen; Xu, Xiaojian

2009-10-01

In this paper, an automatic target recognition (ATR) system based on synthetic aperture radar (SAR) is proposed. This ATR system can play an important role in the simulation of up-to-data battlefield environment and be used in ATR research. To establish an integral and available system, the processing of SAR image was divided into four main stages which are de-noise, detection, cluster-discrimination and segment-recognition, respectively. The first three stages are used for searching region of interest (ROI). Once the ROIs are extracted, the recognition stage will be taken to compute the similarity between the ROIs and the templates in the electromagnetic simulation software National Electromagnetic Scattering Code (NESC). Due to the lack of the SAR raw data, the electromagnetic simulated images are added to the measured SAR background to simulate the battlefield environment8. The purpose of the system is to find the ROIs which can be the artificial military targets such as tanks, armored cars and so on and to categorize the ROIs into the right classes according to the existing templates. From the results we can see that the proposed system achieves a satisfactory result.

The research of multi-frame target recognition based on laser active imaging

NASA Astrophysics Data System (ADS)

Wang, Can-jin; Sun, Tao; Wang, Tin-feng; Chen, Juan

2013-09-01

Laser active imaging is fit to conditions such as no difference in temperature between target and background, pitch-black night, bad visibility. Also it can be used to detect a faint target in long range or small target in deep space, which has advantage of high definition and good contrast. In one word, it is immune to environment. However, due to the affect of long distance, limited laser energy and atmospheric backscatter, it is impossible to illuminate the whole scene at the same time. It means that the target in every single frame is unevenly or partly illuminated, which make the recognition more difficult. At the same time the speckle noise which is common in laser active imaging blurs the images . In this paper we do some research on laser active imaging and propose a new target recognition method based on multi-frame images . Firstly, multi pulses of laser is used to obtain sub-images for different parts of scene. A denoising method combined homomorphic filter with wavelet domain SURE is used to suppress speckle noise. And blind deconvolution is introduced to obtain low-noise and clear sub-images. Then these sub-images are registered and stitched to combine a completely and uniformly illuminated scene image. After that, a new target recognition method based on contour moments is proposed. Firstly, canny operator is used to obtain contours. For each contour, seven invariant Hu moments are calculated to generate the feature vectors. At last the feature vectors are input into double hidden layers BP neural network for classification . Experiments results indicate that the proposed algorithm could achieve a high recognition rate and satisfactory real-time performance for laser active imaging.

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.

2011-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

Bioinspired Pollen-Like Hierarchical Surface for Efficient Recognition of Target Cancer Cells.

PubMed

Wang, Wenshuo; Yang, Gao; Cui, Haijun; Meng, Jingxin; Wang, Shutao; Jiang, Lei

2017-08-01

The efficient recognition and isolation of rare cancer cells holds great promise for cancer diagnosis and prognosis. In nature, pollens exploit spiky structures to realize recognition and adhesion to stigma. Herein, a bioinspired pollen-like hierarchical surface is developed by replicating the assembly of pollen grains, and efficient and specific recognition to target cancer cells is achieved. The pollen-like surface is fabricated by combining filtering-assisted assembly and soft lithography-based replication of pollen grains of wild chrysanthemum. After modification with a capture agent specific to cancer cells, the pollen-like surface enables the capture of target cancer cells with high efficiency and specificity. In addition, the pollen-like surface not only assures high viability of captured cells but also performs well in cell mixture system and at low cell density. This study represents a good example of constructing cell recognition biointerfaces inspired by pollen-stigma adhesion. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Temporal identity in axonal target layer recognition.

PubMed

Petrovic, Milan; Hummel, Thomas

2008-12-11

The segregation of axon and dendrite projections into distinct synaptic layers is a fundamental principle of nervous system organization and the structural basis for information processing in the brain. Layer-specific recognition molecules that allow projecting neurons to stabilize transient contacts and initiate synaptogenesis have been identified. However, most of the neuronal cell-surface molecules critical for layer organization are expressed broadly in the developing nervous system, raising the question of how these so-called permissive adhesion molecules support synaptic specificity. Here we show that the temporal expression dynamics of the zinc-finger protein sequoia is the major determinant of Drosophila photoreceptor connectivity into distinct synaptic layers. Neighbouring R8 and R7 photoreceptors show consecutive peaks of elevated sequoia expression, which correspond to their sequential target-layer innervation. Loss of sequoia in R7 leads to a projection switch into the R8 recipient layer, whereas a prolonged expression in R8 induces a redirection of their axons into the R7 layer. The sequoia-induced axon targeting is mediated through the ubiquitously expressed Cadherin-N cell adhesion molecule. Our data support a model in which recognition specificity during synaptic layer formation is generated through a temporally restricted axonal competence to respond to broadly expressed adhesion molecules. Because developing neurons innervating the same target area often project in a distinct, birth-order-dependent sequence, temporal identity seems to contain crucial information in generating not only cell type diversity during neuronal division but also connection diversity of projecting neurons.

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

Bi-Spectral Method for Radar Target Recognition

DTIC Science & Technology

2006-12-01

θazimuth=60° and ϕelevation=30° with HV Polarization....................................53 Figure 50 Comparison of Radar Range Profile with Actual...radar systems. A comparison of the NCTR techniques and their relative advantages and disadvantages in target recognition performance is presented. 8...32 f fR i R R c c f fi R R i R R c c A e A e A e ψ ψ π ψ ψ π ψ ψ π ψ ψ

Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

PubMed

Ren, Weitong; Ji, Dongqing; Xu, Xiulian

2018-01-01

The HIV-1 nucleocapsid 7 (NCp7) plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3) recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

Pharmacologic suppression of target cell recognition by engineered T cells expressing chimeric T-cell receptors.

PubMed

Alvarez-Vallina, L; Yañez, R; Blanco, B; Gil, M; Russell, S J

2000-04-01

Adoptive therapy with autologous T cells expressing chimeric T-cell receptors (chTCRs) is of potential interest for the treatment of malignancy. To limit possible T-cell-mediated damage to normal tissues that weakly express the targeted tumor antigen (Ag), we have tested a strategy for the suppression of target cell recognition by engineered T cells. Jurkat T cells were transduced with an anti-hapten chTCR tinder the control of a tetracycline-suppressible promoter and were shown to respond to Ag-positive (hapten-coated) but not to Ag-negative target cells. The engineered T cells were then reacted with hapten-coated target cells at different effector to target cell ratios before and after exposure to tetracycline. When the engineered T cells were treated with tetracycline, expression of the chTCR was greatly decreased and recognition of the hapten-coated target cells was completely suppressed. Tetracycline-mediated suppression of target cell recognition by engineered T cells may be a useful strategy to limit the toxicity of the approach to cancer gene therapy.

Lysosomal enzyme delivery by ICAM-1-targeted nanocarriers bypassing glycosylation- and clathrin-dependent endocytosis.

PubMed

Muro, Silvia; Schuchman, Edward H; Muzykantov, Vladimir R

2006-01-01

Enzyme replacement therapy, a state-of-the-art treatment for many lysosomal storage disorders, relies on carbohydrate-mediated binding of recombinant enzymes to receptors that mediate lysosomal delivery via clathrin-dependent endocytosis. Suboptimal glycosylation of recombinant enzymes and deficiency of clathrin-mediated endocytosis in some lysosomal enzyme-deficient cells limit delivery and efficacy of enzyme replacement therapy for lysosomal disorders. We explored a novel delivery strategy utilizing nanocarriers targeted to a glycosylation- and clathrin-independent receptor, intercellular adhesion molecule (ICAM)-1, a glycoprotein expressed on diverse cell types, up-regulated and functionally involved in inflammation, a hallmark of many lysosomal disorders. We targeted recombinant human acid sphingomyelinase (ASM), deficient in types A and B Niemann-Pick disease, to ICAM-1 by loading this enzyme to nanocarriers coated with anti-ICAM. Anti-ICAM/ASM nanocarriers, but not control ASM or ASM nanocarriers, bound to ICAM-1-positive cells (activated endothelial cells and Niemann-Pick disease patient fibroblasts) via ICAM-1, in a glycosylation-independent manner. Anti-ICAM/ASM nanocarriers entered cells via CAM-mediated endocytosis, bypassing the clathrin-dependent pathway, and trafficked to lysosomes, where delivered ASM displayed stable activity and alleviated lysosomal lipid accumulation. Therefore, lysosomal enzyme targeting using nanocarriers targeted to ICAM-1 bypasses defunct pathways and may improve the efficacy of enzyme replacement therapy for lysosomal disorders, such as Niemann-Pick disease.

Prostate Cancer Relevant Antigens and Enzymes for Targeted Drug Delivery

PubMed Central

Barve, Ashutosh; Jin, Wei; Cheng, Kun

2014-01-01

Chemotherapy is one of the most widely used approaches in combating advanced prostate cancer, but its therapeutic efficacy is usually insufficient due to lack of specificity and associated toxicity. Lack of targeted delivery to prostate cancer cells is also the primary obstacles in achieving feasible therapeutic effect of other promising agents including peptide, protein, and nucleic acid. Consequently, there remains a critical need for strategies to increase the selectivity of anti-prostate cancer agents. This review will focus on various prostate cancer-specific antigens and enzymes that could be exploited for prostate cancer targeted drug delivery. Among various targeting strategies, active targeting is the most advanced approach to specifically deliver drugs to their designated cancer cells. In this approach, drug carriers are modified with targeting ligands that can specifically bind to prostate cancer-specific antigens. Moreover, there are several specific enzymes in the tumor microenvironment of prostate cancer that can be exploited for stimulus-responsive drug delivery systems. These systems can specifically release the active drug in the tumor microenvironment of prostate cancer, leading to enhanced tumor penetration efficiency. PMID:24878184

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Information-based approach to performance estimation and requirements allocation in multisensor fusion for target recognition

NASA Astrophysics Data System (ADS)

Harney, Robert C.

1997-03-01

A novel methodology offering the potential for resolving two of the significant problems of implementing multisensor target recognition systems, i.e., the rational selection of a specific sensor suite and optimal allocation of requirements among sensors, is presented. Based on a sequence of conjectures (and their supporting arguments) concerning the relationship of extractable information content to recognition performance of a sensor system, a set of heuristics (essentially a reformulation of Johnson's criteria applicable to all sensor and data types) is developed. An approach to quantifying the information content of sensor data is described. Coupling this approach with the widely accepted Johnson's criteria for target recognition capabilities results in a quantitative method for comparing the target recognition ability of diverse sensors (imagers, nonimagers, active, passive, electromagnetic, acoustic, etc.). Extension to describing the performance of multiple sensors is straightforward. The application of the technique to sensor selection and requirements allocation is discussed.

Enzyme-triggered Gelation: Targeting Proteases with Internal Cleavage Sites

PubMed Central

Bremmer, Steven C.

2014-01-01

A generalizable method for detecting protease activity via gelation is described. A recognition sequence is used to target the protease of interest while a second protease is used to remove the residual residues from the gelator scaffold. Using this approach, selective assays for both MMP-9 and PSA are demonstrated. PMID:24394494

Redox polymer and probe DNA tethered to gold electrodes for enzyme-amplified amperometric detection of DNA hybridization.

PubMed

Kavanagh, Paul; Leech, Dónal

2006-04-15

The detection of nucleic acids based upon recognition surfaces formed by co-immobilization of a redox polymer mediator and DNA probe sequences on gold electrodes is described. The recognition surface consists of a redox polymer, [Os(2,2'-bipyridine)2(polyvinylimidazole)(10)Cl](+/2+), and a model single DNA strand cross-linked and tethered to a gold electrode via an anchoring self-assembled monolayer (SAM) of cysteamine. Hybridization between the immobilized probe DNA of the recognition surface and a biotin-conjugated target DNA sequence (designed from the ssrA gene of Listeria monocytogenes), followed by addition of an enzyme (glucose oxidase)-avidin conjugate, results in electrical contact between the enzyme and the mediating redox polymer. In the presence of glucose, the current generated due to the catalytic oxidation of glucose to gluconolactone is measured, and a response is obtained that is binding-dependent. The tethering of the probe DNA and redox polymer to the SAM improves the stability of the surface to assay conditions of rigorous washing and high salt concentration (1 M). These conditions eliminate nonspecific interaction of both the target DNA and the enzyme-avidin conjugate with the recognition surfaces. The sensor response increases linearly with increasing concentration of target DNA in the range of 1 x 10(-9) to 2 x 10(-6) M. The detection limit is approximately 1.4 fmol, (corresponding to 0.2 nM of target DNA). Regeneration of the recognition surface is possible by treatment with 0.25 M NaOH solution. After rehybridization of the regenerated surface with the target DNA sequence, >95% of the current is recovered, indicating that the redox polymer and probe DNA are strongly bound to the surface. These results demonstrate the utility of the proposed approach.

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target

Adenylating Enzymes in Mycobacterium tuberculosis as Drug Targets

PubMed Central

Duckworth, Benjamin P.; Nelson, Kathryn M.; Aldrich, Courtney C.

2013-01-01

Adenylation or adenylate-forming enzymes (AEs) are widely found in nature and are responsible for the activation of carboxylic acids to intermediate acyladenylates, which are mixed anhydrides of AMP. In a second reaction, AEs catalyze the transfer of the acyl group of the acyladenylate onto a nucleophilic amino, alcohol, or thiol group of an acceptor molecule leading to amide, ester, and thioester products, respectively. Mycobacterium tuberculosis encodes for more than 60 adenylating enzymes, many of which represent potential drug targets due to their confirmed essentiality or requirement for virulence. Several strategies have been used to develop potent and selective AE inhibitors including high-throughput screening, fragment-based screening, and the rationale design of bisubstrate inhibitors that mimic the acyladenylate. In this review, a comprehensive analysis of the mycobacterial adenylating enzymes will be presented with a focus on the identification of small molecule inhibitors. Specifically, this review will cover the aminoacyl tRNA-synthetases (aaRSs), MenE required for menaquinone synthesis, the FadD family of enzymes including the fatty acyl-AMP ligases (FAAL) and the fatty acyl-CoA ligases (FACLs) involved in lipid metabolism, and the nonribosomal peptide synthetase adenylation enzyme MbtA that is necessary for mycobactin synthesis. Additionally, the enzymes NadE, GuaA, PanC, and MshC involved in the respective synthesis of NAD, guanine, pantothenate, and mycothiol will be discussed as well as BirA that is responsible for biotinylation of the acyl CoA-carboxylases. PMID:22283817

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute.

PubMed

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-06-21

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson-Crick base-pairing even in the 3'-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5' base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region.

The striking similarities between standard, distractor-free, and target-free recognition

PubMed Central

Dobbins, Ian G.

2012-01-01

It is often assumed that observers seek to maximize correct responding during recognition testing by actively adjusting a decision criterion. However, early research by Wallace (Journal of Experimental Psychology: Human Learning and Memory 4:441–452, 1978) suggested that recognition rates for studied items remained similar, regardless of whether or not the tests contained distractor items. We extended these findings across three experiments, addressing whether detection rates or observer confidence changed when participants were presented standard tests (targets and distractors) versus “pure-list” tests (lists composed entirely of targets or distractors). Even when observers were made aware of the composition of the pure-list test, the endorsement rates and confidence patterns remained largely similar to those observed during standard testing, suggesting that observers are typically not striving to maximize the likelihood of success across the test. We discuss the implications for decision models that assume a likelihood ratio versus a strength decision axis, as well as the implications for prior findings demonstrating large criterion shifts using target probability manipulations. PMID:21476108

Automated Target Acquisition, Recognition and Tracking (ATTRACT). Phase 1

NASA Technical Reports Server (NTRS)

Abdallah, Mahmoud A.

1995-01-01

The primary objective of phase 1 of this research project is to conduct multidisciplinary research that will contribute to fundamental scientific knowledge in several of the USAF critical technology areas. Specifically, neural networks, signal processing techniques, and electro-optic capabilities are utilized to solve problems associated with automated target acquisition, recognition, and tracking. To accomplish the stated objective, several tasks have been identified and were executed.

Single-stranded DNA cleavage by divergent CRISPR-Cas9 enzymes

PubMed Central

Ma, Enbo; Harrington, Lucas B.; O’Connell, Mitchell R.; Zhou, Kaihong; Doudna, Jennifer A.

2015-01-01

Summary Double-stranded DNA (dsDNA) cleavage by Cas9 is a hallmark of type II CRISPR-Cas immune systems. Cas9–guide RNA complexes recognize 20-base-pair sequences in DNA and generate a site-specific double-strand break, a robust activity harnessed for genome editing. DNA recognition by all studied Cas9 enzymes requires a protospacer adjacent motif (PAM) next to the target site. We show that Cas9 enzymes from evolutionarily divergent bacteria can recognize and cleave single-stranded DNA (ssDNA) by an RNA-guided, PAM-independent recognition mechanism. Comparative analysis shows that in contrast to the type II-A S. pyogenes Cas9 that is widely used for genome engineering, the smaller type II-C Cas9 proteins have limited dsDNA binding and unwinding activity and promiscuous guide-RNA specificity. These results indicate that inefficiency of type II-C Cas9 enzymes for genome editing results from a limited ability to cleave dsDNA, and suggest that ssDNA cleavage was an ancestral function of the Cas9 enzyme family. PMID:26545076

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

A hierarchical, automated target recognition algorithm for a parallel analog processor

NASA Technical Reports Server (NTRS)

Woodward, Gail; Padgett, Curtis

1997-01-01

A hierarchical approach is described for an automated target recognition (ATR) system, VIGILANTE, that uses a massively parallel, analog processor (3DANN). The 3DANN processor is capable of performing 64 concurrent inner products of size 1x4096 every 250 nanoseconds.

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute

PubMed Central

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-01-01

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson–Crick base-pairing even in the 3′-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5′ base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region. PMID:27325485

Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

NASA Astrophysics Data System (ADS)

Yan, Yue

2018-03-01

A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

Target-context unitization effect on the familiarity-related FN400: a face recognition exclusion task.

PubMed

Guillaume, Fabrice; Etienne, Yann

2015-03-01

Using two exclusion tasks, the present study examined how the ERP correlates of face recognition are affected by the nature of the information to be retrieved. Intrinsic (facial expression) and extrinsic (background scene) visual information were paired with face identity and constituted the exclusion criterion at test time. Although perceptual information had to be taken into account in both situations, the FN400 old-new effect was observed only for old target faces on the expression-exclusion task, whereas it was found for both old target and old non-target faces in the background-exclusion situation. These results reveal that the FN400, which is generally interpreted as a correlate of familiarity, was modulated by the retrieval of intra-item and intrinsic face information, but not by the retrieval of extrinsic information. The observed effects on the FN400 depended on the nature of the information to be retrieved and its relationship (unitization) to the recognition target. On the other hand, the parietal old-new effect (generally described as an ERP correlate of recollection) reflected the retrieval of both types of contextual features equivalently. The current findings are discussed in relation to recent controversies about the nature of the recognition processes reflected by the ERP correlates of face recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Structures of the peptide-modifying radical SAM enzyme SuiB elucidate the basis of substrate recognition.

PubMed

Davis, Katherine M; Schramma, Kelsey R; Hansen, William A; Bacik, John P; Khare, Sagar D; Seyedsayamdost, Mohammad R; Ando, Nozomi

2017-09-26

Posttranslational modification of ribosomally synthesized peptides provides an elegant means for the production of biologically active molecules known as RiPPs (ribosomally synthesized and posttranslationally modified peptides). Although the leader sequence of the precursor peptide is often required for turnover, the exact mode of recognition by the modifying enzymes remains unclear for many members of this class of natural products. Here, we have used X-ray crystallography and computational modeling to examine the role of the leader peptide in the biosynthesis of a homolog of streptide, a recently identified peptide natural product with an intramolecular lysine-tryptophan cross-link, which is installed by the radical S -adenosylmethionine (SAM) enzyme, StrB. We present crystal structures of SuiB, a close ortholog of StrB, in various forms, including apo SuiB, SAM-bound SuiB, and a complex of SuiB with SAM and its peptide substrate, SuiA. Although the N-terminal domain of SuiB adopts a typical RRE (RiPP recognition element) motif, which has been implicated in precursor peptide recognition, we observe binding of the leader peptide in the catalytic barrel rather than the N-terminal domain. Computational simulations support a mechanism in which the leader peptide guides posttranslational modification by positioning the cross-linking residues of the precursor peptide within the active site. Together the results shed light onto binding of the precursor peptide and the associated conformational changes needed for the formation of the unique carbon-carbon cross-link in the streptide family of natural products.

Thermodynamics of DNA target site recognition by homing endonucleases

PubMed Central

Eastberg, Jennifer H.; Smith, Audrey McConnell; Zhao, Lei; Ashworth, Justin; Shen, Betty W.; Stoddard, Barry L.

2007-01-01

The thermodynamic profiles of target site recognition have been surveyed for homing endonucleases from various structural families. Similar to DNA-binding proteins that recognize shorter target sites, homing endonucleases display a narrow range of binding free energies and affinities, mediated by structural interactions that balance the magnitude of enthalpic and entropic forces. While the balance of ΔH and TΔS are not strongly correlated with the overall extent of DNA bending, unfavorable ΔHbinding is associated with unstacking of individual base steps in the target site. The effects of deleterious basepair substitutions in the optimal target sites of two LAGLIDADG homing endonucleases, and the subsequent effect of redesigning one of those endonucleases to accommodate that DNA sequence change, were also measured. The substitution of base-specific hydrogen bonds in a wild-type endonuclease/DNA complex with hydrophobic van der Waals contacts in a redesigned complex reduced the ability to discriminate between sites, due to nonspecific ΔSbinding. PMID:17947319

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

PubMed Central

Peng, Yuan; Qiu, Mengran; Shi, Jianfei; Liu, Liangliang

2018-01-01

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved. PMID:29780407

Integrated approach for automatic target recognition using a network of collaborative sensors.

PubMed

Mahalanobis, Abhijit; Van Nevel, Alan

2006-10-01

We introduce what is believed to be a novel concept by which several sensors with automatic target recognition (ATR) capability collaborate to recognize objects. Such an approach would be suitable for netted systems in which the sensors and platforms can coordinate to optimize end-to-end performance. We use correlation filtering techniques to facilitate the development of the concept, although other ATR algorithms may be easily substituted. Essentially, a self-configuring geometry of netted platforms is proposed that positions the sensors optimally with respect to each other, and takes into account the interactions among the sensor, the recognition algorithms, and the classes of the objects to be recognized. We show how such a paradigm optimizes overall performance, and illustrate the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing position as a sensor parameter.

Research and Development of Target Recognition and Location Crawling Platform based on Binocular Vision

NASA Astrophysics Data System (ADS)

Xu, Weidong; Lei, Zhu; Yuan, Zhang; Gao, Zhenqing

2018-03-01

The application of visual recognition technology in industrial robot crawling and placing operation is one of the key tasks in the field of robot research. In order to improve the efficiency and intelligence of the material sorting in the production line, especially to realize the sorting of the scattered items, the robot target recognition and positioning crawling platform based on binocular vision is researched and developed. The images were collected by binocular camera, and the images were pretreated. Harris operator was used to identify the corners of the images. The Canny operator was used to identify the images. Hough-chain code recognition was used to identify the images. The target image in the image, obtain the coordinates of each vertex of the image, calculate the spatial position and posture of the target item, and determine the information needed to capture the movement and transmit it to the robot control crawling operation. Finally, In this paper, we use this method to experiment the wrapping problem in the express sorting process The experimental results show that the platform can effectively solve the problem of sorting of loose parts, so as to achieve the purpose of efficient and intelligent sorting.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Low, slow, small target recognition based on spatial vision network

NASA Astrophysics Data System (ADS)

Cheng, Zhao; Guo, Pei; Qi, Xin

2018-03-01

Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.

Competitive Deep-Belief Networks for Underwater Acoustic Target Recognition

PubMed Central

Shen, Sheng; Yao, Xiaohui; Sheng, Meiping; Wang, Chen

2018-01-01

Underwater acoustic target recognition based on ship-radiated noise belongs to the small-sample-size recognition problems. A competitive deep-belief network is proposed to learn features with more discriminative information from labeled and unlabeled samples. The proposed model consists of four stages: (1) A standard restricted Boltzmann machine is pretrained using a large number of unlabeled data to initialize its parameters; (2) the hidden units are grouped according to categories, which provides an initial clustering model for competitive learning; (3) competitive training and back-propagation algorithms are used to update the parameters to accomplish the task of clustering; (4) by applying layer-wise training and supervised fine-tuning, a deep neural network is built to obtain features. Experimental results show that the proposed method can achieve classification accuracy of 90.89%, which is 8.95% higher than the accuracy obtained by the compared methods. In addition, the highest accuracy of our method is obtained with fewer features than other methods. PMID:29570642

Recent advances in targeting protein arginine methyltransferase enzymes in cancer therapy.

PubMed

Smith, Emily; Zhou, Wei; Shindiapina, Polina; Sif, Said; Li, Chenglong; Baiocchi, Robert A

2018-05-21

Exploration in the field of epigenetics has revealed the diverse roles of the protein arginine methyltransferase (PRMT) family of proteins in multiple disease states. These findings have led to the development of specific inhibitors and discovery of several new classes of drugs with potential to treat both benign and malignant conditions. Areas covered: We provide an overview on the role of PRMT enzymes in healthy and malignant cells, highlighting the role of arginine methylation in specific pathways relevant to cancer pathogenesis. Additionally, we describe structure and catalytic activity of PRMT and discuss the mechanisms of action of novel small molecule inhibitors of specific members of the arginine methyltransferase family. Expert opinion: As the field of PRMT biology advances, it's becoming clear that this class of enzymes is highly relevant to maintaining normal physiologic processes as well and disease pathogenesis. We discuss the potential impact of PRMT inhibitors as a broad class of drugs, including the pleiotropic effects, off target effects the need for more detailed PRMT-centric interactomes, and finally, the potential for targeting this class of enzymes in clinical development of experimental therapeutics for cancer.

Evaluation of target acquisition difficulty using recognition distance to measure required retinal area

NASA Astrophysics Data System (ADS)

Nilsson, Thomy H.

2001-09-01

The psychophysical method of limits was used to measure the distance at which observers could distinguish military vehicles photographed in natural landscapes. Obtained from the TNO-TM Search_2 dataset, these pictures either were rear-projected 35-mm slides or were presented on a computer monitor. Based on the rationale that more difficult vehicle targets would require more visual pathways for recognition, difficult of acquisition was defined in terms of the relative retinal area required for recognition. Relative retinal area was derived from the inverse square of the recognition distance of a particular vehicle relative to the distance of the vehicle that could be seen furthest away. Results are compared with data on the time required to find the vehicles in these pictures. These comparison indicate recognition distance thresholds can be a suitable means of defining standards for the effectiveness of vital graphic information; and the two methods are complementary with respect to distinguishing different degrees of acquisition difficulty, and together may provide a means to measure the total information processing required for recognition.

Catalase, a remarkable enzyme: targeting the oldest antioxidant enzyme to find a new cancer treatment approach.

PubMed

Glorieux, Christophe; Calderon, Pedro Buc

2017-09-26

This review is centered on the antioxidant enzyme catalase and will present different aspects of this particular protein. Among them: historical discovery, biological functions, types of catalases and recent data with regard to molecular mechanisms regulating its expression. The main goal is to understand the biological consequences of chronic exposure of cells to hydrogen peroxide leading to cellular adaptation. Such issues are of the utmost importance with potential therapeutic extrapolation for various pathologies. Catalase is a key enzyme in the metabolism of H2O2 and reactive nitrogen species, and its expression and localization is markedly altered in tumors. The molecular mechanisms regulating the expression of catalase, the oldest known and first discovered antioxidant enzyme, are not completely elucidated. As cancer cells are characterized by an increased production of reactive oxygen species (ROS) and a rather altered expression of antioxidant enzymes, these characteristics represent an advantage in terms of cell proliferation. Meanwhile, they render cancer cells particularly sensitive to an oxidant insult. In this context, targeting the redox status of cancer cells by modulating catalase expression is emerging as a novel approach to potentiate chemotherapy.

Infrared target simulation environment for pattern recognition applications

NASA Astrophysics Data System (ADS)

Savakis, Andreas E.; George, Nicholas

1994-07-01

The generation of complete databases of IR data is extremely useful for training human observers and testing automatic pattern recognition algorithms. Field data may be used for realism, but require expensive and time-consuming procedures. IR scene simulation methods have emerged as a more economical and efficient alternative for the generation of IR databases. A novel approach to IR target simulation is presented in this paper. Model vehicles at 1:24 scale are used for the simulation of real targets. The temperature profile of the model vehicles is controlled using resistive circuits which are embedded inside the models. The IR target is recorded using an Inframetrics dual channel IR camera system. Using computer processing we place the recorded IR target in a prerecorded background. The advantages of this approach are: (1) the range and 3D target aspect can be controlled by the relative position between the camera and model vehicle; (2) the temperature profile can be controlled by adjusting the power delivered to the resistive circuit; (3) the IR sensor effects are directly incorporated in the recording process, because the real sensor is used; (4) the recorded target can embedded in various types of backgrounds recorded under different weather conditions, times of day etc. The effectiveness of this approach is demonstrated by generating an IR database of three vehicles which is used to train a back propagation neural network. The neural network is capable of classifying vehicle type, vehicle aspect, and relative temperature with a high degree of accuracy.

MicroRNAs: Processing, Maturation, Target Recognition and Regulatory Functions

PubMed Central

Shukla, Girish C.; Singh, Jagjit; Barik, Sailen

2012-01-01

The remarkable discovery of small noncoding microRNAs (miRNAs) and their role in posttranscriptional gene regulation have revealed another fine-tuning step in the expression of genetic information. A large number of cellular pathways, which act in organismal development and are important in health and disease, appear to be modulated by miRNAs. At the molecular level, miRNAs restrain the production of proteins by affecting the stability of their target mRNA and/or by down-regulating their translation. This review attempts to offer a snapshot of aspects of miRNA coding, processing, target recognition and function in animals. Our goal here is to provide the readers with a thought-provoking and mechanistic introduction to the miRNA world rather than with a detailed encyclopedia. PMID:22468167

OTUB1 Co-opts Lys48-Linked Ubiquitin Recognition to Suppress E2 Enzyme Function

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

Juang, Yu-Chi; Landry, Marie-Claude; Sanches, Mario

2012-03-26

Ubiquitylation entails the concerted action of E1, E2, and E3 enzymes. We recently reported that OTUB1, a deubiquitylase, inhibits the DNA damage response independently of its isopeptidase activity. OTUB1 does so by blocking ubiquitin transfer by UBC13, the cognate E2 enzyme for RNF168. OTUB1 also inhibits E2s of the UBE2D and UBE2E families. Here we elucidate the structural mechanism by which OTUB1 binds E2s to inhibit ubiquitin transfer. OTUB1 recognizes ubiquitin-charged E2s through contacts with both donor ubiquitin and the E2 enzyme. Surprisingly, free ubiquitin associates with the canonical distal ubiquitin-binding site on OTUB1 to promote formation of the inhibitedmore » E2 complex. Lys48 of donor ubiquitin lies near the OTUB1 catalytic site and the C terminus of free ubiquitin, a configuration that mimics the products of Lys48-linked ubiquitin chain cleavage. OTUB1 therefore co-opts Lys48-linked ubiquitin chain recognition to suppress ubiquitin conjugation and the DNA damage response.« less

Enzyme-driven metabolomic screening: a proof-of-principle method for discovery of plant defence compounds targeted by pathogens.

PubMed

Carere, Jason; Colgrave, Michelle L; Stiller, Jiri; Liu, Chunji; Manners, John M; Kazan, Kemal; Gardiner, Donald M

2016-11-01

Plants produce a variety of secondary metabolites to defend themselves from pathogen attack, while pathogens have evolved to overcome plant defences by producing enzymes that degrade or modify these defence compounds. However, many compounds targeted by pathogen enzymes currently remain enigmatic. Identifying host compounds targeted by pathogen enzymes would enable us to understand the potential importance of such compounds in plant defence and modify them to make them insensitive to pathogen enzymes. Here, a proof of concept metabolomics-based method was developed to discover plant defence compounds modified by pathogens using two pathogen enzymes with known targets in wheat and tomato. Plant extracts treated with purified pathogen enzymes were subjected to LC-MS, and the relative abundance of metabolites before and after treatment were comparatively analysed. Using two enzymes from different pathogens the in planta targets could be found by combining relatively simple enzymology with the power of untargeted metabolomics. Key to the method is dataset simplification based on natural isotope occurrence and statistical filtering, which can be scripted. The method presented here will aid in our understanding of plant-pathogen interactions and may lead to the development of new plant protection strategies. © 2016 CSIRO. New Phytologist © 2016 New Phytologist Trust.

Assembly and analysis of eukaryotic Argonaute–RNA complexes in microRNA-target recognition

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2015-01-01

Experimental studies have uncovered a variety of microRNA (miRNA)–target duplex structures that include perfect, imperfect and seedless duplexes. However, non-canonical binding modes from imperfect/seedless duplexes are not well predicted by computational approaches, which rely primarily on sequence and secondary structural features, nor have their tertiary structures been characterized because solved structures to date are limited to near perfect, straight duplexes in Argonautes (Agos). Here, we use structural modeling to examine the role of Ago dynamics in assembling viable eukaryotic miRNA-induced silencing complexes (miRISCs). We show that combinations of low-frequency, global modes of motion of Ago domains are required to accommodate RNA duplexes in model human and C. elegans Ago structures. Models of viable miRISCs imply that Ago adopts variable conformations at distinct target sites that generate distorted, imperfect miRNA-target duplexes. Ago's ability to accommodate a duplex is dependent on the region where structural distortions occur: distortions in solvent-exposed seed and 3′-end regions are less likely to produce steric clashes than those in the central duplex region. Energetic analyses of assembled miRISCs indicate that target recognition is also driven by favorable Ago-duplex interactions. Such structural insights into Ago loading and target recognition mechanisms may provide a more accurate assessment of miRNA function. PMID:26432829

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

Enzyme Biosensors for Biomedical Applications: Strategies for Safeguarding Analytical Performances in Biological Fluids

PubMed Central

Rocchitta, Gaia; Spanu, Angela; Babudieri, Sergio; Latte, Gavinella; Madeddu, Giordano; Galleri, Grazia; Nuvoli, Susanna; Bagella, Paola; Demartis, Maria Ilaria; Fiore, Vito; Manetti, Roberto; Serra, Pier Andrea

2016-01-01

Enzyme-based chemical biosensors are based on biological recognition. In order to operate, the enzymes must be available to catalyze a specific biochemical reaction and be stable under the normal operating conditions of the biosensor. Design of biosensors is based on knowledge about the target analyte, as well as the complexity of the matrix in which the analyte has to be quantified. This article reviews the problems resulting from the interaction of enzyme-based amperometric biosensors with complex biological matrices containing the target analyte(s). One of the most challenging disadvantages of amperometric enzyme-based biosensor detection is signal reduction from fouling agents and interference from chemicals present in the sample matrix. This article, therefore, investigates the principles of functioning of enzymatic biosensors, their analytical performance over time and the strategies used to optimize their performance. Moreover, the composition of biological fluids as a function of their interaction with biosensing will be presented. PMID:27249001

The research of edge extraction and target recognition based on inherent feature of objects

NASA Astrophysics Data System (ADS)

Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

2008-03-01

Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots

Two-fold Bioorthogonal Derivatization by Different Formylglycine-Generating Enzymes.

PubMed

Krüger, Tobias; Weiland, Stefanie; Falck, Georg; Gerlach, Marcus; Boschanski, Mareile; Alam, Sarfaraz; Müller, Kristian M; Dierks, Thomas; Sewald, Norbert

2018-03-26

Formylglycine-generating enzymes are of increasing interest in the field of bioconjugation chemistry. They catalyze the site-specific oxidation of a cysteine residue to the aldehyde-containing amino acid C α -formylglycine (FGly). This non-canonical residue can be generated within any desired target protein and can subsequently be used for bioorthogonal conjugation reactions. The prototypic formylglycine-generating enzyme (FGE) and the iron-sulfur protein AtsB display slight variations in their recognition sequences. We designed specific tags in peptides and proteins that were selectively converted by the different enzymes. Combination of the different tag motifs within a single peptide or recombinant protein enabled the independent and consecutive introduction of two formylglycine residues and the generation of heterobifunctionalized protein conjugates. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tumor necrosis factor alpha converting enzyme: an encouraging target for various inflammatory disorders.

PubMed

Bahia, Malkeet S; Silakari, Om

2010-05-01

Tumor necrosis factor alpha is one of the most common pro-inflammatory cytokines responsible for various inflammatory disorders. It plays an important role in the origin and progression of rheumatoid arthritis and also in other autoimmune disease conditions. Some anti-tumor necrosis factor alpha antibodies like Enbrel, Humira and Remicade have been successfully used in these disease conditions as antagonists of tumor necrosis factor alpha. Inhibition of generation of active form of tumor necrosis factor alpha is a promising therapy for various inflammatory disorders. Therefore, the inhibition of an enzyme (tumor necrosis factor alpha converting enzyme), which is responsible for processing inactive form of tumor necrosis factor alpha into its active soluble form, is an encouraging target. Many tumor necrosis factor alpha converting enzyme inhibitors have been the candidates of clinical trials but none of them have reached in to the market because of their broad spectrum inhibitory activity for other matrix metalloproteases. Selectivity of tumor necrosis factor alpha converting enzyme inhibition over matrix metalloproteases is of utmost importance. If selectivity is achieved successfully, side-effects can be over-ruled and this approach may become a novel therapy for treatment of rheumatoid arthritis and other inflammatory disorders. This cytokine not only plays a pivotal role in inflammatory conditions but also in some cancerous conditions. Thus, successful targeting of tumor necrosis factor alpha converting enzyme may result in multifunctional therapy.

Automated target recognition using passive radar and coordinated flight models

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2003-09-01

Rather than emitting pulses, passive radar systems rely on illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. These systems are particularly attractive since they allow receivers to operate without emitting energy, rendering them covert. Many existing passive radar systems estimate the locations and velocities of targets. This paper focuses on adding an automatic target recognition (ATR) component to such systems. Our approach to ATR compares the Radar Cross Section (RCS) of targets detected by a passive radar system to the simulated RCS of known targets. To make the comparison as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. The estimated positions become inputs for an algorithm that uses a coordinated flight model to compute probable aircraft orientation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of several potential target classes as they execute the estimated maneuvers. The RCS is then scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. The Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, so that the RCS can be further scaled. The Rician model compares the RCS of the illuminated aircraft with those of the potential targets. This comparison results in target identification.

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an

Target recognition of ladar range images using slice image: comparison of four improved algorithms

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

An algorithm for automatic target recognition using passive radar and an EKF for estimating aircraft orientation

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.

2005-07-01

Rather than emitting pulses, passive radar systems rely on "illuminators of opportunity," such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

NASA Astrophysics Data System (ADS)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high

Restriction enzyme body doubles and PCR cloning: on the general use of type IIs restriction enzymes for cloning.

PubMed

Tóth, Eszter; Huszár, Krisztina; Bencsura, Petra; Kulcsár, Péter István; Vodicska, Barbara; Nyeste, Antal; Welker, Zsombor; Tóth, Szilvia; Welker, Ervin

2014-01-01

The procedure described here allows the cloning of PCR fragments containing a recognition site of the restriction endonuclease (Type IIP) used for cloning in the sequence of the insert. A Type IIS endonuclease--a Body Double of the Type IIP enzyme--is used to generate the same protruding palindrome. Thus, the insert can be cloned to the Type IIP site of the vector without digesting the PCR product with the same Type IIP enzyme. We achieve this by incorporating the recognition site of a Type IIS restriction enzyme that cleaves the DNA outside of its recognition site in the PCR primer in such a way that the cutting positions straddle the desired overhang sequence. Digestion of the PCR product by the Body Double generates the required overhang. Hitherto the use of Type IIS restriction enzymes in cloning reactions has only been used for special applications, the approach presented here makes Type IIS enzymes as useful as Type IIP enzymes for general cloning purposes. To assist in finding Body Double enzymes, we summarised the available Type IIS enzymes which are potentially useful for Body Double cloning and created an online program (http://group.szbk.u-szeged.hu/welkergr/body_double/index.html) for the selection of suitable Body Double enzymes and the design of the appropriate primers.

Autophagy and Mis-targeting of Therapeutic Enzyme in Skeletal Muscle in Pompe Disease

PubMed Central

Fukuda, Tokiko; Ahearn, Meghan; Roberts, Ashley; Mattaliano, Robert J.; Zaal, Kristien; Ralston, Evelyn; Plotz, Paul H.; Raben, Nina

2009-01-01

Enzyme replacement therapy (ERT) became a reality for patients with Pompe disease, a fatal cardiomyopathy and skeletal muscle myopathy caused by a deficiency of glycogen-degrading lysosomal enzyme acid alpha-glucosidase (GAA). The therapy, which relies on receptor-mediated endocytosis of recombinant human GAA (rhGAA), appears to be effective in cardiac muscle, but less so in skeletal muscle. We have previously shown a profound disturbance of the lysosomal degradative pathway (autophagy) in therapy-resistant muscle of GAA knockout mice (KO). Our findings here demonstrate a progressive age-dependent autophagic build-up in addition to enlargement of glycogen-filled lysosomes in multiple muscle groups in the KO. Trafficking and processing of the therapeutic enzyme along the endocytic pathway appear to be affected by the autophagy. Confocal microscopy of live single muscle fibers exposed to fluorescently labeled rhGAA indicates that a significant portion of the endocytosed enzyme in the KO was trapped as a partially processed form in the autophagic areas instead of reaching its target – the lysosomes. A fluid-phase endocytic marker was similarly mis-targeted and accumulated in vesicular structures within the autophagic areas. These findings may explain why ERT often falls short of reversing the disease process, and point to new avenues for the development of pharmacological intervention. PMID:17008131

Functional cooperation between exonucleases and endonucleases—basis for the evolution of restriction enzymes

PubMed Central

Raghavendra, Nidhanapathi K.; Rao, Desirazu N.

2003-01-01

Many types of restriction enzymes cleave DNA away from their recognition site. Using the type III restriction enzyme, EcoP15I, which cleaves DNA 25–27 bp away from its recognition site, we provide evidence to show that an intact recognition site on the cleaved DNA sequesters the restriction enzyme and decreases the effective concentration of the enzyme. EcoP15I restriction enzyme is shown here to perform only a single round of DNA cleavage. Significantly, we show that an exonuclease activity is essential for EcoP15I restriction enzyme to perform multiple rounds of DNA cleavage. This observation may hold true for all restriction enzymes cleaving DNA sufficiently far away from their recognition site. Our results highlight the importance of functional cooperation in the modulation of enzyme activity. Based on results presented here and other data on well-characterised restriction enzymes, a functional evolutionary hierarchy of restriction enzymes is discussed. PMID:12655005

Network Architecture Predisposes an Enzyme to Either Pharmacologic or Genetic Targeting.

PubMed

Jensen, Karin J; Moyer, Christian B; Janes, Kevin A

2016-02-24

Chemical inhibition and genetic knockdown of enzymes are not equivalent in cells, but network-level mechanisms that cause discrepancies between knockdown and inhibitor perturbations are not understood. Here we report that enzymes regulated by negative feedback are robust to knockdown but susceptible to inhibition. Using the Raf-MEK-ERK kinase cascade as a model system, we find that ERK activation is resistant to genetic knockdown of MEK but susceptible to a comparable degree of chemical MEK inhibition. We demonstrate that negative feedback from ERK to Raf causes this knockdown-versus-inhibitor discrepancy in vivo. Exhaustive mathematical modeling of three-tiered enzyme cascades suggests that this result is general: negative autoregulation or feedback favors inhibitor potency, whereas positive autoregulation or feedback favors knockdown potency. Our findings provide a rationale for selecting pharmacologic versus genetic perturbations in vivo and point out the dangers of using knockdown approaches in search of drug targets.

Enzyme-free homogeneous electrochemical biosensor for DNA assay using toehold-triggered strand displacement reaction coupled with host-guest recognition of Fe3O4@SiO2@β-CD nanocomposites.

PubMed

Jiang, Jingjing; Lin, Xinyi; Ding, Dong; Diao, Guowang

2018-04-17

Taking advantages of the toehold-triggered strand displacement reaction (TSDR) and host-guest interaction of β-cyclodextrin (β-CD), a facile enzyme-free and homogeneous electrochemical sensing strategy was designed for the sensitive assay of target DNA using Fe 3 O 4 @SiO 2 @β-CD nanocomposites and ferrocene-labeled hairpin DNA (H-1) as the capture and electrochemical probes, respectively. Upon addition of target molecule, the initiated TSDR process induced the conformational change of H-1, and subsequently stimulated the dynamic assembly of assist probes (A-1 and A-2) to generate H-1:A-1:A-2 duplex along with the release of target sequence. The released target could drive the next TSDR recycling and finally result in the formation of numerous DNA duplex. After the molecular recognition of Fe 3 O 4 @SiO 2 @β-CD nanocomposites, a large number of duplex were easily separated from the supernatant solution under an external magnetic field, which led to a decreased H-1 concentration in residual solution, concomitant with a remarkable reduction of peak current. Under the optimized conditions, wide linear range (1-5000 pM), low detection limit (0.3 pM), desirable reproducibility, good selectivity, and satisfactory practical analysis were obtained by the combination of the superior recognition capability of β-CD, TSDR-induced signal amplification, and homogeneous electroanalytical method. The proposed detection strategy could offer a universal approach for the monitoring of various biological analytes via the rational design of probe sequences. Copyright © 2018 Elsevier B.V. All rights reserved.

The study of infrared target recognition at sea background based on visual attention computational model

NASA Astrophysics Data System (ADS)

Wang, Deng-wei; Zhang, Tian-xu; Shi, Wen-jun; Wei, Long-sheng; Wang, Xiao-ping; Ao, Guo-qing

2009-07-01

Infrared images at sea background are notorious for the low signal-to-noise ratio, therefore, the target recognition of infrared image through traditional methods is very difficult. In this paper, we present a novel target recognition method based on the integration of visual attention computational model and conventional approach (selective filtering and segmentation). The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The visual attention algorithm searches the salient regions automatically, and represented them by a set of winner points, at the same time, demonstrated the salient regions in terms of circles centered at these winner points. This provides a priori knowledge for the filtering and segmentation process. Based on the winner point, we construct a rectangular region to facilitate the filtering and segmentation, then the labeling operation will be added selectively by requirement. Making use of the labeled information, from the final segmentation result we obtain the positional information of the interested region, label the centroid on the corresponding original image, and finish the localization for the target. The cost time does not depend on the size of the image but the salient regions, therefore the consumed time is greatly reduced. The method is used in the recognition of several kinds of real infrared images, and the experimental results reveal the effectiveness of the algorithm presented in this paper.

Metabolic Diseases Downregulate the Majority of Histone Modification Enzymes, Making a Few Upregulated Enzymes Novel Therapeutic Targets--"Sand Out and Gold Stays".

PubMed

Shao, Ying; Chernaya, Valeria; Johnson, Candice; Yang, William Y; Cueto, Ramon; Sha, Xiaojin; Zhang, Yi; Qin, Xuebin; Sun, Jianxin; Choi, Eric T; Wang, Hong; Yang, Xiao-feng

2016-02-01

To determine whether the expression of histone modification enzymes is regulated in physiological and pathological conditions, we took an experimental database mining approach pioneered in our labs to determine a panoramic expression profile of 164 enzymes in 19 human and 17 murine tissues. We have made the following significant findings: (1) Histone enzymes are differentially expressed in cardiovascular, immune, and other tissues; (2) our new pyramid model showed that heart and T cells are among a few tissues in which histone acetylation/deacetylation, and histone methylation/demethylation are in the highest varieties; and (3) histone enzymes are more downregulated than upregulated in metabolic diseases and regulatory T cell (Treg) polarization/ differentiation, but not in tumors. These results have demonstrated a new working model of "Sand out and Gold stays," where more downregulation than upregulation of histone enzymes in metabolic diseases makes a few upregulated enzymes the potential novel therapeutic targets in metabolic diseases and Treg activity.

Autonomous space target recognition and tracking approach using star sensors based on a Kalman filter.

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.

Enzyme-Encapsulated Liposome-Linked Immunosorbent Assay Enabling Sensitive Personal Glucose Meter Readout for Portable Detection of Disease Biomarkers.

PubMed

Lin, Bingqian; Liu, Dan; Yan, Jinmao; Qiao, Zhi; Zhong, Yunxin; Yan, Jiawei; Zhu, Zhi; Ji, Tianhai; Yang, Chaoyong James

2016-03-23

There is considerable demand for sensitive, selective, and portable detection of disease-associated proteins, particularly in clinical practice and diagnostic applications. Portable devices are highly desired for detection of disease biomarkers in daily life due to the advantages of being simple, rapid, user-friendly, and low-cost. Herein we report an enzyme-encapsulated liposome-linked immunosorbent assay for sensitive detection of proteins using personal glucose meters (PGM) for portable quantitative readout. Liposomes encapsulating a large amount of amyloglucosidase or invertase are surface-coated with recognition elements such as aptamers or antibodies for target recognition. By translating molecular recognition signal into a large amount of glucose with the encapsulated enzyme, disease biomarkers such as thrombin or C-reactive protein (CRP) can be quantitatively detected by a PGM with a high detection limit of 1.8 or 0.30 nM, respectively. With the advantages of portability, ease of use, and low-cost, the method reported here has potential for portable and quantitative detection of various targets for different POC testing scenarios, such as rapid diagnosis in clinic offices, health monitoring at the bedside, and chemical/biochemical safety control in the field.

Improving of enzyme immunoassay for detection and quantification of the target molecules using silver nanoparticles

NASA Astrophysics Data System (ADS)

Syrvatka, Vasyl J.; Slyvchuk, Yurij I.; Rozgoni, Ivan I.; Gevkan, Ivan I.; Overchuk, Marta O.

2014-02-01

Modern routine enzyme immunoassays for detection and quantification of biomolecules have several disadvantages such as high cost, insufficient sensitivity, complexity and long-term execution. The surface plasmon resonance of silver nanoparticles gives reasons of creating new in the basis of simple, highly sensitive and low cost colorimetric assays that can be applied to the detection of small molecules, DNA, proteins and pollutants. The main aim of the study was the improving of enzyme immunoassay for detection and quantification of the target molecules using silver nanoparticles. For this purpose we developed method for synthesis of silver nanoparticles with hyaluronic acid and studied possibility of use these nanoparticles in direct determination of target molecules concentration (in particular proteins) and for improving of enzyme immunoassay. As model we used conventional enzyme immunoassays for determination of progesterone and estradiol concentration. We obtained the possibility to produce silver nanoparticles with hyaluronan homogeneous in size between 10 and 12 nm, soluble and stable in water during long term of storage using modified procedure of silver nanoparticles synthesis. New method allows to obtain silver nanoparticles with strong optical properties at the higher concentrations - 60-90 μg/ml with the peak of absorbance at the wavelength 400 nm. Therefore surface plasmon resonance of silver nanoparticles with hyaluronan and ultraviolet-visible spectroscopy provide an opportunity for rapid determination of target molecules concentration (especial protein). We used silver nanoparticles as enzyme carriers and signal enhancers. Our preliminary data show that silver nanoparticles increased absorbance of samples that allows improving upper limit of determination of estradiol and progesterone concentration.

Specific metal recognition in nickel trafficking

PubMed Central

Higgins, Khadine A.; Carr, Carolyn E.; Maroney, Michael J.

2012-01-01

Nickel is an essential metal for a number of bacterial species that have developed systems for acquiring, delivering and incorporating the metal into target enzymes, and controlling the levels of nickel in cells to avoid toxic effects. As with other transition metals, these trafficking systems must be able to distinguish between the desired metal and other transition metal ions with similar physical and chemical properties. Because there are few enzymes (targets) that require nickel for activity (e.g., E. coli traffics nickel for hydrogenases made under anaerobic conditions and H. pylori requires nickel for hydrogenase and urease that are essential for acid viability), the ‘traffic pattern’ for nickel is relatively simple, and nickel trafficking therefore presents an opportunity to examine a system for the mechanisms that are used to distinguish nickel from other metals. In this review, we describe the details known for examples of uptake permeases, metallochaperones and proteins involved in metallocenter assembly, and nickel metalloregulators. We also illustrate the variety of mechanisms, including molecular recognition in the case of NikA protein and examples of allosteric regulation for HypA, NikR and RcnR, employed to generate specific biological responses to nickel ions. PMID:22970729

Chemogenetic Characterization of Inositol Phosphate Metabolic Pathway Reveals Druggable Enzymes for Targeting Kinetoplastid Parasites.

PubMed

Cestari, Igor; Haas, Paige; Moretti, Nilmar Silvio; Schenkman, Sergio; Stuart, Ken

2016-05-19

Kinetoplastids cause Chagas disease, human African trypanosomiasis, and leishmaniases. Current treatments for these diseases are toxic and inefficient, and our limited knowledge of drug targets and inhibitors has dramatically hindered the development of new drugs. Here we used a chemogenetic approach to identify new kinetoplastid drug targets and inhibitors. We conditionally knocked down Trypanosoma brucei inositol phosphate (IP) pathway genes and showed that almost every pathway step is essential for parasite growth and infection. Using a genetic and chemical screen, we identified inhibitors that target IP pathway enzymes and are selective against T. brucei. Two series of these inhibitors acted on T. brucei inositol polyphosphate multikinase (IPMK) preventing Ins(1,4,5)P3 and Ins(1,3,4,5)P4 phosphorylation. We show that IPMK is functionally conserved among kinetoplastids and that its inhibition is also lethal for Trypanosoma cruzi. Hence, IP enzymes are viable drug targets in kinetoplastids, and IPMK inhibitors may aid the development of new drugs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Conserved water-mediated recognition and dynamics of NAD+ (carboxamide group) to hIMPDH enzyme: water mimic approach toward the design of isoform-selective inhibitor.

PubMed

Bairagya, Hridoy R; Mishra, Deepak K; Mukhopadhyay, Bishnu P; Sekar, K

2014-01-01

Inosine monophosphate dehydrogenase (IMPDH) enzyme involves in GMP biosynthesis pathway. Type I hIMPDH is expressed at lower levels in all cells, whereas type II is especially observed in acute myelogenous leukemia, chronic myelogenous leukemia cancer cells, and 10 ns simulation of the IMP-NAD(+) complex structures (PDB ID. 1B3O and 1JCN) have revealed the presence of a few conserved hydrophilic centers near carboxamide group of NAD(+). Three conserved water molecules (W1, W, and W1') in di-nucleotide binding pocket of enzyme have played a significant role in the recognition of carboxamide group (of NAD(+)) to D274 and H93 residues. Based on H-bonding interaction of conserved hydrophilic (water molecular) centers within IMP-NAD(+)-enzyme complexes and their recognition to NAD(+), some covalent modification at carboxamide group of di-nucleotide (NAD(+)) has been made by substituting the -CONH2group by -CONHNH2 (carboxyl hydrazide group) using water mimic inhibitor design protocol. The modeled structure of modified ligand may, though, be useful for the development of antileukemic agent or it could be act as better inhibitor for hIMPDH-II.

Automatic target recognition apparatus and method

DOEpatents

Baumgart, Chris W.; Ciarcia, Christopher A.

2000-01-01

An automatic target recognition apparatus (10) is provided, having a video camera/digitizer (12) for producing a digitized image signal (20) representing an image containing therein objects which objects are to be recognized if they meet predefined criteria. The digitized image signal (20) is processed within a video analysis subroutine (22) residing in a computer (14) in a plurality of parallel analysis chains such that the objects are presumed to be lighter in shading than the background in the image in three of the chains and further such that the objects are presumed to be darker than the background in the other three chains. In two of the chains the objects are defined by surface texture analysis using texture filter operations. In another two of the chains the objects are defined by background subtraction operations. In yet another two of the chains the objects are defined by edge enhancement processes. In each of the analysis chains a calculation operation independently determines an error factor relating to the probability that the objects are of the type which should be recognized, and a probability calculation operation combines the results of the analysis chains.

Abundant off-target edits from site-directed RNA editing can be reduced by nuclear localization of the editing enzyme.

PubMed

Vallecillo-Viejo, Isabel C; Liscovitch-Brauer, Noa; Montiel-Gonzalez, Maria Fernanda; Eisenberg, Eli; Rosenthal, Joshua J C

2018-01-02

Site-directed RNA editing (SDRE) is a general strategy for making targeted base changes in RNA molecules. Although the approach is relatively new, several groups, including our own, have been working on its development. The basic strategy has been to couple the catalytic domain of an adenosine (A) to inosine (I) RNA editing enzyme to a guide RNA that is used for targeting. Although highly efficient on-target editing has been reported, off-target events have not been rigorously quantified. In this report we target premature termination codons (PTCs) in messages encoding both a fluorescent reporter protein and the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) protein transiently transfected into human epithelial cells. We demonstrate that while on-target editing is efficient, off-target editing is extensive, both within the targeted message and across the entire transcriptome of the transfected cells. By redirecting the editing enzymes from the cytoplasm to the nucleus, off-target editing is reduced without compromising the on-target editing efficiency. The addition of the E488Q mutation to the editing enzymes, a common strategy for increasing on-target editing efficiency, causes a tremendous increase in off-target editing. These results underscore the need to reduce promiscuity in current approaches to SDRE.

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Dual signal amplification for highly sensitive electrochemical detection of uropathogens via enzyme-based catalytic target recycling.

PubMed

Su, Jiao; Zhang, Haijie; Jiang, Bingying; Zheng, Huzhi; Chai, Yaqin; Yuan, Ruo; Xiang, Yun

2011-11-15

We report an ultrasensitive electrochemical approach for the detection of uropathogen sequence-specific DNA target. The sensing strategy involves a dual signal amplification process, which combines the signal enhancement by the enzymatic target recycling technique with the sensitivity improvement by the quantum dot (QD) layer-by-layer (LBL) assembled labels. The enzyme-based catalytic target DNA recycling process results in the use of each target DNA sequence for multiple times and leads to direct amplification of the analytical signal. Moreover, the LBL assembled QD labels can further enhance the sensitivity of the sensing system. The coupling of these two effective signal amplification strategies thus leads to low femtomolar (5fM) detection of the target DNA sequences. The proposed strategy also shows excellent discrimination between the target DNA and the single-base mismatch sequences. The advantageous intrinsic sequence-independent property of exonuclease III over other sequence-dependent enzymes makes our new dual signal amplification system a general sensing platform for monitoring ultralow level of various types of target DNA sequences. Copyright © 2011 Elsevier B.V. All rights reserved.

Infrared target recognition based on improved joint local ternary pattern

NASA Astrophysics Data System (ADS)

Sun, Junding; Wu, Xiaosheng

2016-05-01

This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

Slp-76 is a critical determinant of NK-cell mediated recognition of missing-self targets.

PubMed

Lampe, Kristin; Endale, Mehari; Cashman, Siobhan; Fang, Hao; Mattner, Jochen; Hildeman, David; Hoebe, Kasper

2015-07-01

Absence of MHC class I expression is an important mechanism by which NK cells recognize a variety of target cells, yet the pathways underlying "missing-self" recognition, including the involvement of activating receptors, remain poorly understood. Using ethyl-N-nitrosourea mutagenesis in mice, we identified a germline mutant, designated Ace, with a marked defect in NK cell mediated recognition and elimination of "missing-self" targets. The causative mutation was linked to chromosome 11 and identified as a missense mutation (Thr428Ile) in the SH2 domain of Slp-76-a critical adapter molecule downstream of ITAM-containing surface receptors. The Slp-76 Ace mutation behaved as a hypomorphic allele-while no major defects were observed in conventional T-cell development/function, a marked defect in NK cell mediated elimination of β2-microglobulin (β2M) deficient target cells was observed. Further studies revealed Slp-76 to control NK-cell receptor expression and maturation; however, activation of Slp-76(ace/ace) NK cells through ITAM-containing NK-cell receptors or allogeneic/tumor target cells appeared largely unaffected. Imagestream analysis of the NK-β2M(-/-) target cell synapse revealed a specific defect in actin recruitment to the conjugate synapse in Slp-76(ace/ace) NK cells. Overall these studies establish Slp-76 as a critical determinant of NK-cell development and NK cell mediated elimination of missing-self target cells in mice. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Slp-76 is a critical determinant of NK cell-mediated recognition of missing-self targets

PubMed Central

Lampe, Kristin; Endale, Mehari; Cashman, Siobhan; Fang, Hao; Mattner, Jochen; Hildeman, David; Hoebe, Kasper

2015-01-01

Absence of MHC class I expression is an important mechanism by which NK cells recognize a variety of target cells, yet the pathways underlying “missing-self” recognition, including the involvement of activating receptors, remain poorly understood. Using ENU mutagenesis in mice, we identified a germline mutant, designated Ace, with a marked defect in NK cell-mediated recognition and elimination of “missing-self” targets. The causative mutation was linked to chromosome 11 and identified as a missense mutation [Thr428Ile] in the SH2 domain of Slp-76—a critical adapter molecule downstream of ITAM-containing surface receptors. The Slp-76 Ace mutation behaved as a hypomorphic allele—while no major defects were observed in conventional T cell development/function, a marked defect in NK cell-mediated elimination of β2-Microglobulin (β2M)-deficient target cells was observed. Further studies revealed Slp-76 to control NK cell receptor expression and maturation, however, activation of Slp-76ace/ace NK cells through ITAM-containing NK cell receptors or allogeneic/tumor target cells appeared largely unaffected. Imagestream analysis of the NK-β2M−/− target cell synapse, revealed a specific defect in actin recruitment to the conjugate synapse in Slp-76ace/ace NK cells. Overall these studies establish Slp-76 as a critical determinant of NK cell development and NK cell-mediated elimination of missing-self target cells. PMID:25929249

Invariant-feature-based adaptive automatic target recognition in obscured 3D point clouds

NASA Astrophysics Data System (ADS)

Khuon, Timothy; Kershner, Charles; Mattei, Enrico; Alverio, Arnel; Rand, Robert

2014-06-01

Target recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system. The signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a desired tolerance is required to perform classification and recognition optimally. The feature-based pattern recognition algorithm architecture as described below is particularly devised for solving a single-sensor classification non-parametrically. Feature set is extracted from an input point cloud, normalized, and classifier a neural network classifier. For instance, automatic target recognition in an urban area would require different feature sets from one in a dense foliage area. The figure above (see manuscript) illustrates the architecture of the feature based adaptive signature extraction of 3D point cloud including LIDAR, RADAR, and electro-optical data. This network takes a 3D cluster and classifies it into a specific class. The algorithm is a supervised and adaptive classifier with two modes: the training mode and the performing mode. For the training mode, a number of novel patterns are selected from actual or artificial data. A particular 3D cluster is input to the network as shown above for the decision class output. The network consists of three sequential functional modules. The first module is for feature extraction that extracts the input cluster into a set of singular value features or feature vector. Then the feature vector is input into the feature normalization module to normalize and balance it before being fed to the neural net classifier for the classification. The neural net can be trained by actual or artificial novel data until each trained output reaches the declared output within the defined tolerance. In case new novel data is added after the neural net has been learned, the training is then resumed until the neural net has incrementally learned with the new

A unique dual recognition hairpin probe mediated fluorescence amplification method for sensitive detection of uracil-DNA glycosylase and endonuclease IV activities.

PubMed

Wu, Yushu; Yan, Ping; Xu, Xiaowen; Jiang, Wei

2016-03-07

Uracil-DNA glycosylase (UDG) and endonuclease IV (Endo IV) play cooperative roles in uracil base-excision repair (UBER) and inactivity of either will interrupt the UBER to cause disease. Detection of UDG and Endo IV activities is crucial to evaluate the UBER process in fundamental research and diagnostic application. Here, a unique dual recognition hairpin probe mediated fluorescence amplification method was developed for sensitively and selectively detecting UDG and Endo IV activities. For detecting UDG activity, the uracil base in the probe was excised by the target enzyme to generate an apurinic/apyrimidinic (AP) site, achieving the UDG recognition. Then, the AP site was cleaved by a tool enzyme Endo IV, releasing a primer to trigger rolling circle amplification (RCA) reaction. Finally, the RCA reaction produced numerous repeated G-quadruplex sequences, which interacted with N-methyl-mesoporphyrin IX to generate an enhanced fluorescence signal. Alternatively, for detecting Endo IV activity, the uracil base in the probe was first converted into an AP site by a tool enzyme UDG. Next, the AP site was cleaved by the target enzyme, achieving the Endo IV recognition. The signal was then generated and amplified in the same way as those in the UDG activity assay. The detection limits were as low as 0.00017 U mL(-1) for UDG and 0.11 U mL(-1) for Endo IV, respectively. Moreover, UDG and Endo IV can be well distinguished from their analogs. This method is beneficial for properly evaluating the UBER process in function studies and disease prognoses.

Structural aspects of denitrifying enzymes.

PubMed

Moura, I; Moura, J J

2001-04-01

The reduction of nitrate to nitrogen gas via nitrite, nitric oxide and nitrous oxide is the metabolic pathway usually known as denitrification, a key step in the nitrogen cycle. As observed for other elemental cycles, a battery of enzymes are utilized, namely the reductases for nitrate, nitrite, nitric oxide and nitrous oxide, as well as multiple electron donors that interact with these enzymes, in order to carry out the stepwise reactions that involve key intermediates. Because of the importance of this pathway (of parallel importance to the nitrogen-fixation pathway), efforts are underway to understand the structures of the participating enzymes and to uncover mechanistic aspects. Three-dimensional structures have been solved for the majority of these enzymes in the past few years, revealing the architecture of the active metal sites as well as global structural aspects, and possible mechanistic aspects. In addition, the recognition of specific electron-transfer partners raises important questions regarding specific electron-transfer pathways, partner recognition and control of metabolism.

Advances in the Engineering of the Gene Editing Enzymes and the Genomes: Understanding and Handling the Off-Target Effects of CRISPR/Cas9.

PubMed

Yin, Yufang; Wang, Qian; Xiao, Li; Wang, Fengjiao; Song, Zhuo; Zhou, Cuilan; Liu, Xuan; Xing, Chungen; He, Nongyue; Li, Kai; Feng, Yan; Zhang, Jia

2018-03-01

In the past decades, significant progresses have been achieved in genetic engineering of nucleases. Among the genetically engineered nucleases, zinc finger nucleases, transcription activator-like (TAL) effector nucleases, and CRIPSPR/Cas9 system form a new field of gene editing. The gene editing efficiency or targeting effect and the off-target effect are the two major determinant factors in evaluating the usefulness of a new enzyme. Engineering strategies in improving these gene editing enzymes, particularly in minimizing their off-target effects, are the focus of this paper. Examples of using these genetically engineered enzymes in genome modification are discussed in order to better understand the requirement of engineering efforts in obtaining more powerful and useful gene editing enzymes. In addition, the identification of naturally existed anti-Cas proteins has been employed in minimizing off-target effects. Considering the future application in human gene therapy, optimization of these well recognized gene editing enzymes and exploration of more novel enzymes are both required. Before people find an ideal gene editing system having virtually no off-target effect, technologies used to screen and identify off-target effects are of importance in clinical trials employing gene therapy.

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

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

Li, Minjing; Gao, Yuqian; Qian, Wei-Jun

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different frommore » that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.« less

Metabolic Diseases Downregulate the Majority of Histone Modification Enzymes, Making a Few Upregulated Enzymes Novel Therapeutic Targets – “Sand out and Gold Stays”

PubMed Central

Shao, Ying; Chernaya, Valeria; Johnson, Candice; Yang, William Y.; Cueto, Ramon; Sha, Xiaojin; Zhang, Yi; Qin, Xuebin; Sun, Jianxin; Choi, Eric T.; Wang, Hong; Yang, Xiao-feng

2016-01-01

To determine whether the expression of histone modification enzymes is regulated in physiological and pathological conditions, we took an experimental database mining approach pioneered in our labs to determine a panoramic expression profile of 164 enzymes in 19 human and 17 murine tissues. We have made the following significant findings: 1) Histone enzymes are differentially expressed in cardiovascular, immune and other tissues; 2) Our new pyramid model showed that heart and T cells are among a few tissues in which histone acetylation/deacetylation, histone methylation/demethylation are in the highest varieties; and 3) Histone enzymes are more downregulated than upregulated in metabolic diseases and Treg polarization/differentiation, but not in tumors. These results have demonstrated a new working model of “sand out and gold stays,” where more downregulation than upregulation of histone enzymes in metabolic diseases makes a few upregulated enzymes the potential novel therapeutic targets in metabolic diseases and Treg activity. PMID:26746407

Increase in Speech Recognition Due to Linguistic Mismatch between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

ERIC Educational Resources Information Center

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose: To examine whether improved speech recognition during linguistically mismatched target-masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method: Monolingual English speakers (n = 20) and English-Greek simultaneous bilinguals (n = 20) listened to…

Automatic target recognition using a feature-based optical neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

[A new mechanism of ubiquitin-dependent proteolytic pathway--polyubiquitin chain recognition and proteasomal targeting].

PubMed

Kawahara, Hiroyuki; Yokosawa, Hideyoshi

2008-01-01

The RPN10 subunit of 26S proteasome and several UBA domain proteins can bind to the polyubiquitin chain and play a role as ubiquitin receptors of the 26S proteasome. Although it was thought that substrate recognition is an essential step in the proteasome-mediated protein degradation, deletion of rpn10 genes in yeast does not influence the viability of cells but instead causes only a mild phenotype, suggesting that the above ubiquitin receptors are redundantly involved in substrate delivery to the proteasome. However, their functional difference is still enigmatic. In this review, we summarize recent advances in polyubiquitin chain recognition/delivery system and provide potential applications to modulate this system as a probable target for drug development.

Novel N-substituted aminobenzamide scaffold derivatives targeting the dipeptidyl peptidase-IV enzyme.

PubMed

Al-Balas, Qosay A; Sowaileh, Munia F; Hassan, Mohammad A; Qandil, Amjad M; Alzoubi, Karem H; Mhaidat, Nizar M; Almaaytah, Ammar M; Khabour, Omar F

2014-01-01

The dipeptidyl peptidase-IV (DPP-IV) enzyme is considered a pivotal target for controlling normal blood sugar levels in the body. Incretins secreted in response to ingestion of meals enhance insulin release to the blood, and DPP-IV inactivates these incretins within a short period and stops their action. Inhibition of this enzyme escalates the action of incretins and induces more insulin to achieve better glucose control in diabetic patients. Thus, inhibition of this enzyme will lead to better control of blood sugar levels. In this study, computer-aided drug design was used to help establish a novel N-substituted aminobenzamide scaffold as a potential inhibitor of DPP-IV. CDOCKER software available from Discovery Studio 3.5 was used to evaluate a series of designed compounds and assess their mode of binding to the active site of the DPP-IV enzyme. The designed compounds were synthesized and tested against a DPP-IV enzyme kit provided by Enzo Life Sciences. The synthesized compounds were characterized using proton and carbon nuclear magnetic resonance, mass spectrometry, infrared spectroscopy, and determination of melting point. Sixty-nine novel compounds having an N-aminobenzamide scaffold were prepared, with full characterization. Ten of these compounds showed more in vitro activity against DPP-IV than the reference compounds, with the most active compounds scoring 38% activity at 100 μM concentration. The N-aminobenzamide scaffold was shown in this study to be a valid scaffold for inhibiting the DPP-IV enzyme. Continuing work could unravel more active compounds possessing the same scaffold.

Targeting of Several Glycolytic Enzymes Using RNA Interference Reveals Aldolase Affects Cancer Cell Proliferation through a Non-glycolytic Mechanism

PubMed Central

Lew, Carolyn Ritterson; Tolan, Dean R.

2012-01-01

In cancer, glucose uptake and glycolysis are increased regardless of the oxygen concentration in the cell, a phenomenon known as the Warburg effect. Several (but not all) glycolytic enzymes have been investigated as potential therapeutic targets for cancer treatment using RNAi. Here, four previously untargeted glycolytic enzymes, aldolase A, glyceraldehyde 3-phosphate dehydrogenase, triose phosphate isomerase, and enolase 1, are targeted using RNAi in Ras-transformed NIH-3T3 cells. Of these enzymes, knockdown of aldolase causes the greatest effect, inhibiting cell proliferation by 90%. This defect is rescued by expression of exogenous aldolase. However, aldolase knockdown does not affect glycolytic flux or intracellular ATP concentration, indicating a non-metabolic cause for the cell proliferation defect. Furthermore, this defect could be rescued with an enzymatically dead aldolase variant that retains the known F-actin binding ability of aldolase. One possible model for how aldolase knockdown may inhibit transformed cell proliferation is through its disruption of actin-cytoskeleton dynamics in cell division. Consistent with this hypothesis, aldolase knockdown cells show increased multinucleation. These results are compared with other studies targeting glycolytic enzymes with RNAi in the context of cancer cell proliferation and suggest that aldolase may be a useful target in the treatment of cancer. PMID:23093405

Type III restriction-modification enzymes: a historical perspective.

PubMed

Rao, Desirazu N; Dryden, David T F; Bheemanaik, Shivakumara

2014-01-01

Restriction endonucleases interact with DNA at specific sites leading to cleavage of DNA. Bacterial DNA is protected from restriction endonuclease cleavage by modifying the DNA using a DNA methyltransferase. Based on their molecular structure, sequence recognition, cleavage position and cofactor requirements, restriction-modification (R-M) systems are classified into four groups. Type III R-M enzymes need to interact with two separate unmethylated DNA sequences in inversely repeated head-to-head orientations for efficient cleavage to occur at a defined location (25-27 bp downstream of one of the recognition sites). Like the Type I R-M enzymes, Type III R-M enzymes possess a sequence-specific ATPase activity for DNA cleavage. ATP hydrolysis is required for the long-distance communication between the sites before cleavage. Different models, based on 1D diffusion and/or 3D-DNA looping, exist to explain how the long-distance interaction between the two recognition sites takes place. Type III R-M systems are found in most sequenced bacteria. Genome sequencing of many pathogenic bacteria also shows the presence of a number of phase-variable Type III R-M systems, which play a role in virulence. A growing number of these enzymes are being subjected to biochemical and genetic studies, which, when combined with ongoing structural analyses, promise to provide details for mechanisms of DNA recognition and catalysis.

A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against Leishmania major

PubMed Central

Catharina, Larissa; Lima, Carlyle Ribeiro; Franca, Alexander; Guimarães, Ana Carolina Ramos; Alves-Ferreira, Marcelo; Tuffery, Pierre; Derreumaux, Philippe; Carels, Nicolas

2017-01-01

We present an approach for detecting enzymes that are specific of Leishmania major compared with Homo sapiens and provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific for L major compared with H sapiens, only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific of L major and 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with H sapiens. Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes for L major that may serve as targets for drug development. PMID:28638238

A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against Leishmania major.

PubMed

Catharina, Larissa; Lima, Carlyle Ribeiro; Franca, Alexander; Guimarães, Ana Carolina Ramos; Alves-Ferreira, Marcelo; Tuffery, Pierre; Derreumaux, Philippe; Carels, Nicolas

2017-01-01

We present an approach for detecting enzymes that are specific of Leishmania major compared with Homo sapiens and provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific for L major compared with H sapiens , only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific of L major and 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with H sapiens . Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes for L major that may serve as targets for drug development.

SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

NASA Astrophysics Data System (ADS)

Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

2018-05-01

Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

Structural and functional features of enzymes of Mycobacterium tuberculosis peptidoglycan biosynthesis as targets for drug development

PubMed Central

Moraes, Gleiciane Leal; Gomes, Guelber Cardoso; de Sousa, Paulo Robson Monteiro; Alves, Cláudio Nahum; Govender, Thavendran; Kruger, Hendrik G.; Maguire, Glenn E.M.; Lamichhane, Gyanu; Lameira, Jerônimo

2015-01-01

SUMMARY Tuberculosis (TB) is the second leading cause of human mortality from infectious diseases worldwide. The WHO reported 1.3 million deaths and 8.6 million new cases of TB in 2012. Mycobacterium tuberculosis (M. tuberculosis), the infectious bacteria that causes TB, is encapsulated by a thick and robust cell wall. The innermost segment of the cell wall is comprised of peptidoglycan, a layer that is required for survival and growth of the pathogen. Enzymes that catalyse biosynthesis of the peptidoglycan are essential and are therefore attractive targets for discovery of novel antibiotics as humans lack similar enzymes making it possible to selectively target bacteria only. In this paper, we have reviewed the structures and functions of enzymes GlmS, GlmM, GlmU, MurA, MurB, MurC, MurD, MurE and MurF from M. tuberculosis that are involved in peptidoglycan biosynthesis. In addition, we report homology modelled 3D structures of those key enzymes from M. tuberculosis of which the structures are still unknown. We demonstrated that natural substrates can be successfully docked into the active sites of the GlmS and GlmU respectively. It is therefore expected that the models and the data provided herein will facilitate translational research to develop new drugs to treat TB. PMID:25701501

Pattern recognition of the targets with help of polarization properties of the signal

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; de Rivera, Luis N.; Castellanos, Aldo B.; Popov, Anatoly V.

1999-10-01

We proposed to use the possibility of recognition of the targets on background of the scattering from the surface, weather objects with the help of polarimetric 3-cm radar. It has been investigated such polarization characteristics: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy section was less than 1 dB at ranges up to 15 km and less than 1.5 dB at ranges up to 100 km. During the experiments urban objects and 6 various ships of small displacement having the closest values of the backscattering cross-section were used. The analysis has shown: the factor of the polarization selection for anisotropy objects and weather objects had the values about 0.02-0.08 Isotropy had the values of polarimetric correlation factor for hydrometers about 0.7-0.8, for earth surface about 0.8-0.9, for sea surface - from 0.33 to 0.7. The results of the work of recognition algorithm of a class 'concrete objects', and 'metal objects' are submitted as example in the paper. The result of experiments have shown that the probability of correct recognition of the identified objects was in the limits from 0.93 to 0.97.

Action Recognition in a Crowded Environment

PubMed Central

Nieuwenhuis, Judith; Bülthoff, Isabelle; Barraclough, Nick; de la Rosa, Stephan

2017-01-01

So far, action recognition has been mainly examined with small point-light human stimuli presented alone within a narrow central area of the observer’s visual field. Yet, we need to recognize the actions of life-size humans viewed alone or surrounded by bystanders, whether they are seen in central or peripheral vision. Here, we examined the mechanisms in central vision and far periphery (40° eccentricity) involved in the recognition of the actions of a life-size actor (target) and their sensitivity to the presence of a crowd surrounding the target. In Experiment 1, we used an action adaptation paradigm to probe whether static or idly moving crowds might interfere with the recognition of a target’s action (hug or clap). We found that this type of crowds whose movements were dissimilar to the target action hardly affected action recognition in central and peripheral vision. In Experiment 2, we examined whether crowd actions that were more similar to the target actions affected action recognition. Indeed, the presence of that crowd diminished adaptation aftereffects in central vision as wells as in the periphery. We replicated Experiment 2 using a recognition task instead of an adaptation paradigm. With this task, we found evidence of decreased action recognition accuracy, but this was significant in peripheral vision only. Our results suggest that the presence of a crowd carrying out actions similar to that of the target affects its recognition. We outline how these results can be understood in terms of high-level crowding effects that operate on action-sensitive perceptual channels. PMID:29308177

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Lead discovery and chemical biology approaches targeting the ubiquitin proteasome system.

PubMed

Akinjiyan, Favour A; Carbonneau, Seth; Ross, Nathan T

2017-10-15

Protein degradation is critical for proteostasis, and the addition of polyubiquitin chains to a substrate is necessary for its recognition by the 26S proteasome. Therapeutic intervention in the ubiquitin proteasome system has implications ranging from cancer to neurodegeneration. Novel screening methods and chemical biology tools for targeting E1-activating, E2-conjugating and deubiquitinating enzymes will be discussed in this review. Approaches for targeting E3 ligase-substrate interactions as well as the proteasome will also be covered, with a focus on recently described approaches. Copyright © 2017. Published by Elsevier Ltd.

Target recognition based on the moment functions of radar signatures

NASA Astrophysics Data System (ADS)

Kim, Kyung-Tae; Kim, Hyo-Tae

2002-03-01

In this paper, we present the results of target recognition research based on the moment functions of various radar signatures, such as time-frequency signatures, range profiles, and scattering centers. The proposed approach utilizes geometrical moments or central moments of the obtained radar signatures. In particular, we derived exact and closed form expressions of the geometrical moments of the adaptive Gaussian representation (AGR), which is one of the adaptive joint time-frequency techniques, and also computed the central moments of range profiles and one-dimensional (1-D) scattering centers on a target, which are obtained by various super-resolution techniques. The obtained moment functions are further processed to provide small dimensional and redundancy-free feature vectors, and classified via a neural network approach or a Bayes classifier. The performances of the proposed technique are demonstrated using a simulated radar cross section (RCS) data set, or a measured RCS data set of various scaled aircraft models, obtained at the Pohang University of Science and Technology (POSTECH) compact range facility. Results show that the techniques in this paper can not only provide reliable classification accuracy, but also save computational resources.

Extending enzyme molecular recognition with an expanded amino acid alphabet

PubMed Central

Windle, Claire L.; Simmons, Katie J.; Ault, James R.; Trinh, Chi H.; Nelson, Adam

2017-01-01

Natural enzymes are constructed from the 20 proteogenic amino acids, which may then require posttranslational modification or the recruitment of coenzymes or metal ions to achieve catalytic function. Here, we demonstrate that expansion of the alphabet of amino acids can also enable the properties of enzymes to be extended. A chemical mutagenesis strategy allowed a wide range of noncanonical amino acids to be systematically incorporated throughout an active site to alter enzymic substrate specificity. Specifically, 13 different noncanonical side chains were incorporated at 12 different positions within the active site of N-acetylneuraminic acid lyase (NAL), and the resulting chemically modified enzymes were screened for activity with a range of aldehyde substrates. A modified enzyme containing a 2,3-dihydroxypropyl cysteine at position 190 was identified that had significantly increased activity for the aldol reaction of erythrose with pyruvate compared with the wild-type enzyme. Kinetic investigation of a saturation library of the canonical amino acids at the same position showed that this increased activity was not achievable with any of the 20 proteogenic amino acids. Structural and modeling studies revealed that the unique shape and functionality of the noncanonical side chain enabled the active site to be remodeled to enable more efficient stabilization of the transition state of the reaction. The ability to exploit an expanded amino acid alphabet can thus heighten the ambitions of protein engineers wishing to develop enzymes with new catalytic properties. PMID:28196894

A Pathogenic Nematode Targets Recognition Proteins to Avoid Insect Defenses

PubMed Central

Toubarro, Duarte; Avila, Mónica Martinez; Montiel, Rafael; Simões, Nelson

2013-01-01

Steinernema carpocapsae is a nematode pathogenic in a wide variety of insect species. The great pathogenicity of this nematode has been ascribed to its ability to overcome the host immune response; however, little is known about the mechanisms involved in this process. The analysis of an expressed sequence tags (EST) library in the nematode during the infective phase was performed and a highly abundant contig homologous to serine protease inhibitors was identified. In this work, we show that this contig is part of a 641-bp cDNA that encodes a BPTI-Kunitz family inhibitor (Sc-KU-4), which is up-regulated in the parasite during invasion and installation. Recombinant Sc-KU-4 protein was produced in Escherichia coli and shown to inhibit chymotrypsin and elastase activities in a dose-dependent manner by a competitive mechanism with Ki values of 1.8 nM and 2.6 nM, respectively. Sc-KU-4 also inhibited trypsin and thrombin activities to a lesser extent. Studies of the mode of action of Sc-KU-4 and its effects on insect defenses suggest that although Sc-KU-4 did not inhibit the activation of hemocytes or the formation of clotting fibers, it did inhibit hemocyte aggregation and the entrapment of foreign particles by fibers. Moreover, Sc-KU-4 avoided encapsulation and the deposition of clotting materials, which usually occurs in response to foreign particles. We show by protein-protein interaction that Sc-KU-4 targets recognition proteins of insect immune system such as masquerade-like and serine protease-like homologs. The interaction of Sc-KU-4 with these proteins explains the ability of the nematode to overcome host reactions and its large pathogenic spectrum, once these immune proteins are well conserved in insects. The discovery of this inhibitor targeting insect recognition proteins opens new avenues for the development of S . carpocapsae as a biological control agent and provides a new tool to study host-pathogen interactions. PMID:24098715

Fine tuning cellular recognition: The function of the leucine rich repeat (LRR) trans-membrane protein, LRT, in muscle targeting to tendon cells.

PubMed

Gilsohn, Eli; Volk, Talila

2010-01-01

The formation of complex tissues during embryonic development is often accompanied by directed cellular migration towards a target tissue. Specific mutual recognition between the migrating cell and its target tissue leads to the arrest of the cell migratory behavior and subsequent contact formation between the two interacting cell types. Recent studies implicated a novel family of surface proteins containing a trans-membrane domain and single leucine-rich repeat (LRR) domain in inter-cellular recognition and the arrest of cell migration. Here, we describe the involvement of a novel LRR surface protein, LRT, in targeting migrating muscles towards their corresponding tendon cells in the Drosophila embryo. LRT is specifically expressed by the target tendon cells and is essential for arresting the migratory behavior of the muscle cells. Additional studies in Drosophila S2 cultured cells suggest that LRT forms a protein complex with the Roundabout (Robo) receptor, essential for guiding muscles towards their tendon partners. Genetic analysis supports a model in which LRT performs its activity non-autonomously through its interaction with the Robo receptors expressed on the muscle surfaces. These results suggest a novel mechanism of intercellular recognition through interactions between LRR family members and Robo receptors.

Creation of a type IIS restriction endonuclease with a long recognition sequence

PubMed Central

Lippow, Shaun M.; Aha, Patti M.; Parker, Matthew H.; Blake, William J.; Baynes, Brian M.; Lipovšek, Daša

2009-01-01

Type IIS restriction endonucleases cleave DNA outside their recognition sequences, and are therefore particularly useful in the assembly of DNA from smaller fragments. A limitation of type IIS restriction endonucleases in assembly of long DNA sequences is the relative abundance of their target sites. To facilitate ligation-based assembly of extremely long pieces of DNA, we have engineered a new type IIS restriction endonuclease that combines the specificity of the homing endonuclease I-SceI with the type IIS cleavage pattern of FokI. We linked a non-cleaving mutant of I-SceI, which conveys to the chimeric enzyme its specificity for an 18-bp DNA sequence, to the catalytic domain of FokI, which cuts DNA at a defined site outside the target site. Whereas previously described chimeric endonucleases do not produce type IIS-like precise DNA overhangs suitable for ligation, our chimeric endonuclease cleaves double-stranded DNA exactly 2 and 6 nt from the target site to generate homogeneous, 5′, four-base overhangs, which can be ligated with 90% fidelity. We anticipate that these enzymes will be particularly useful in manipulation of DNA fragments larger than a thousand bases, which are very likely to contain target sites for all natural type IIS restriction endonucleases. PMID:19304757

Enzyme/non-enzyme discrimination and prediction of enzyme active site location using charge-based methods.

PubMed

Bate, Paul; Warwicker, Jim

2004-07-02

Calculations of charge interactions complement analysis of a characterised active site, rationalising pH-dependence of activity and transition state stabilisation. Prediction of active site location through large DeltapK(a)s or electrostatic strain is relevant for structural genomics. We report a study of ionisable groups in a set of 20 enzymes, finding that false positives obscure predictive potential. In a larger set of 156 enzymes, peaks in solvent-space electrostatic properties are calculated. Both electric field and potential match well to active site location. The best correlation is found with electrostatic potential calculated from uniform charge density over enzyme volume, rather than from assignment of a standard atom-specific charge set. Studying a shell around each molecule, for 77% of enzymes the potential peak is within that 5% of the shell closest to the active site centre, and 86% within 10%. Active site identification by largest cleft, also with projection onto a shell, gives 58% of enzymes for which the centre of the largest cleft lies within 5% of the active site, and 70% within 10%. Dielectric boundary conditions emphasise clefts in the uniform charge density method, which is suited to recognition of binding pockets embedded within larger clefts. The variation of peak potential with distance from active site, and comparison between enzyme and non-enzyme sets, gives an optimal threshold distinguishing enzyme from non-enzyme. We find that 87% of the enzyme set exceeds the threshold as compared to 29% of the non-enzyme set. Enzyme/non-enzyme homologues, "structural genomics" annotated proteins and catalytic/non-catalytic RNAs are studied in this context.

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

Structural and functional features of enzymes of Mycobacterium tuberculosis peptidoglycan biosynthesis as targets for drug development.

PubMed

Moraes, Gleiciane Leal; Gomes, Guelber Cardoso; Monteiro de Sousa, Paulo Robson; Alves, Cláudio Nahum; Govender, Thavendran; Kruger, Hendrik G; Maguire, Glenn E M; Lamichhane, Gyanu; Lameira, Jerônimo

2015-03-01

Tuberculosis (TB) is the second leading cause of human mortality from infectious diseases worldwide. The WHO reported 1.3 million deaths and 8.6 million new cases of TB in 2012. Mycobacterium tuberculosis (M. tuberculosis), the infectious bacteria that causes TB, is encapsulated by a thick and robust cell wall. The innermost segment of the cell wall is comprised of peptidoglycan, a layer that is required for survival and growth of the pathogen. Enzymes that catalyse biosynthesis of the peptidoglycan are essential and are therefore attractive targets for discovery of novel antibiotics as humans lack similar enzymes making it possible to selectively target bacteria only. In this paper, we have reviewed the structures and functions of enzymes GlmS, GlmM, GlmU, MurA, MurB, MurC, MurD, MurE and MurF from M. tuberculosis that are involved in peptidoglycan biosynthesis. In addition, we report homology modelled 3D structures of those key enzymes from M. tuberculosis of which the structures are still unknown. We demonstrated that natural substrates can be successfully docked into the active sites of the GlmS and GlmU respectively. It is therefore expected that the models and the data provided herein will facilitate translational research to develop new drugs to treat TB. Copyright © 2015. Published by Elsevier Ltd.

Perceptual fluency and affect without recognition.

PubMed

Anand, P; Sternthal, B

1991-05-01

A dichotic listening task was used to investigate the affect-without-recognition phenomenon. Subjects performed a distractor task by responding to the information presented in one ear while ignoring the target information presented in the other ear. The subjects' recognition of and affect toward the target information as well as toward foils was measured. The results offer evidence for the affect-without-recognition phenomenon. Furthermore, the data suggest that the subjects' affect toward the stimuli depended primarily on the extent to which the stimuli were perceived as familiar (i.e., subjective familiarity), and this perception was influenced by the ear in which the distractor or the target information was presented. These data are interpreted in terms of current models of recognition memory and hemispheric lateralization.

TIA-1 RRM23 binding and recognition of target oligonucleotides

PubMed Central

Waris, Saboora; García-Mauriño, Sofía M.; Sivakumaran, Andrew; Beckham, Simone A.; Loughlin, Fionna E.; Gorospe, Myriam; Díaz-Moreno, Irene; Wilce, Matthew C.J.

2017-01-01

Abstract TIA-1 (T-cell restricted intracellular antigen-1) is an RNA-binding protein involved in splicing and translational repression. It mainly interacts with RNA via its second and third RNA recognition motifs (RRMs), with specificity for U-rich sequences directed by RRM2. It has recently been shown that RRM3 also contributes to binding, with preferential binding for C-rich sequences. Here we designed UC-rich and CU-rich 10-nt sequences for engagement of both RRM2 and RRM3 and demonstrated that the TIA-1 RRM23 construct preferentially binds the UC-rich RNA ligand (5΄-UUUUUACUCC-3΄). Interestingly, this binding depends on the presence of Lys274 that is C-terminal to RRM3 and binding to equivalent DNA sequences occurs with similar affinity. Small-angle X-ray scattering was used to demonstrate that, upon complex formation with target RNA or DNA, TIA-1 RRM23 adopts a compact structure, showing that both RRMs engage with the target 10-nt sequences to form the complex. We also report the crystal structure of TIA-1 RRM2 in complex with DNA to 2.3 Å resolution providing the first atomic resolution structure of any TIA protein RRM in complex with oligonucleotide. Together our data support a specific mode of TIA-1 RRM23 interaction with target oligonucleotides consistent with the role of TIA-1 in binding RNA to regulate gene expression. PMID:28184449

Phage lytic enzymes targeting streptococci

USDA-ARS?s Scientific Manuscript database

Streptococcal pathogens contribute to a wide variety of human and livestock diseases. There is a need for new antimicrobials to replace over-used conventional antibiotics. Bacteriophage (viruses that infect bacteria) endolysins (enzymes that help degrade the bacterial cell wall) are ideal candidat...

The effects of altered N-linked oligosaccharide structures on maturation and targeting of lysosomal enzymes in Dictyostelium discoideum.

PubMed

Freeze, H H; Koza-Taylor, P; Saunders, A; Cardelli, J A

1989-11-15

We have examined the relationship of N-linked oligosaccharide structures to the proper targeting and proteolytic processing of two lysosomal enzymes, alpha-mannosidase and beta-glucosidase, in the slime mold Dictyostelium discoideum. Two different mutant strains, HL241 and HL243, each synthesize the same nonglucosylated, truncated, lipid-linked oligosaccharide precursor, Man6GlcNAc2. [3H]Mannose-labeled N-linked oligosaccharides were studied following their release from immunoprecipitated alpha-mannosidase and beta-glucosidase by digestion with peptide:N-glycosidase F. The oligosaccharides from both mutants resembled each other, but they were smaller and contained fewer anionic groups than those from the wild-type. The oligosaccharides from the mutants strains were reduced in sulfate and Man-6-P content, and all Man-6-P was in the form of acid-stable phosphodiesters. Pulse-chase radiolabeling experiments using [35S] methionine indicated that the precursor forms of both enzymes were smaller than wild-type, and that this difference was due solely to differences in N-linked oligosaccharides. The precursor forms of the enzymes were not over-secreted, but appeared to be proteolytically processed into mature forms at approximately 50% the rate of wild-type. This is mainly due to their prolonged retention in the rough endoplasmic reticulum, but, ultimately, both enzymes were properly targeted to lysosomes. These studies indicate that a reduction in the amount of sulfation, phosphorylation or size of the N-linked oligosaccharides in these mutants is not critical for the proteolytic processing and targeting of the lysosomal enzymes, but that these changes may influence their rate of exit from the rough endoplasmic reticulum.

Research on application of LADAR in ground vehicle recognition

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Antitumor Synergism and Enhanced Survival with a Tumor Vasculature-Targeted Enzyme Prodrug System, Rapamycin, and Cyclophosphamide.

PubMed

Krais, John J; Virani, Needa; McKernan, Patrick H; Nguyen, Quang; Fung, Kar-Ming; Sikavitsas, Vassilios I; Kurkjian, Carla; Harrison, Roger G

2017-09-01

Mutant cystathionine gamma-lyase was targeted to phosphatidylserine exposed on tumor vasculature through fusion with Annexin A1 or Annexin A5. Cystathionine gamma-lyase E58N, R118L, and E338N mutations impart nonnative methionine gamma-lyase activity, resulting in tumor-localized generation of highly toxic methylselenol upon systemic administration of nontoxic selenomethionine. The described therapeutic system circumvents systemic toxicity issues using a novel drug delivery/generation approach and avoids the administration of nonnative proteins and/or DNA required with other enzyme prodrug systems. The enzyme fusion exhibits strong and stable in vitro binding with dissociation constants in the nanomolar range for both human and mouse breast cancer cells and in a cell model of tumor vascular endothelium. Daily administration of the therapy suppressed growth of highly aggressive triple-negative murine 4T1 mammary tumors in immunocompetent BALB/cJ mice and MDA-MB-231 tumors in SCID mice. Treatment did not result in the occurrence of negative side effects or the elicitation of neutralizing antibodies. On the basis of the vasculature-targeted nature of the therapy, combinations with rapamycin and cyclophosphamide were evaluated. Rapamycin, an mTOR inhibitor, reduces the prosurvival signaling of cells in a hypoxic environment potentially exacerbated by a vasculature-targeted therapy. IHC revealed, unsurprisingly, a significant hypoxic response (increase in hypoxia-inducible factor 1 α subunit, HIF1A) in the enzyme prodrug-treated tumors and a dramatic reduction of HIF1A upon rapamycin treatment. Cyclophosphamide, an immunomodulator at low doses, was combined with the enzyme prodrug therapy and rapamycin; this combination synergistically reduced tumor volumes, inhibited metastatic progression, and enhanced survival. Mol Cancer Ther; 16(9); 1855-65. ©2017 AACR . ©2017 American Association for Cancer Research.

In silico molecular docking studies of new potential 4-phthalazinyl-hydrazones on selected Trypanosoma cruzi and Leishmania enzyme targets.

PubMed

Romero, Angel H; López, Simón E

2017-09-01

Recently, a series of 4-phthalazinyl-hydrazones under its E-configuration have exhibited excellent in vitro antichagasic and antileishmanial profiles. Preliminary assays on both parasites suggested that the most active derivatives act through oxidative and nitrosative stress mechanisms; however, their exact mode of actions as anti-trypanosomal and anti-leishmanial agents have not been completely elucidated. This motivated to perform a molecular docking study on essential trypanosomatid enzymes such as superoxide dismutase (SOD), trypanothione reductase (TryR), cysteine-protease (CP) and pteridine reductase 1 (PTR1). In addition, to understand the experimental results of nitric oxide production obtained for infected macrophages with Leishmania parasite, a molecular docking was evaluated on nitric oxide synthase (iNOS) enzyme of Rattus norvegicus. Both diastereomers (E and Z) of the 4-phthalazinyl-hydrazones were docked on the mentioned targets. In general, molecular docking on T. cruzi enzymes revealed that the E-diastereomers exhibited lower binding energies than Z-diastereomers on the Fe-SOD and CP enzymes, while Z-diastereomers showed lower docking energies than E-isomers on TryR enzyme. For the Leishmania docking studies, the Z-isomers exhibited the best binding affinities on the PTR1 and iNOS enzymes, while the TryR enzyme showed a minor dependence with the stereoselectivity of the tested phthalazines. However, either the structural information of the ligand-enzyme complexes or the experimental data suggest that the significant antitrypanosomatid activity of the most active derivatives is not associated to the inhibition of the SOD, CP and PTR1 enzymes, while the TryR inhibition and nitric oxide generation in host cells emerge as interesting antitrypanosomatid therapeutic targets. Copyright © 2017 Elsevier Inc. All rights reserved.

Unusual target site disruption by the rare-cutting HNH restriction endonuclease PacI

PubMed Central

Shen, Betty; Heiter, Daniel F.; Chan, Siu-Hong; Wang, Hua; Xu, Shuang-Yong; Morgan, Richard D.; Wilson, Geoffrey G.; Stoddard, Barry L.

2010-01-01

The crystal structure of the rare-cutting HNH restriction endonuclease PacI in complex with its eight base pair target recognition sequence 5'-TTAATTAA-3' has been determined to 1.9 Å resolution. The enzyme forms an extended homodimer, with each subunit containing two zinc-bound motifs surrounding a ββα-metal catalytic site. The latter is unusual in that a tyrosine residue likely initiates strand-cleavage. PacI dramatically distorts its target sequence from Watson-Crick duplex DNA basepairing, with every base separated from its original partner. Two bases on each strand are unpaired, four are engaged in non-canonical A:A and T:T base pairs, and the remaining two bases are matched with new Watson-Crick partners. This represents a highly unusual DNA binding mechanism for a restriction endonuclease, and implies that initial recognition of the target site might involve significantly different contacts from those visualized in the DNA-bound cocrystal structures. PMID:20541511

Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

NASA Astrophysics Data System (ADS)

Kim, Sungho

2017-06-01

Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

Programmable and multiparameter DNA-based logic platform for cancer recognition and targeted therapy.

PubMed

You, Mingxu; Zhu, Guizhi; Chen, Tao; Donovan, Michael J; Tan, Weihong

2015-01-21

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy.

Programmable and Multiparameter DNA-Based Logic Platform For Cancer Recognition and Targeted Therapy

PubMed Central

2014-01-01

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy. PMID:25361164

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

TIA-1 RRM23 binding and recognition of target oligonucleotides.

PubMed

Waris, Saboora; García-Mauriño, Sofía M; Sivakumaran, Andrew; Beckham, Simone A; Loughlin, Fionna E; Gorospe, Myriam; Díaz-Moreno, Irene; Wilce, Matthew C J; Wilce, Jacqueline A

2017-05-05

TIA-1 (T-cell restricted intracellular antigen-1) is an RNA-binding protein involved in splicing and translational repression. It mainly interacts with RNA via its second and third RNA recognition motifs (RRMs), with specificity for U-rich sequences directed by RRM2. It has recently been shown that RRM3 also contributes to binding, with preferential binding for C-rich sequences. Here we designed UC-rich and CU-rich 10-nt sequences for engagement of both RRM2 and RRM3 and demonstrated that the TIA-1 RRM23 construct preferentially binds the UC-rich RNA ligand (5΄-UUUUUACUCC-3΄). Interestingly, this binding depends on the presence of Lys274 that is C-terminal to RRM3 and binding to equivalent DNA sequences occurs with similar affinity. Small-angle X-ray scattering was used to demonstrate that, upon complex formation with target RNA or DNA, TIA-1 RRM23 adopts a compact structure, showing that both RRMs engage with the target 10-nt sequences to form the complex. We also report the crystal structure of TIA-1 RRM2 in complex with DNA to 2.3 Å resolution providing the first atomic resolution structure of any TIA protein RRM in complex with oligonucleotide. Together our data support a specific mode of TIA-1 RRM23 interaction with target oligonucleotides consistent with the role of TIA-1 in binding RNA to regulate gene expression. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Assessing the performance of a covert automatic target recognition algorithm

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2005-05-01

Passive radar systems exploit illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. Doing so allows them to operate covertly and inexpensively. Our research seeks to enhance passive radar systems by adding automatic target recognition (ATR) capabilities. In previous papers we proposed conducting ATR by comparing the radar cross section (RCS) of aircraft detected by a passive radar system to the precomputed RCS of aircraft in the target class. To effectively model the low-frequency setting, the comparison is made via a Rician likelihood model. Monte Carlo simulations indicate that the approach is viable. This paper builds on that work by developing a method for quickly assessing the potential performance of the ATR algorithm without using exhaustive Monte Carlo trials. This method exploits the relation between the probability of error in a binary hypothesis test under the Bayesian framework to the Chernoff information. Since the data are well-modeled as Rician, we begin by deriving a closed-form approximation for the Chernoff information between two Rician densities. This leads to an approximation for the probability of error in the classification algorithm that is a function of the number of available measurements. We conclude with an application that would be particularly cumbersome to accomplish via Monte Carlo trials, but that can be quickly addressed using the Chernoff information approach. This application evaluates the length of time that an aircraft must be tracked before the probability of error in the ATR algorithm drops below a desired threshold.

Structural biology of antibody recognition of carbohydrate epitopes and potential uses for targeted cancer immunotherapies.

PubMed

Dingjan, Tamir; Spendlove, Ian; Durrant, Lindy G; Scott, Andrew M; Yuriev, Elizabeth; Ramsland, Paul A

2015-10-01

Monoclonal antibodies represent the most successful class of biopharmaceuticals for the treatment of cancer. Mechanisms of action of therapeutic antibodies are very diverse and reflect their ability to engage in antibody-dependent effector mechanisms, internalize to deliver cytotoxic payloads, and display direct effects on cells by lysis or by modulating the biological pathways of their target antigens. Importantly, one of the universal changes in cancer is glycosylation and carbohydrate-binding antibodies can be produced to selectively recognize tumor cells over normal tissues. A promising group of cell surface antibody targets consists of carbohydrates presented as glycolipids or glycoproteins. In this review, we outline the basic principles of antibody-based targeting of carbohydrate antigens in cancer. We also present a detailed structural view of antibody recognition and the conformational properties of a series of related tissue-blood group (Lewis) carbohydrates that are being pursued as potential targets of cancer immunotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Loop nucleotides control primary and mature miRNA function in target recognition and repression

PubMed Central

Yue, Si-Biao; Deis Trujillo, Robin; Tang, Yujie; O'Gorman, William E

2011-01-01

MicroRNA (miRNA) genes produce three major RNA products; primary (pri-), precursor (pre-), and mature miRNAs. Each product includes sequences complementary to cognate targets, thus they all can in principle interact with the targets. In a recent study we showed that pri-miRNAs play a direct role in target recognition and repression in the absence of functional mature miRNAs. Here we examined the functional contribution of pri-miRNAs in target regulation when full-length functional miRNAs are present. We found that pri-let-7 loop nucleotides control the production of the 5′ end of mature miRNAs and modulate the activity of the miRNA gene. This insight enabled us to modulate biogenesis of functional mature miRNAs and dissect the causal relationships between mature miRNA biogenesis and target repression. We demonstrate that both pri- and mature miRNAs can contribute to target repression and that their contributions can be distinguished by the differences between the pri- and mature miRNAs' sensitivity to bind to the first seed nucleotide. Our results demonstrate that the regulatory information encoded in the pri-/pre-miRNA loop nucleotides controls the activities of pri-miRNAs and mature let-7 by influencing pri-miRNA and target complex formation and the fidelity of mature miRNA seed generation. PMID:22142974

Internal Light Source-Driven Photoelectrochemical 3D-rGO/Cellulose Device Based on Cascade DNA Amplification Strategy Integrating Target Analog Chain and DNA Mimic Enzyme.

PubMed

Lan, Feifei; Liang, Linlin; Zhang, Yan; Li, Li; Ren, Na; Yan, Mei; Ge, Shenguang; Yu, Jinghua

2017-11-01

In this work, a chemiluminescence-driven collapsible greeting card-like photoelectrochemical lab-on-paper device (GPECD) with hollow channel was demonstrated, in which target-triggering cascade DNA amplification strategy was ingeniously introduced. The GPECD had the functions of reagents storage and signal collection, and the change of configuration could control fluidic path, reaction time and alterations in electrical connectivity. In addition, three-dimentional reduced graphene oxide affixed Au flower was in situ grown on paper cellulose fiber for achieving excellent conductivity and biocompatibility. The cascade DNA amplification strategy referred to the cyclic formation of target analog chain and its trigger action to hybridization chain reaction (HCR), leading to the formation of numerous hemin/G-quadruplex DNA mimic enzyme with the presence of hemin. Subjected to the catalysis of hemin/G-quadruplex, the strong chemiluminiscence of luminol-H 2 O 2 system was obtained, which then was used as internal light source to excite photoactive materials realizing the simplification of instrument. In this analyzing process, thrombin served as proof-of-concept, and the concentration of target was converted into the DNA signal output by the specific recognition of aptamer-protein and target analog chain recycling. The target analog chain was produced in quantity with the presence of target, which further triggered abundant HCR and introduced hemin/G-quadruplex into the system. The photocurrent signal was obtained after the nitrogen-doped carbon dots sensitized ZnO was stimulated by chemiluminescence. The proposed GPECD exhibited excellent specificity and sensitivity toward thrombin with a detection limit of 16.7 fM. This judiciously engineered GPECD paved a luciferous way for detecting other protein with trace amounts in bioanalysis and clinical biomedicine.

Increase in Speech Recognition due to Linguistic Mismatch Between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

PubMed Central

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose To examine whether improved speech recognition during linguistically mismatched target–masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method Monolingual English speakers (n = 20) and English–Greek simultaneous bilinguals (n = 20) listened to English sentences in the presence of competing English and Greek speech. Data were analyzed using mixed-effects regression models to determine differences in English recogition performance between the 2 groups and 2 masker conditions. Results Results indicated that English sentence recognition for monolinguals and simultaneous English–Greek bilinguals improved when the masker speech changed from competing English to competing Greek speech. Conclusion The improvement in speech recognition that has been observed for linguistically mismatched target–masker experiments cannot be simply explained by the masker language being linguistically unknown or unfamiliar to the listeners. Listeners can improve their speech recognition in linguistically mismatched target–masker experiments even when the listener is able to obtain meaningful linguistic information from the masker speech. PMID:24167230

Molecular recognition of glyconanoparticles by RCA and E. coli K88 - designing transports for targeted therapy.

PubMed

Gallegos-Tabanico, Amed; Sarabia-Sainz, Jose A; Sarabia-Sainz, H Manuel; Carrillo Torres, Roberto; Guzman-Partida, Ana M; Monfort, Gabriela Ramos-Clamont; Silva-Campa, Erika; Burgara-Estrella, Alexel J; Angulo-Molina, Aracely; Acosta-Elias, Mónica; Pedroza-Montero, Martín; Vazquez-Moreno, Luz

2017-01-01

The targeted drug delivery has been studied as one of the main methods in medicine to ensure successful treatments of diseases. Pharmaceutical sciences are using micro or nano carriers to obtain a controlled delivery of drugs, able to selectively interact with pathogens, cells or tissues. In this work, we modified bovine serum albumin (BSA) with lactose, obtaining a neoglycan (BSA-Lac). Subsequently, we synthesized glyconanoparticles (NPBSA-Lac) with the premise that it would be recognized by microbial galactose specific lectins. NPBSA-Lac were tested for bio-recognition with adhesins of E. coli K88 and Ricinus communis agglutinin I (RCA). Glycation of BSA with lactose was analyzed by electrophoresis, infrared spectroscopy and fluorescence. Approximately 41 lactoses per BSA molecule were estimated. Nanoparticles were obtained using water in oil emulsion method and spheroid morphology with a range size of 300-500 nm was observed. Specific recognition of NPBSA-Lac by RCA and E. coli K88 was displayed by aggregation of nanoparticles analyzed by dynamic light scattering and atomic force microscopy. The results indicate that the lactosylated nanovectors could be targeted at the E. coli K88 adhesin and potentially could be used as a transporter for an antibacterial drug.

Enzyme Informatics

PubMed Central

Alderson, Rosanna G.; Ferrari, Luna De; Mavridis, Lazaros; McDonagh, James L.; Mitchell, John B. O.; Nath, Neetika

2012-01-01

Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many cheminformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking. PMID:23116471

Targeted proteome analysis of single-gene deletion strains of Saccharomyces cerevisiae lacking enzymes in the central carbon metabolism.

PubMed

Matsuda, Fumio; Kinoshita, Syohei; Nishino, Shunsuke; Tomita, Atsumi; Shimizu, Hiroshi

2017-01-01

Central carbon metabolism is controlled by modulating the protein abundance profiles of enzymes that maintain the essential systems in living organisms. In this study, metabolic adaptation mechanisms in the model organism Saccharomyces cerevisiae were investigated by direct determination of enzyme abundance levels in 30 wild type and mutant strains. We performed a targeted proteome analysis using S. cerevisiae strains that lack genes encoding the enzymes responsible for central carbon metabolism. Our analysis revealed that at least 30% of the observed variations in enzyme abundance levels could be explained by global regulatory mechanisms. A enzyme-enzyme co-abundance analysis revealed that the abundances of enzyme proteins involved in the trehalose metabolism and glycolysis changed in a coordinated manner under the control of the transcription factors for global regulation. The remaining variations were derived from local mechanisms such as a mutant-specific increase in the abundances of remote enzymes. The proteome data also suggested that, although the functional compensation of the deficient enzyme was attained by using more resources for protein biosynthesis, available resources for the biosynthesis of the enzymes responsible for central metabolism were not abundant in S. cerevisiae cells. These results showed that global and local regulation of enzyme abundance levels shape central carbon metabolism in S. cerevisiae by using a limited resource for protein biosynthesis.

Personal glucose meters for detection and quantification of a broad range of analytes

DOEpatents

Lu, Yi; Xiang, Yu

2015-02-03

A general methodology for the development of highly sensitive and selective sensors that can achieve portable, low-cost and quantitative detection of a broad range of targets using only a personal glucose meter (PGM) is disclosed. The method uses recognition molecules that are specific for a target agent, enzymes that can convert an enzyme substrate into glucose, and PGM. Also provided are sensors, which can include a solid support to which is attached a recognition molecule that permits detection of a target agent, wherein the recognition molecule specifically binds to the target agent in the presence of the target agent but not significantly to other agents as well as an enzyme that can catalyze the conversion of a substance into glucose, wherein the enzyme is attached directly or indirectly to the recognition molecule, and wherein in the presence of the target agent the enzyme can convert the substance into glucose. The disclosed sensors can be part of a lateral flow device. Methods of using such sensors for detecting target agents are also provided.

Vigilante: Ultrafast Smart Sensor for Target Recognition and Precision Tracking in a Simulated CMD Scenario

NASA Technical Reports Server (NTRS)

Uldomkesmalee, Suraphol; Suddarth, Steven C.

1997-01-01

VIGILANTE is an ultrafast smart sensor testbed for generic Automatic Target Recognition (ATR) applications with a series of capability demonstration focussed on cruise missile defense (CMD). VIGILANTE's sensor/processor architecture is based on next-generation UV/visible/IR sensors and a tera-operations per second sugar-cube processor, as well as supporting airborne vehicle. Excellent results of efficient ATR methodologies that use an eigenvectors/neural network combination and feature-based precision tracking have been demonstrated in the laboratory environment.

Chemiresistive and Gravimetric Dual-Mode Gas Sensor toward Target Recognition and Differentiation.

PubMed

Chen, Yan; Zhang, Hao; Feng, Zhihong; Zhang, Hongxiang; Zhang, Rui; Yu, Yuanyuan; Tao, Jin; Zhao, Hongyuan; Guo, Wenlan; Pang, Wei; Duan, Xuexin; Liu, Jing; Zhang, Daihua

2016-08-24

We demonstrate a dual-mode gas sensor for simultaneous and independent acquisition of electrical and mechanical signals from the same gas adsorption event. The device integrates a graphene field-effect transistor (FET) with a piezoelectric resonator in a seamless manner by leveraging multiple structural and functional synergies. Dual signals resulting from independent physical processes, i.e., mass attachment and charge transfer can reflect intrinsic properties of gas molecules and potentially enable target recognition and quantification at the same time. Fabrication of the device is based on standard Integrated Circuit (IC) foundry processes and fully compatible with system-on-a-chip (SoC) integration to achieve extremely small form factors. In addition, the ability of simultaneous measurements of mass adsorption and charge transfer guides us to a more precise understanding of the interactions between graphene and various gas molecules. Besides its practical functions, the device serves as an effective tool to quantitatively investigate the physical processes and sensing mechanisms for a large library of sensing materials and target analytes.

Plastic antibody for the recognition of chemical warfare agent sulphur mustard.

PubMed

Boopathi, M; Suryanarayana, M V S; Nigam, Anil Kumar; Pandey, Pratibha; Ganesan, K; Singh, Beer; Sekhar, K

2006-06-15

Molecularly imprinted polymers (MIPs) known as plastic antibodies (PAs) represent a new class of materials possessing high selectivity and affinity for the target molecule. Since their discovery, PAs have attracted considerable interest from bio- and chemical laboratories to pharmaceutical institutes. PAs are becoming an important class of synthetic materials mimicking molecular recognition by natural receptors. In addition, they have been utilized as catalysts, sorbents for solid-phase extraction, stationary phase for liquid chromatography and mimics of enzymes. In this paper, first time we report the preparation and characterization of a PA for the recognition of blistering chemical warfare agent sulphur mustard (SM). The SM imprinted PA exhibited more surface area when compared to the control non-imprinted polymer (NIP). In addition, SEM image showed an ordered nano-pattern for the PA of SM that is entirely different from the image of NIP. The imprinting also enhanced SM rebinding ability to the PA when compared to the NIP with an imprinting efficiency (alpha) of 1.3.

Continuous activation of Nrf2 and its target antioxidant enzymes leads to arsenite-induced malignant transformation of human bronchial epithelial cells

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

Yang, Xu; Wang, Dapeng; Department of Toxicology, School of Public Health, Guizhou Medical University, Guiyang, Guizhou

Long-term exposure to arsenite leads to human lung cancer, but the underlying mechanisms of carcinogenesis remain obscure. The transcription factor of nuclear factor-erythroid-2 p45-related factor (Nrf2)-mediated antioxidant response represents a critical cellular defense mechanism and protection against various diseases. Paradoxically, emerging data suggest that the constitutive activation of Nrf2 is associated with cancer development, progression and chemotherapy resistance. However, the role of Nrf2 in the occurrence of cancer induced by long-term arsenite exposure remains to be fully understood. By establishing transformed human bronchial epithelial (HBE) cells via chronic low-dose arsenite treatment, we showed that, in acquiring this malignant phenotype, continuousmore » low level of ROS and sustained enhancement of Nrf2 and its target antioxidant enzyme levels were observed in the later-stage of arsenite-induced cell transformation. The downregulation of Keap1 level may be responsible for the over-activation of Nrf2 and its target enzymes. To validate these observations, Nrf2 was knocked down in arsenite-transformed HBE cells by SiRNA transfection, and the levels of Nrf2 and its target antioxidant enzymes, ROS, cell proliferation, migration, and colony formation were determined following these treatments. Results showed that blocked Nrf2 expression significantly reduced Nrf2 and its target antioxidant enzyme levels, restored ROS levels, and eventually suppressed cell proliferation, migration, and colony formation of the transformed cells. In summary, the results of the study strongly suggested that the continuous activation of Nrf2 and its target antioxidant enzymes led to the over-depletion of intracellular ROS levels, which contributed to arsenite-induced HBE cell transformation. - Highlights: • Low level, long term arsenite exposure induces malignant transformation in vitro. • Long term arsenite exposure reduces ROS and MDA levels. • Long term

Random-walk enzymes.

PubMed

Mak, Chi H; Pham, Phuong; Afif, Samir A; Goodman, Myron F

2015-09-01

Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C→U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.

Random-walk enzymes

PubMed Central

Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.

2015-01-01

Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C → U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics. PMID:26465508

Random-walk enzymes

NASA Astrophysics Data System (ADS)

Mak, Chi H.; Pham, Phuong; Afif, Samir A.; Goodman, Myron F.

2015-09-01

Enzymes that rely on random walk to search for substrate targets in a heterogeneously dispersed medium can leave behind complex spatial profiles of their catalyzed conversions. The catalytic signatures of these random-walk enzymes are the result of two coupled stochastic processes: scanning and catalysis. Here we develop analytical models to understand the conversion profiles produced by these enzymes, comparing an intrusive model, in which scanning and catalysis are tightly coupled, against a loosely coupled passive model. Diagrammatic theory and path-integral solutions of these models revealed clearly distinct predictions. Comparison to experimental data from catalyzed deaminations deposited on single-stranded DNA by the enzyme activation-induced deoxycytidine deaminase (AID) demonstrates that catalysis and diffusion are strongly intertwined, where the chemical conversions give rise to new stochastic trajectories that were absent if the substrate DNA was homogeneous. The C →U deamination profiles in both analytical predictions and experiments exhibit a strong contextual dependence, where the conversion rate of each target site is strongly contingent on the identities of other surrounding targets, with the intrusive model showing an excellent fit to the data. These methods can be applied to deduce sequence-dependent catalytic signatures of other DNA modification enzymes, with potential applications to cancer, gene regulation, and epigenetics.

Identifying Effective Enzyme Activity Targets for Recombinant Class I and Class II Collagenase for Successful Human Islet Isolation.

PubMed

Balamurugan, Appakalai N; Green, Michael L; Breite, Andrew G; Loganathan, Gopalakrishnan; Wilhelm, Joshua J; Tweed, Benjamin; Vargova, Lenka; Lockridge, Amber; Kuriti, Manikya; Hughes, Michael G; Williams, Stuart K; Hering, Bernhard J; Dwulet, Francis E; McCarthy, Robert C

2016-01-01

Isolation following a good manufacturing practice-compliant, human islet product requires development of a robust islet isolation procedure where effective limits of key reagents are known. The enzymes used for islet isolation are critical but little is known about the doses of class I and class II collagenase required for successful islet isolation. We used a factorial approach to evaluate the effect of high and low target activities of recombinant class I (rC1) and class II (rC2) collagenase on human islet yield. Consequently, 4 different enzyme formulations with divergent C1:C2 collagenase mass ratios were assessed, each supplemented with the same dose of neutral protease. Both split pancreas and whole pancreas models were used to test enzyme targets (n = 20). Islet yield/g pancreas was compared with historical enzymes (n = 42). Varying the Wunsch (rC2) and collagen degradation activity (CDA, rC1) target dose, and consequently the C1:C2 mass ratio, had no significant effect on tissue digestion. Digestions using higher doses of Wunsch and CDA resulted in comparable islet yields to those obtained with 60% and 50% of those activities, respectively. Factorial analysis revealed no significant main effect of Wunsch activity or CDA for any parameter measured. Aggregate results from 4 different collagenase formulations gave 44% higher islet yield (>5000 islet equivalents/g) in the body/tail of the pancreas (n = 12) when compared with those from the same segment using a standard natural collagenase/protease mixture (n = 6). Additionally, islet yields greater than 5000 islet equivalents/g pancreas were also obtained in whole human pancreas. A broader C1:C2 ratio can be used for human islet isolation than has been used in the past. Recombinant collagenase is an effective replacement for the natural enzyme and we have determined that high islet yield can be obtained even with low doses of rC1:rC2, which is beneficial for the survival of islets.

Beta-lactamase targeted enzyme activatable photosensitizers for antimicrobial PDT

NASA Astrophysics Data System (ADS)

Zheng, Xiang; Verma, Sarika; Sallum, Ulysses W.; Hasan, Tayyaba

2009-06-01

Photodynamic therapy (PDT) as a treatment modality for infectious disease has shown promise. However, most of the antimicrobial photosensitizers (PS) non-preferentially accumulate in both bacteria and host tissues, causing host tissue phototoxicity during treatment. We have developed a new antimicrobial PDT strategy which exploits beta-lactam resistance mechanism, one of the major drug-resistance bacteria evolved, to achieve enhanced target specificity with limited host damage. Our strategy comprises a prodrug construct with a PS and a quencher linked by beta-lactam ring, resulting in a diminished phototoxicity. This construct, beta-lactamase enzyme-activated-photosensitizer (beta-LEAP), can only be activated in the presence of both light and bacteria, and remains inactive elsewhere such as mammalian tissue. Beta-LEAP construct had shown specific cleavage by purified beta-lactamase and by beta-lactamase over-expressing methicillin resistant Staphylococcus aureus (MRSA). Specific photodynamic toxicity was observed towards MRSA, while dark and light toxicity were equivalent to reference strains. The prodrug design, synthesis and photophysical properties will be discussed.

Developments in Molecular Recognition and Sensing at Interfaces

PubMed Central

Ariga, Katsuhiko; Hill, Jonathan P.; Endo, Hiroshi

2007-01-01

In biological systems, molecular recognition events occur mostly within interfacial environments such as at membrane surfaces, enzyme reaction sites, or at the interior of the DNA double helix. Investigation of molecular recognition at model interfaces provides great insights into biological phenomena. Molecular recognition at interfaces not only has relevance to biological systems but is also important for modern applications such as high sensitivity sensors. Selective binding of guest molecules in solution to host molecules located at solid surfaces is crucial for electronic or photonic detection of analyte substances. In response to these demands, molecular recognition at interfaces has been investigated extensively during the past two decades using Langmuir monolayers, self-assembled monolayers, and lipid assemblies as recognition media. In this review, advances of molecular recognition at interfaces are briefly summarized.

Nature's inordinate fondness for metabolic enzymes: why metabolic enzyme loci are so frequently targets of selection.

PubMed

Marden, James H

2013-12-01

Metabolic enzyme loci were some of the first genes accessible for molecular evolution and ecology research. New technologies now make the whole genome, transcriptome or proteome readily accessible, allowing unbiased scans for loci exhibiting significant differences in allele frequency or expression level and associated with phenotypes and/or responses to natural selection. With surprising frequency and in many cases in proportions greater than chance relative to other genes, glycolysis and TCA cycle enzyme loci appear among the genes with significant associations in these studies. Hence, there is an ongoing need to understand the basis for fitness effects of metabolic enzyme polymorphisms. Allele-specific effects on the binding affinity and catalytic rate of individual enzymes are well known, but often of uncertain significance because metabolic control theory and in vivo studies indicate that many individual metabolic enzymes do not affect pathway flux rate. I review research, so far little used in evolutionary biology, showing that metabolic enzyme substrates affect signalling pathways that regulate cell and organismal biology, and that these enzymes have moonlighting functions. To date there is little knowledge of how alleles in natural populations affect these phenotypes. I discuss an example in which alleles of a TCA enzyme locus associate with differences in a signalling pathway and development, organismal performance, and ecological dynamics. Ultimately, understanding how metabolic enzyme polymorphisms map to phenotypes and fitness remains a compelling and ongoing need for gaining robust knowledge of ecological and evolutionary processes. © 2013 John Wiley & Sons Ltd.

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

PubMed Central

Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

2014-01-01

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

Allosteric Inhibitory Molecular Recognition of a Photochromic Dye by a Digestive Enzyme: Dihydroindolizine makes α-chymotrypsin Photo-responsive

NASA Astrophysics Data System (ADS)

Bagchi, Damayanti; Ghosh, Abhijit; Singh, Priya; Dutta, Shreyasi; Polley, Nabarun; Althagafi, Ismail. I.; Jassas, Rabab S.; Ahmed, Saleh A.; Pal, Samir Kumar

2016-09-01

The structural-functional regulation of enzymes by the administration of an external stimulus such as light could create photo-switches that exhibit unique biotechnological applications. However, molecular recognition of small ligands is a central phenomenon involved in all biological processes. We demonstrate herein that the molecular recognition of a photochromic ligand, dihydroindolizine (DHI), by serine protease α-chymotrypsin (CHT) leads to the photo-control of enzymatic activity. We synthesized and optically characterized the photochromic DHI. Light-induced reversible pyrroline ring opening and a consequent thermal back reaction via 1,5-electrocyclization are responsible for the photochromic behavior. Furthermore, DHI inhibits the enzymatic activity of CHT in a photo-controlled manner. Simultaneous binding of the well-known inhibitors 4-nitrophenyl anthranilate (NPA) or proflavin (PF) in the presence of DHI displays spectral overlap between the emission of CHT-NPA or CHT-PF with the respective absorption of cis or trans DHI. The results suggest an opportunity to explore the binding site of DHI using Förster resonance energy transfer (FRET). Moreover, to more specifically evaluate the DHI binding interactions, we employed molecular docking calculations, which suggested binding near the hydrophobic site of Cys-1-Cys-122 residues. Variations in the electrostatic interactions of the two conformers of DHI adopt unfavorable conformations, leading to the allosteric inhibition of enzymatic activity.

Optical implementation of a feature-based neural network with application to automatic target recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1993-01-01

An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

Development of Targeted, Enzyme-Activated Nano-Conjugates for Hepatic Cancer Therapy

NASA Astrophysics Data System (ADS)

Kuruvilla, Sibu Philip

Hepatocellular carcinoma (HCC) is the 5th most commonly-occurring cancer worldwide and the 2nd highest cause for cancer-related deaths globally. The current treatment strategy is the direct injection of a chemotherapeutic agent (e.g. doxorubicin; DOX) into the hepatic artery, through a process called hepatic arterial infusion (HAI). Unfortunately, HAI is severely hindered by limited therapeutic efficacy against the tumor and high systemic toxicity to surrounding organs (e.g. cardiotoxicity). This thesis focuses on the development of a targeted, nanoparticle-based drug delivery system aimed to improve the clinical treatment of HCC. In particular, we employ generation 5 (G5) poly(amido amine) (PAMAM) dendrimers targeted to hepatic cancer cells via N-acetylgalactosamine (NAcGal) ligands attached to the surface through a poly(ethylene glycol) (PEG) brush. DOX is attached to the G5 surface through two different enzyme-sensitive linkages, L3 or L4, to achieve controllable release of the drug inside hepatic cancer cells. The combination of NAcGal-PEG targeting branches with either L3- or L4-DOX linkages led to the development of P1 and P2 particles, respectively. In Part 1, we discuss the development of these particles and measure their ability to target and kill hepatic cancer cells in vitro. In Part 2, we investigate the antitumor activity of P1 and P2 particles in tumor-bearing mice in comparison to the free drug, and we measure the cardiac function of mice undergoing treatment to assess differences in DOX-induced cardiotoxicity. Finally, in Part 3, we explore multi-valent targeting of G5 dendrimers in pursuit of further improving their specificity to hepatic cancer cells. Ultimately, this thesis provides insight into the utility of nanoparticle-based drug delivery systems that can potentially be translated to the clinic to improve cancer therapy.

A robust algorithm for automated target recognition using precomputed radar cross sections

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2004-09-01

Passive radar is an emerging technology that offers a number of unique benefits, including covert operation. Many such systems are already capable of detecting and tracking aircraft. The goal of this work is to develop a robust algorithm for adding automated target recognition (ATR) capabilities to existing passive radar systems. In previous papers, we proposed conducting ATR by comparing the precomputed RCS of known targets to that of detected targets. To make the precomputed RCS as accurate as possible, a coordinated flight model is used to estimate aircraft orientation. Once the aircraft's position and orientation are known, it is possible to determine the incident and observed angles on the aircraft, relative to the transmitter and receiver. This makes it possible to extract the appropriate radar cross section (RCS) from our simulated database. This RCS is then scaled to account for propagation losses and the receiver's antenna gain. A Rician likelihood model compares these expected signals from different targets to the received target profile. We have previously employed Monte Carlo runs to gauge the probability of error in the ATR algorithm; however, generation of a statistically significant set of Monte Carlo runs is computationally intensive. As an alternative to Monte Carlo runs, we derive the relative entropy (also known as Kullback-Liebler distance) between two Rician distributions. Since the probability of Type II error in our hypothesis testing problem can be expressed as a function of the relative entropy via Stein's Lemma, this provides us with a computationally efficient method for determining an upper bound on our algorithm's performance. It also provides great insight into the types of classification errors we can expect from our algorithm. This paper compares the numerically approximated probability of Type II error with the results obtained from a set of Monte Carlo runs.

Whole CMV Proteome Pattern Recognition Analysis after HSCT Identifies Unique Epitope Targets Associated with the CMV Status

PubMed Central

Pérez-Bercoff, Lena; Valentini, Davide; Gaseitsiwe, Simani; Mahdavifar, Shahnaz; Schutkowski, Mike; Poiret, Thomas; Pérez-Bercoff, Åsa; Ljungman, Per; Maeurer, Markus J.

2014-01-01

Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution. PMID:24740411

Automatic target recognition and detection in infrared imagery under cluttered background

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Koç, Aykut; Alatan, A. Aydın.

2017-10-01

Visual object classification has long been studied in visible spectrum by utilizing conventional cameras. Since the labeled images has recently increased in number, it is possible to train deep Convolutional Neural Networks (CNN) with significant amount of parameters. As the infrared (IR) sensor technology has been improved during the last two decades, labeled images extracted from IR sensors have been started to be used for object detection and recognition tasks. We address the problem of infrared object recognition and detection by exploiting 15K images from the real-field with long-wave and mid-wave IR sensors. For feature learning, a stacked denoising autoencoder is trained in this IR dataset. To recognize the objects, the trained stacked denoising autoencoder is fine-tuned according to the binary classification loss of the target object. Once the training is completed, the test samples are propagated over the network, and the probability of the test sample belonging to a class is computed. Moreover, the trained classifier is utilized in a detect-by-classification method, where the classification is performed in a set of candidate object boxes and the maximum confidence score in a particular location is accepted as the score of the detected object. To decrease the computational complexity, the detection step at every frame is avoided by running an efficient correlation filter based tracker. The detection part is performed when the tracker confidence is below a pre-defined threshold. The experiments conducted on the real field images demonstrate that the proposed detection and tracking framework presents satisfactory results for detecting tanks under cluttered background.

Hierarchical Context Modeling for Video Event Recognition.

PubMed

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Utilization of peptide carrier system to improve intestinal absorption: targeting prolidase as a prodrug-converting enzyme

NASA Technical Reports Server (NTRS)

Bai, J. P.; Hu, M.; Subramanian, P.; Mosberg, H. I.; Amidon, G. L.

1992-01-01

The feasibility of targeting prolidase as a peptide prodrug-converting enzyme has been examined. The enzymatic hydrolysis by prolidase of substrates for the peptide transporter L-alpha-methyldopa-pro and several dipeptide analogues without an N-terminal alpha-amino group (phenylpropionylproline, phenylacetylproline, N-benzoylproline, and N-acetylproline) was investigated. The Michaelis-Menten parameters Km and Vmax for L-alpha-methyldopa-pro are 0.09 +/- 0.02 mM and 3.98 +/- 0.25 mumol/min/mg protein, respectively. However, no hydrolysis of the dipeptide analogues without an N-terminal alpha-amino group is observed, suggesting that an N-terminal alpha-amino group is required for prolidase activity. These results demonstrate that prolidase may serve as a prodrug-converting enzyme for the dipeptide-type prodrugs, utilizing the peptide carrier for transport of prodrugs into the mucosal cells and prolidase, a cytosolic enzyme, to release the drug. However, a free alpha-amino group appears to be necessary for prolidase hydrolysis.

Advanced development of immobilized enzyme reactors

NASA Technical Reports Server (NTRS)

Jolly, Clifford D.; Schussel, Leonard J.; Carter, Layne

1991-01-01

Fixed-bed reactors have been used at NASA-Marshall to purify wastewater generated by an end-use equipment facility, on the basis of a combination of multifiltration unibeds and enzyme unibeds. The enzyme beds were found to effectively remove such targeted organics as urea, alcohols, and aldehydes, down to levels lying below detection limits. The enzyme beds were also found to remove organic contaminants not specifically targeted.

A cascading activity-based probe sequentially targets E1–E2–E3 ubiquitin enzymes

PubMed Central

Mulder, Monique P.C.; Witting, Katharina; Berlin, Ilana; Pruneda, Jonathan N.; Wu, Kuen-Phon; Chang, Jer-Gung; Merkx, Remco; Bialas, Johanna; Groettrup, Marcus; Vertegaal, Alfred C.O.; Schulman, Brenda A.; Komander, David; Neefjes, Jacques; Oualid, Farid El; Ovaa, Huib

2016-01-01

Post-translational modifications of proteins with ubiquitin (Ub) and ubiquitin-like (Ubl) modifiers, orchestrated by a cascade of specialized E1, E2 and E3 enzymes, control a staggering breadth of cellular processes. To monitor catalysis along these complex reaction pathways, we developed a cascading activity-based probe, UbDha. Akin to the native Ub, upon ATP-dependent activation by the E1, UbDha can travel downstream to the E2 (and subsequently E3) enzymes through sequential trans-thioesterifications. Unlike the native Ub, at each step along the cascade UbDha has the option to react irreversibly with active site cysteine residues of target enzymes, thus enabling their detection. We show that our cascading probe ‘hops’ and ‘traps’ catalytically active ubiquitin-modifying enzymes (but not their substrates) by a mechanism diversifiable to Ubls. Our founder methodology, amenable to structural studies, proteome-wide profiling and monitoring of enzymatic activities in living cells, presents novel and versatile tools to interrogate the Ub/Ubl cascades. PMID:27182664

Conformational states and recognition of amyloidogenic peptides of human insulin-degrading enzyme.

PubMed

McCord, Lauren A; Liang, Wenguang G; Dowdell, Evan; Kalas, Vasilios; Hoey, Robert J; Koide, Akiko; Koide, Shohei; Tang, Wei-Jen

2013-08-20

Insulin-degrading enzyme (IDE) selectively degrades the monomer of amyloidogenic peptides and contributes to clearance of amyloid β (Aβ). Thus, IDE retards the progression of Alzheimer's disease. IDE possesses an enclosed catalytic chamber that engulfs and degrades its peptide substrates; however, the molecular mechanism of IDE function, including substrate access to the chamber and recognition, remains elusive. Here, we captured a unique IDE conformation by using a synthetic antibody fragment as a crystallization chaperone. An unexpected displacement of a door subdomain creates an ~18-Å opening to the chamber. This swinging-door mechanism permits the entry of short peptides into the catalytic chamber and disrupts the catalytic site within IDE door subdomain. Given the propensity of amyloidogenic peptides to convert into β-strands for their polymerization into amyloid fibrils, they also use such β-strands to stabilize the disrupted catalytic site resided at IDE door subdomain for their degradation by IDE. Thus, action of the swinging door allows IDE to recognize amyloidogenicity by substrate-induced stabilization of the IDE catalytic cleft. Small angle X-ray scattering (SAXS) analysis revealed that IDE exists as a mixture of closed and open states. These open states, which are distinct from the swinging door state, permit entry of larger substrates (e.g., Aβ, insulin) to the chamber and are preferred in solution. Mutational studies confirmed the critical roles of the door subdomain and hinge loop joining the N- and C-terminal halves of IDE for catalysis. Together, our data provide insights into the conformational changes of IDE that govern the selective destruction of amyloidogenic peptides.

Control of working memory: effects of attention training on target recognition and distractor salience in an auditory selection task.

PubMed

Melara, Robert D; Tong, Yunxia; Rao, Aparna

2012-01-09

Behavioral and electrophysiological measures of target and distractor processing were examined in an auditory selective attention task before and after three weeks of distractor suppression training. Behaviorally, training improved target recognition and led to less conservative and more rapid responding. Training also effectively shortened the temporal distance between distractors and targets needed to achieve a fixed level of target sensitivity. The effects of training on event-related potentials were restricted to the distracting stimulus: earlier N1 latency, enhanced P2 amplitude, and weakened P3 amplitude. Nevertheless, as distractor P2 amplitude increased, so too did target P3 amplitude, connecting experience-dependent changes in distractor processing with greater distinctiveness of targets in working memory. We consider the effects of attention training on the processing priorities, representational noise, and inhibitory processes operating in working memory. Copyright © 2011 Elsevier B.V. All rights reserved.

Intact suppression of increased false recognition in schizophrenia.

PubMed

Weiss, Anthony P; Dodson, Chad S; Goff, Donald C; Schacter, Daniel L; Heckers, Stephan

2002-09-01

Recognition memory is impaired in patients with schizophrenia, as they rely largely on item familiarity, rather than conscious recollection, to make mnemonic decisions. False recognition of novel items (foils) is increased in schizophrenia and may relate to this deficit in conscious recollection. By studying pictures of the target word during encoding, healthy adults can suppress false recognition. This study examined the effect of pictorial encoding on subsequent recognition of repeated foils in patients with schizophrenia. The study included 40 patients with schizophrenia and 32 healthy comparison subjects. After incidental encoding of 60 words or pictures, subjects were tested for recognition of target items intermixed with 60 new foils. These new foils were subsequently repeated following either a two- or 24-word delay. Subjects were instructed to label these repeated foils as new and not to mistake them for old target words. Schizophrenic patients showed greater overall false recognition of repeated foils. The rate of false recognition of repeated foils was lower after picture encoding than after word encoding. Despite higher levels of false recognition of repeated new items, patients and comparison subjects demonstrated a similar degree of false recognition suppression after picture, as compared to word, encoding. Patients with schizophrenia displayed greater false recognition of repeated foils than comparison subjects, suggesting both a decrement of item- (or source-) specific recollection and a consequent reliance on familiarity in schizophrenia. Despite these deficits, presenting pictorial information at encoding allowed schizophrenic subjects to suppress false recognition to a similar degree as the comparison group, implying the intact use of a high-level cognitive strategy in this population.

Targeting Heparan Sulfate Proteoglycans and their Modifying Enzymes to Enhance Anticancer Chemotherapy Efficacy and Overcome Drug Resistance.

PubMed

Lanzi, Cinzia; Zaffaroni, Nadia; Cassinelli, Giuliana

2017-01-01

Targeting heparan sulfate proteoglycans (HSPGs) and enzymes involved in heparan sulfate (HS) chain editing is emerging as a new anticancer strategy. The involvement of HSPGs in tumor cell signaling, inflammation, angiogenesis and metastasis indicates that agents able to inhibit aberrant HSPG functions can potentially act as multitarget drugs affecting both tumor cell growth and the supportive boost provided by the microenvironment. Moreover, accumulating evidence supports that an altered expression or function of HSPGs, or of the complex enzyme system regulating their activities, can also depress the tumor response to anticancer treatments in several tumor types. Thereby, targeting HSPGs or HSPG modifying enzymes appears an appealing approach to enhance chemotherapy efficacy. A great deal of effort from academia and industry has led to the development of agents mimicking HS, and/or inhibiting HSPG modifying enzymes. Inhibitors of Sulf-2, an endosulfatase that edits the HS sulfation pattern, and inhibitors of heparanase, the endoglycosidase that produces functional HS fragments, appear particularly promising. In fact, a Sulf-2 inhibitor (OKN-007), and two heparanase inhibitors/HS mimics (roneparstat, PG545) are currently under early clinical investigation. In this review, we summarized preclinical studies in experimental tumor models of the main chemical classes of Sulf-2 and heparanase inhibitors. We described examples of different mechanisms through which heparanase and HSPGs, often in cooperation, may impact tumor sensitivity to various antitumor agents. Finally, we reported a few preclinical studies showing increased antitumor efficacy obtained with the use of candidate clinical HS mimics in combination regimens. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Engineering of a target site-specific recombinase by a combined evolution- and structure-guided approach

PubMed Central

Abi-Ghanem, Josephine; Chusainow, Janet; Karimova, Madina; Spiegel, Christopher; Hofmann-Sieber, Helga; Hauber, Joachim; Buchholz, Frank; Pisabarro, M. Teresa

2013-01-01

Site-specific recombinases (SSRs) can perform DNA rearrangements, including deletions, inversions and translocations when their naive target sequences are placed strategically into the genome of an organism. Hence, in order to employ SSRs in heterologous hosts, their target sites have to be introduced into the genome of an organism before the enzyme can be practically employed. Engineered SSRs hold great promise for biotechnology and advanced biomedical applications, as they promise to extend the usefulness of SSRs to allow efficient and specific recombination of pre-existing, natural genomic sequences. However, the generation of enzymes with desired properties remains challenging. Here, we use substrate-linked directed evolution in combination with molecular modeling to rationally engineer an efficient and specific recombinase (sTre) that readily and specifically recombines a sequence present in the HIV-1 genome. We elucidate the role of key residues implicated in the molecular recognition mechanism and we present a rationale for sTre’s enhanced specificity. Combining evolutionary and rational approaches should help in accelerating the generation of enzymes with desired properties for use in biotechnology and biomedicine. PMID:23275541

Methyl-hydroxylamine as an efficacious antibacterial agent that targets the ribonucleotide reductase enzyme.

PubMed

Julián, Esther; Baelo, Aida; Gavaldà, Joan; Torrents, Eduard

2015-01-01

The emergence of multidrug-resistant bacteria has encouraged vigorous efforts to develop antimicrobial agents with new mechanisms of action. Ribonucleotide reductase (RNR) is a key enzyme in DNA replication that acts by converting ribonucleotides into the corresponding deoxyribonucleotides, which are the building blocks of DNA replication and repair. RNR has been extensively studied as an ideal target for DNA inhibition, and several drugs that are already available on the market are used for anticancer and antiviral activity. However, the high toxicity of these current drugs to eukaryotic cells does not permit their use as antibacterial agents. Here, we present a radical scavenger compound that inhibited bacterial RNR, and the compound's activity as an antibacterial agent together with its toxicity in eukaryotic cells were evaluated. First, the efficacy of N-methyl-hydroxylamine (M-HA) in inhibiting the growth of different Gram-positive and Gram-negative bacteria was demonstrated, and no effect on eukaryotic cells was observed. M-HA showed remarkable efficacy against Mycobacterium bovis BCG and Pseudomonas aeruginosa. Thus, given the M-HA activity against these two bacteria, our results showed that M-HA has intracellular antimycobacterial activity against BCG-infected macrophages, and it is efficacious in partially disassembling and inhibiting the further formation of P. aeruginosa biofilms. Furthermore, M-HA and ciprofloxacin showed a synergistic effect that caused a massive reduction in a P. aeruginosa biofilm. Overall, our results suggest the vast potential of M-HA as an antibacterial agent, which acts by specifically targeting a bacterial RNR enzyme.

Methyl-Hydroxylamine as an Efficacious Antibacterial Agent That Targets the Ribonucleotide Reductase Enzyme

PubMed Central

Julián, Esther; Baelo, Aida; Gavaldà, Joan; Torrents, Eduard

2015-01-01

The emergence of multidrug-resistant bacteria has encouraged vigorous efforts to develop antimicrobial agents with new mechanisms of action. Ribonucleotide reductase (RNR) is a key enzyme in DNA replication that acts by converting ribonucleotides into the corresponding deoxyribonucleotides, which are the building blocks of DNA replication and repair. RNR has been extensively studied as an ideal target for DNA inhibition, and several drugs that are already available on the market are used for anticancer and antiviral activity. However, the high toxicity of these current drugs to eukaryotic cells does not permit their use as antibacterial agents. Here, we present a radical scavenger compound that inhibited bacterial RNR, and the compound's activity as an antibacterial agent together with its toxicity in eukaryotic cells were evaluated. First, the efficacy of N-methyl-hydroxylamine (M-HA) in inhibiting the growth of different Gram-positive and Gram-negative bacteria was demonstrated, and no effect on eukaryotic cells was observed. M-HA showed remarkable efficacy against Mycobacterium bovis BCG and Pseudomonas aeruginosa. Thus, given the M-HA activity against these two bacteria, our results showed that M-HA has intracellular antimycobacterial activity against BCG-infected macrophages, and it is efficacious in partially disassembling and inhibiting the further formation of P. aeruginosa biofilms. Furthermore, M-HA and ciprofloxacin showed a synergistic effect that caused a massive reduction in a P. aeruginosa biofilm. Overall, our results suggest the vast potential of M-HA as an antibacterial agent, which acts by specifically targeting a bacterial RNR enzyme. PMID:25782003

Social appraisal influences recognition of emotions.

PubMed

Mumenthaler, Christian; Sander, David

2012-06-01

The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved

Microbubble Enzyme-Linked Immunosorbent Assay for the Detection of Targeted Microbubbles in in Vitro Static Binding Assays.

PubMed

Wischhusen, Jennifer; Padilla, Frederic

2017-07-01

Targeted microbubbles (MBs) are ultrasound contrast agents that are functionalized with a ligand for ultrasound molecular imaging of endothelial markers. Novel targeted MBs are characterized in vitro by incubation in protein-coated wells, followed by binding quantification by microscopy or ultrasound imaging. Both methods provide operator-dependent results: Between 3 and 20 fields of view from a heterogeneous sample are typically selected for analysis by microscopy, and in ultrasound imaging, different acoustic settings affect signal intensities. This study proposes a new method to reproducibly quantify MB binding based on enzyme-linked immunosorbent assay (ELISA), in which bound MBs are revealed with an enzyme-linked antibody. MB-ELISA was adapted to in vitro static binding assays, incubating the MBs in inverted position or by agitation, and compared with microscopy. The specificity and sensitivity of MB-ELISA enable the reliable quantification of MB binding in a rapid, high-throughput and whole-well analysis, facilitating the characterization of new targeted contrast agents. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Identification of the RNA recognition element of the RBPMS family of RNA-binding proteins and their transcriptome-wide mRNA targets

PubMed Central

Farazi, Thalia A.; Leonhardt, Carl S.; Mukherjee, Neelanjan; Mihailovic, Aleksandra; Li, Song; Max, Klaas E.A.; Meyer, Cindy; Yamaji, Masashi; Cekan, Pavol; Jacobs, Nicholas C.; Gerstberger, Stefanie; Bognanni, Claudia; Larsson, Erik; Ohler, Uwe; Tuschl, Thomas

2014-01-01

Recent studies implicated the RNA-binding protein with multiple splicing (RBPMS) family of proteins in oocyte, retinal ganglion cell, heart, and gastrointestinal smooth muscle development. These RNA-binding proteins contain a single RNA recognition motif (RRM), and their targets and molecular function have not yet been identified. We defined transcriptome-wide RNA targets using photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) in HEK293 cells, revealing exonic mature and intronic pre-mRNA binding sites, in agreement with the nuclear and cytoplasmic localization of the proteins. Computational and biochemical approaches defined the RNA recognition element (RRE) as a tandem CAC trinucleotide motif separated by a variable spacer region. Similar to other mRNA-binding proteins, RBPMS family of proteins relocalized to cytoplasmic stress granules under oxidative stress conditions suggestive of a support function for mRNA localization in large and/or multinucleated cells where it is preferentially expressed. PMID:24860013

Structure-guided Discovery of Dual-recognition Chemibodies.

PubMed

Cheng, Alan C; Doherty, Elizabeth M; Johnstone, Sheree; DiMauro, Erin F; Dao, Jennifer; Luthra, Abhinav; Ye, Jay; Tang, Jie; Nixey, Thomas; Min, Xiaoshan; Tagari, Philip; Miranda, Les P; Wang, Zhulun

2018-05-15

Small molecules and antibodies each have advantages and limitations as therapeutics. Here, we present for the first time to our knowledge, the structure-guided design of "chemibodies" as small molecule-antibody hybrids that offer dual recognition of a single target by both a small molecule and an antibody, using DPP-IV enzyme as a proof of concept study. Biochemical characterization demonstrates that the chemibodies present superior DPP-IV inhibition compared to either small molecule or antibody component alone. We validated our design by successfully solving a co-crystal structure of a chemibody in complex with DPP-IV, confirming specific binding of the small molecule portion at the interior catalytic site and the Fab portion at the protein surface. The discovery of chemibodies presents considerable potential for novel therapeutics that harness the power of both small molecule and antibody modalities to achieve superior specificity, potency, and pharmacokinetic properties.

Domain Regeneration for Cross-Database Micro-Expression Recognition

NASA Astrophysics Data System (ADS)

Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

2018-05-01

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

User acceptance of intelligent avionics: A study of automatic-aided target recognition

NASA Technical Reports Server (NTRS)

Becker, Curtis A.; Hayes, Brian C.; Gorman, Patrick C.

1991-01-01

User acceptance of new support systems typically was evaluated after the systems were specified, designed, and built. The current study attempts to assess user acceptance of an Automatic-Aided Target Recognition (ATR) system using an emulation of such a proposed system. The detection accuracy and false alarm level of the ATR system were varied systematically, and subjects rated the tactical value of systems exhibiting different performance levels. Both detection accuracy and false alarm level affected the subjects' ratings. The data from two experiments suggest a cut-off point in ATR performance below which the subjects saw little tactical value in the system. An ATR system seems to have obvious tactical value only if it functions at a correct detection rate of 0.7 or better with a false alarm level of 0.167 false alarms per square degree or fewer.

Colorimetric Aptasensor Based on Enzyme for the Detection of Vibrio parahemolyticus.

PubMed

Wu, Shijia; Wang, Yinqiu; Duan, Nuo; Ma, Haile; Wang, Zhouping

2015-09-09

A simple colorimetric aptasensor system has been developed to detect Vibrio parahemolyticus. Magnetic nanoparticles (MNPs) are synthesized and conjugated with specific aptamers against target and used as capture probes. In addition, this method employs gold nanoparticles (AuNPs) as carriers of horseradish peroxidase (HRP) and aptamers, which served as signal probes. In the presence of target, a "sandwich-type" complex of AuNPs-HRP-aptamer-target-aptamer-MNPs is formed through specific recognition of aptamers and corresponding target. As a result, HRP molecules confined at the surface of the "sandwich" complexes catalyze the enzyme substrate, 3,3',5,5'-tetramethylbenzidine (TMB) and H2O2 and generate an optical signal. Under optimal conditions, the signals are linearly dependent on V. parahemolyticus concentrations from 10 to 10(6) colony-forming units (cfu)/mL in a logarithmic plot, with a limit of detection of 10 cfu/mL. Owing to AuNPs, a large amount of HRP could be loaded, resulting in an amplified signal, and the sensitivity would be improved. This strategy has the potential of being extended to the construction of simple monitor systems for a variety of biomolecules related to food safety.

Indoleamine-2,3-dioxygenase, an immunosuppressive enzyme that inhibits natural killer cell function, as a useful target for ovarian cancer therapy

PubMed Central

WANG, DONGDONG; SAGA, YASUSHI; MIZUKAMI, HIROAKI; SATO, NAOTO; NONAKA, HIROAKI; FUJIWARA, HIROYUKI; TAKEI, YUJI; MACHIDA, SHIZUO; TAKIKAWA, OSAMU; OZAWA, KEIYA; SUZUKI, MITSUAKI

2012-01-01

This study examined the role of the immunosuppressive enzyme indoleamine-2,3-dioxygenase (IDO) in ovarian cancer progression, and the possible application of this enzyme as a target for ovarian cancer therapy. We transfected a short hairpin RNA vector targeting IDO into the human ovarian cancer cell line SKOV-3, that constitutively expresses IDO and established an IDO downregulated cell line (SKOV-3/shIDO) to determine whether inhibition of IDO mediates the progression of ovarian cancer. IDO downregulation suppressed tumor growth and peritoneal dissemination in vivo, without influencing cancer cell growth. Moreover, IDO downregulation enhanced the sensitivity of cancer cells to natural killer (NK) cells in vitro, and promoted NK cell accumulation in the tumor stroma in vivo. These findings indicate that downregulation of IDO controls ovarian cancer progression by activating NK cells, suggesting IDO targeting as a potential therapy for ovarian cancer. PMID:22179492

A novel double recognition enzyme-linked immunosorbent assay based on the nucleocapsid protein for early detection of European porcine reproductive and respiratory syndrome virus infection.

PubMed

Venteo, A; Rebollo, B; Sarraseca, J; Rodriguez, M J; Sanz, A

2012-04-01

Precise and rapid detection of porcine reproductive respiratory syndrome virus (PRRSV) infection in swine farms is critical. Improvement of control procedures, such as testing incoming gilt and surveillance of seronegative herds requires more rapid and sensitive methods. However, standard serological techniques detect mainly IgG antibodies. A double recognition enzyme-linked immunosorbent assay (DR-ELISA) was developed for detection of antibodies specific to European PRRSV. This new assay can recognize both IgM and IgG antibodies to PRSSV which might be useful for detecting in routine surveillance assays pigs that are in the very early stages of infection and missed by conventional assays detecting only IgG antibodies. DR-ELISA is based on the double recognition of antigen by antibody. In this study, the recombinant nucleocapsid protein (N) of PRRSV was used both as the coating and the enzyme-conjugated antigen. To evaluate the sensitivity of the assay at early stages of the infection, sera from 69 pigs infected with PRRSV were collected during successive days post infection (pi) and tested. While standard methods showed low sensitivity rates before day 14 pi, DR-ELISA detected 88.4% seropositive samples at day 7 showing greater sensitivity at early stages of the infection. Further studies were carried out to assess the efficiency of the new assay, and the results showed DR-ELISA to be a sensitive and accurate method for early diagnosis of EU-PRRSV infection. Copyright © 2012 Elsevier B.V. All rights reserved.

Repurposing Suzuki Coupling Reagents as a Directed Fragment Library Targeting Serine Hydrolases and Related Enzymes.

PubMed

Lanier, Marion; Cole, Derek C; Istratiy, Yelena; Klein, Michael G; Schwartz, Phillip A; Tjhen, Richard; Jennings, Andy; Hixon, Mark S

2017-06-22

Serine hydrolases are susceptible to potent reversible inhibition by boronic acids. Large collections of chemically diverse boronic acid fragments are commercially available because of their utility in coupling chemistry. We repurposed the approximately 650 boronic acid reagents in our collection as a directed fragment library targeting serine hydrolases and related enzymes. Highly efficient hits (LE > 0.6) often result. The utility of the approach is illustrated with the results against autotaxin, a phospholipase implicated in cardiovascular disease.

Rational design of a split-Cas9 enzyme complex.

PubMed

Wright, Addison V; Sternberg, Samuel H; Taylor, David W; Staahl, Brett T; Bardales, Jorge A; Kornfeld, Jack E; Doudna, Jennifer A

2015-03-10

Cas9, an RNA-guided DNA endonuclease found in clustered regularly interspaced short palindromic repeats (CRISPR) bacterial immune systems, is a versatile tool for genome editing, transcriptional regulation, and cellular imaging applications. Structures of Streptococcus pyogenes Cas9 alone or bound to single-guide RNA (sgRNA) and target DNA revealed a bilobed protein architecture that undergoes major conformational changes upon guide RNA and DNA binding. To investigate the molecular determinants and relevance of the interlobe rearrangement for target recognition and cleavage, we designed a split-Cas9 enzyme in which the nuclease lobe and α-helical lobe are expressed as separate polypeptides. Although the lobes do not interact on their own, the sgRNA recruits them into a ternary complex that recapitulates the activity of full-length Cas9 and catalyzes site-specific DNA cleavage. The use of a modified sgRNA abrogates split-Cas9 activity by preventing dimerization, allowing for the development of an inducible dimerization system. We propose that split-Cas9 can act as a highly regulatable platform for genome-engineering applications.

Rational design of a split-Cas9 enzyme complex

DOE PAGES

Wright, Addison V.; Sternberg, Samuel H.; Taylor, David W.; ...

2015-02-23

Cas9, an RNA-guided DNA endonuclease found in clustered regularly interspaced short palindromic repeats (CRISPR) bacterial immune systems, is a versatile tool for genome editing, transcriptional regulation, and cellular imaging applications. Structures of Streptococcus pyogenes Cas9 alone or bound to single-guide RNA (sgRNA) and target DNA revealed a bilobed protein architecture that undergoes major conformational changes upon guide RNA and DNA binding. To investigate the molecular determinants and relevance of the interlobe rearrangement for target recognition and cleavage, we designed a split-Cas9 enzyme in which the nuclease lobe and α-helical lobe are expressed as separate polypeptides. The lobes do not interactmore » on their own, the sgRNA recruits them into a ternary complex that recapitulates the activity of full-length Cas9 and catalyzes site-specific DNA cleavage. The use of a modified sgRNA abrogates split-Cas9 activity by preventing dimerization, allowing for the development of an inducible dimerization system. We propose that split-Cas9 can act as a highly regulatable platform for genome-engineering applications.« less

Rational design of a split-Cas9 enzyme complex

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

Wright, Addison V.; Sternberg, Samuel H.; Taylor, David W.

Cas9, an RNA-guided DNA endonuclease found in clustered regularly interspaced short palindromic repeats (CRISPR) bacterial immune systems, is a versatile tool for genome editing, transcriptional regulation, and cellular imaging applications. Structures of Streptococcus pyogenes Cas9 alone or bound to single-guide RNA (sgRNA) and target DNA revealed a bilobed protein architecture that undergoes major conformational changes upon guide RNA and DNA binding. To investigate the molecular determinants and relevance of the interlobe rearrangement for target recognition and cleavage, we designed a split-Cas9 enzyme in which the nuclease lobe and α-helical lobe are expressed as separate polypeptides. The lobes do not interactmore » on their own, the sgRNA recruits them into a ternary complex that recapitulates the activity of full-length Cas9 and catalyzes site-specific DNA cleavage. The use of a modified sgRNA abrogates split-Cas9 activity by preventing dimerization, allowing for the development of an inducible dimerization system. We propose that split-Cas9 can act as a highly regulatable platform for genome-engineering applications.« less

Evolution of I-SceI Homing Endonucleases with Increased DNA Recognition Site Specificity

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

Joshi, Rakesh; Ho, Kwok Ki; Tenney, Kristen

2013-09-18

Elucidating how homing endonucleases undergo changes in recognition site specificity will facilitate efforts to engineer proteins for gene therapy applications. I-SceI is a monomeric homing endonuclease that recognizes and cleaves within an 18-bp target. It tolerates limited degeneracy in its target sequence, including substitution of a C:G{sub +4} base pair for the wild-type A:T{sub +4} base pair. Libraries encoding randomized amino acids at I-SceI residue positions that contact or are proximal to A:T{sub +4} were used in conjunction with a bacterial one-hybrid system to select I-SceI derivatives that bind to recognition sites containing either the A:T{sub +4} or the C:G{submore » +4} base pairs. As expected, isolates encoding wild-type residues at the randomized positions were selected using either target sequence. All I-SceI proteins isolated using the C:G{sub +4} recognition site included small side-chain substitutions at G100 and either contained (K86R/G100T, K86R/G100S and K86R/G100C) or lacked (G100A, G100T) a K86R substitution. Interestingly, the binding affinities of the selected variants for the wild-type A:T{sub +4} target are 4- to 11-fold lower than that of wild-type I-SceI, whereas those for the C:G{sub +4} target are similar. The increased specificity of the mutant proteins is also evident in binding experiments in vivo. These differences in binding affinities account for the observed -36-fold difference in target preference between the K86R/G100T and wild-type proteins in DNA cleavage assays. An X-ray crystal structure of the K86R/G100T mutant protein bound to a DNA duplex containing the C:G{sub +4} substitution suggests how sequence specificity of a homing enzyme can increase. This biochemical and structural analysis defines one pathway by which site specificity is augmented for a homing endonuclease.« less

Hyaluronan functionalizing QDs as turn-on fluorescent probe for targeted recognition CD44 receptor

NASA Astrophysics Data System (ADS)

Zhou, Shang; Huo, Danqun; Hou, Changjun; Yang, Mei; Fa, Huanbao

2017-09-01

The recognition of tumor markers in living cancer cells has attracted increasing interest. In the present study, the turn-on fluorescence probe was designed based on the fluorescence of thiolated chitosan-coated CdTe QDs (CdTe/TCS QDs) quenched by hyaluronan, which could provide the low background signal for sensitive cellular imaging. This system is expected to offer specific recognition of CD44 receptor over other substances owing to the specific affinity of hyaluronan and CD44 receptor ( 8-9 kcal/mol). The probe is stable in aqueous and has little toxicity to living cells; thus, it can be utilized for targeted cancer cell imaging. The living lung cancer cell imaging experiments further demonstrate its value in recognizing cell-surface CD44 receptor with turn-on mode. In addition, the probe can be used to recognize and differentiate the subtypes of lung cancer cells based on the difference of CD44 expression on the surface of lung cancer cells. And, the western blot test further confirmed that the expression level of the CD44 receptor in lung cancer cells is different. Therefore, this probe may be potentially applied in recognizing lung cancer cells with higher contrast and sensitivity and provide new tools for cancer prognosis and therapy. [Figure not available: see fulltext.

Four new type I restriction enzymes identified in Escherichia coli clinical isolates

PubMed Central

Kasarjian, Julie K. A.; Kodama, Yoshiaki; Iida, Masatake; Matsuda, Katsura; Ryu, Junichi

2005-01-01

Using a plasmid transformation method and the RM search computer program, four type I restriction enzymes with new recognition sites and two isoschizomers (EcoBI and Eco377I) were identified in a collection of clinical Escherichia coli isolates. These new enzymes were designated Eco394I, Eco826I, Eco851I and Eco912I. Their recognition sequences were determined to be GAC(5N)RTAAY, GCA(6N)CTGA, GTCA(6N)TGAY and CAC(5N)TGGC, respectively. A methylation sensitivity assay, using various synthetic oligonucleotides, was used to identify the adenines that prevent cleavage when methylated (underlined). These results suggest that type I enzymes are abundant in E.coli and many other bacteria, as has been inferred from bacterial genome sequencing projects. PMID:16040596

Drug effects on drug targets: inhibition of enzymes by neuroleptics, antimycotics, antibiotics and other drugs on human pathogenic amoebas and their anti-proliferative effects.

PubMed

Ondarza, Raúl N

2007-11-01

This paper reviews the inhibition of various enzymes by neuroleptics, anti-mycotics, antibiotics and other drugs on three species of human pathogenic amoebas, mainly Entamoeba histolytica, Acanthamoeba polyphaga and Naegleria fowleri, and their antiproliferative effects. A recent patent registered by Philip relates to the combination of an antibacterial formulation and antifungal agent for producing a therapeutically effective quantity of an antimicrobial that is suitable for suppressing or treating fungal growth. The rationale behind this patent focused on essential and valid targets with a description of the main pathogenic characteristics of these amoebas. The study of new targets, such as trypanothione and trypanothione reductase, and the drug effects of selected agents were arranged into six main groups: A) Inhibition of disulfide reducing enzymes by neuroleptics, antimycotics and antibiotics; B) Comparative evaluation of the efficacies of several drugs with antiproliferative activities; C) Inhibition of the enzymes for the synthesis of trypanothione, such as ornithine decarboxylase, spermidine synthase and trypanothione synthetase; D) Inhibition of the glycolytic enzyme PPi-dependent phosphofructokinase (PFK) from Entamoeba and Naegleria by pyrophosphate analogues, different from the host enzyme; E) Inhibition of enzymes secreted by these parasites to invade the human host, for example cysteine proteinases; and F) Inhibition of encystment pathways and cyst-wall assembly proteins.

Human target acquisition performance

NASA Astrophysics Data System (ADS)

Teaney, Brian P.; Du Bosq, Todd W.; Reynolds, Joseph P.; Thompson, Roger; Aghera, Sameer; Moyer, Steven K.; Flug, Eric; Espinola, Richard; Hixson, Jonathan

2012-06-01

The battlefield has shifted from armored vehicles to armed insurgents. Target acquisition (identification, recognition, and detection) range performance involving humans as targets is vital for modern warfare. The acquisition and neutralization of armed insurgents while at the same time minimizing fratricide and civilian casualties is a mounting concern. U.S. Army RDECOM CERDEC NVESD has conducted many experiments involving human targets for infrared and reflective band sensors. The target sets include human activities, hand-held objects, uniforms & armament, and other tactically relevant targets. This paper will define a set of standard task difficulty values for identification and recognition associated with human target acquisition performance.

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

Cognitive enhancers (Nootropics). Part 3: drugs interacting with targets other than receptors or enzymes. Disease-modifying drugs. Update 2014.

PubMed

Froestl, Wolfgang; Pfeifer, Andrea; Muhs, Andreas

2014-01-01

Scientists working in the field of Alzheimer's disease and, in particular, cognitive enhancers, are very productive. The review "Drugs interacting with Targets other than Receptors or Enzymes. Disease-modifying Drugs" was accepted in October 2012. In the last 20 months, new targets for the potential treatment of Alzheimer's disease were identified. Enormous progress was realized in the pharmacological characterization of natural products with cognitive enhancing properties. This review covers the evolution of research in this field through May 2014.

Cystatin C Properties Crucial for Uptake and Inhibition of Intracellular Target Enzymes*

PubMed Central

Wallin, Hanna; Abrahamson, Magnus; Ekström, Ulf

2013-01-01

To elucidate the molecular requirements for cancer cell internalization of the extracellular cysteine protease inhibitor cystatin C, 12 variants of the protein were produced and used for uptake experiments in MCF-7 cells. Variants with alterations in the cysteine cathepsin binding region ((Δ1–10)-, K5A-, R8G-, (R8G,L9G,V10G)-, (R8G,L9G,V10G,W106G)-, and W106G-cystatin C) were internalized to a very low extent compared with the wild-type inhibitor. Substitutions of N39 in the legumain binding region (N39K- and N39A-cystatin C) decreased the internalization and (R24A,R25A)-cystatin C, with substitutions of charged residues not involved in enzyme inhibition, was not taken up at all. Two variants, W106F- and K75A-cystatin C, showed that the internalization can be positively affected by engineering of the cystatin molecule. Microscopy revealed vesicular co-localization of internalized cystatin C with the lysosomal marker proteins cathepsin D and legumain. Activities of both cysteine cathepsins and legumain, possible target enzymes associated with cancer cell invasion and metastasis, were down-regulated in cell homogenates following cystatin C uptake. A positive effect on regulation of intracellular enzyme activity by a cystatin variant selected from uptake properties was illustrated by incubating cells with W106F-cystatin C. This resulted in more efficient down-regulation of intracellular legumain activity than when cells were incubated with wild-type cystatin C. Uptake experiments in prostate cancer cells corroborated that the cystatin C internalization is generally relevant and confirmed an increased uptake of W106F-cystatin C, in PC3 cells. Thus, intracellular cysteine proteases involved in cancer-promoting processes might be controled by cystatin uptake. PMID:23629651

Hetero-enzyme-based two-round signal amplification strategy for trace detection of aflatoxin B1 using an electrochemical aptasensor.

PubMed

Zheng, Wanli; Teng, Jun; Cheng, Lin; Ye, Yingwang; Pan, Daodong; Wu, Jingjing; Xue, Feng; Liu, Guodong; Chen, Wei

2016-06-15

An electrochemical aptasensor for trace detection of aflatoxin B1 (AFB1) was developed by using an aptamer as the recognition unit while adopting the telomerase and EXO III based two-round signal amplification strategy as the signal enhancement units. The telomerase amplification was used to elongate the ssDNA probes on the surface of gold nanoparticles, by which the signal response range of the signal-off model electrochemical aptasensor could be correspondingly enlarged. Then, the EXO III amplification was used to hydrolyze the 3'-end of the dsDNA after the recognition of target AFB1, which caused the release of bounded AFB1 into the sensing system, where it participated in the next recognition-sensing cycle. With this two-round signal amplified electrochemical aptasensor, target AFB1 was successfully measured at trace concentrations with excellent detection limit of 0.6*10(-4)ppt and satisfied specificity due to the excellent affinity of the aptamer against AFB1. Based on this designed two-round signal amplification strategy, both the sensing range and detection limit were greatly improved. This proposed ultrasensitive electrochemical aptasensor method was also validated by comparison with the classic instrumental methods. Importantly, this hetero-enzyme based two-round signal amplified electrochemical aptasensor offers a great promising protocol for ultrasensitive detection of AFB1 and other mycotoxins by replacing the core recognition sequence of the aptamer. Copyright © 2016 Elsevier B.V. All rights reserved.

Structural Basis for Conserved Regulation and Adaptation of the Signal Recognition Particle Targeting Complex.

PubMed

Wild, Klemens; Bange, Gert; Motiejunas, Domantas; Kribelbauer, Judith; Hendricks, Astrid; Segnitz, Bernd; Wade, Rebecca C; Sinning, Irmgard

2016-07-17

The signal recognition particle (SRP) is a ribonucleoprotein complex with a key role in targeting and insertion of membrane proteins. The two SRP GTPases, SRP54 (Ffh in bacteria) and FtsY (SRα in eukaryotes), form the core of the targeting complex (TC) regulating the SRP cycle. The architecture of the TC and its stimulation by RNA has been described for the bacterial SRP system while this information is lacking for other domains of life. Here, we present the crystal structures of the GTPase heterodimers of archaeal (Sulfolobus solfataricus), eukaryotic (Homo sapiens), and chloroplast (Arabidopsis thaliana) SRP systems. The comprehensive structural comparison combined with Brownian dynamics simulations of TC formation allows for the description of the general blueprint and of specific adaptations of the quasi-symmetric heterodimer. Our work defines conserved external nucleotide-binding sites for SRP GTPase activation by RNA. Structural analyses of the GDP-bound, post-hydrolysis states reveal a conserved, magnesium-sensitive switch within the I-box. Overall, we provide a general model for SRP cycle regulation by RNA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rational optimization of drug-target residence time: Insights from inhibitor binding to the S. aureus FabI enzyme-product complex

PubMed Central

Chang, Andrew; Schiebel, Johannes; Yu, Weixuan; Bommineni, Gopal R.; Pan, Pan; Baxter, Michael V.; Khanna, Avinash; Sotriffer, Christoph A.; Kisker, Caroline; Tonge, Peter J.

2013-01-01

Drug-target kinetics has recently emerged as an especially important facet of the drug discovery process. In particular, prolonged drug-target residence times may confer enhanced efficacy and selectivity in the open in vivo system. However, the lack of accurate kinetic and structural data for series of congeneric compounds hinders the rational design of inhibitors with decreased off-rates. Therefore, we chose the Staphylococcus aureus enoyl-ACP reductase (saFabI) - an important target for the development of new anti-staphylococcal drugs - as a model system to rationalize and optimize the drug-target residence time on a structural basis. Using our new, efficient and widely applicable mechanistically informed kinetic approach, we obtained a full characterization of saFabI inhibition by a series of 20 diphenyl ethers complemented by a collection of 9 saFabI-inhibitor crystal structures. We identified a strong correlation between the affinities of the investigated saFabI diphenyl ether inhibitors and their corresponding residence times, which can be rationalized on a structural basis. Due to its favorable interactions with the enzyme, the residence time of our most potent compound exceeds 10 hours. In addition, we found that affinity and residence time in this system can be significantly enhanced by modifications predictable by a careful consideration of catalysis. Our study provides a blueprint for investigating and prolonging drug-target kinetics and may aid in the rational design of long-residence-time inhibitors targeting the essential saFabI enzyme. PMID:23697754

Structural Insights Into the Recognition of Peroxisomal Targeting Signal 1 By Trypanosoma Brucei Peroxin 5

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

Sampathkumar, P.; Roach, C.; Michels, P.A.M.

2009-05-27

Glycosomes are peroxisome-like organelles essential for trypanosomatid parasites. Glycosome biogenesis is mediated by proteins called 'peroxins,' which are considered to be promising drug targets in pathogenic Trypanosomatidae. The first step during protein translocation across the glycosomal membrane of peroxisomal targeting signal 1 (PTS1)-harboring proteins is signal recognition by the cytosolic receptor peroxin 5 (PEX5). The C-terminal PTS1 motifs interact with the PTS1 binding domain (P1BD) of PEX5, which is made up of seven tetratricopeptide repeats. Obtaining diffraction-quality crystals of the P1BD of Trypanosoma brucei PEX5 (TbPEX5) required surface entropy reduction mutagenesis. Each of the seven tetratricopeptide repeats appears to havemore » a residue in the alpha(L) conformation in the loop connecting helices A and B. Five crystal structures of the P1BD of TbPEX5 were determined, each in complex with a hepta- or decapeptide corresponding to a natural or nonnatural PTS1 sequence. The PTS1 peptides are bound between the two subdomains of the P1BD. These structures indicate precise recognition of the C-terminal Leu of the PTS1 motif and important interactions between the PTS1 peptide main chain and up to five invariant Asn side chains of PEX5. The TbPEX5 structures reported here reveal a unique hydrophobic pocket in the subdomain interface that might be explored to obtain compounds that prevent relative motions of the subdomains and interfere selectively with PTS1 motif binding or release in trypanosomatids, and would therefore disrupt glycosome biogenesis and prevent parasite growth.« less

Enzymes and Enzyme Activity Encoded by Nonenveloped Viruses.

PubMed

Azad, Kimi; Banerjee, Manidipa; Johnson, John E

2017-09-29

Viruses are obligate intracellular parasites that rely on host cell machineries for their replication and survival. Although viruses tend to make optimal use of the host cell protein repertoire, they need to encode essential enzymatic or effector functions that may not be available or accessible in the host cellular milieu. The enzymes encoded by nonenveloped viruses-a group of viruses that lack any lipid coating or envelope-play vital roles in all the stages of the viral life cycle. This review summarizes the structural, biochemical, and mechanistic information available for several classes of enzymes and autocatalytic activity encoded by nonenveloped viruses. Advances in research and development of antiviral inhibitors targeting specific viral enzymes are also highlighted.

Challenging ocular image recognition

NASA Astrophysics Data System (ADS)

Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.

2011-06-01

Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

Active Site Gate Dynamics Modulate the Catalytic Activity of the Ubiquitination Enzyme E2-25K.

PubMed

Rout, Manoj K; Lee, Brian L; Lin, Aiyang; Xiao, Wei; Spyracopoulos, Leo

2018-05-03

The ubiquitin proteasome system (UPS) signals for degradation of proteins through attachment of K48-linked polyubiquitin chains, or alterations in protein-protein recognition through attachment of K63-linked chains. Target proteins are ubiquitinated in three sequential chemical steps by a three-component enzyme system. Ubiquitination, or E2 enzymes, catalyze the central step by facilitating reaction of a target protein lysine with the C-terminus of Ub that is attached to the active site cysteine of the E2 through a thioester bond. E2 reactivity is modulated by dynamics of an active site gate, whose central residue packs against the active site cysteine in a closed conformation. Interestingly, for the E2 Ubc13, which specifically catalyzes K63-linked ubiquitination, the central gate residue adopts an open conformation. We set out to determine if active site gate dynamics play a role in catalysis for E2-25K, which adopts the canonical, closed gate conformation, and which selectively synthesizes K48-linked ubiquitin chains. Gate dynamics were characterized using mutagenesis of key residues, combined with enzyme kinetics measurements, and main chain NMR relaxation. The experimental data were interpreted with all atom MD simulations. The data indicate that active site gate opening and closing rates for E2-25K are precisely balanced.

ROBIN: a platform for evaluating automatic target recognition algorithms: I. Overview of the project and presentation of the SAGEM DS competition

NASA Astrophysics Data System (ADS)

Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.

2008-04-01

The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set

Oxytocin increases bias, but not accuracy, in face recognition line-ups.

PubMed

Bate, Sarah; Bennetts, Rachel; Parris, Benjamin A; Bindemann, Markus; Udale, Robert; Bussunt, Amanda

2015-07-01

Previous work indicates that intranasal inhalation of oxytocin improves face recognition skills, raising the possibility that it may be used in security settings. However, it is unclear whether oxytocin directly acts upon the core face-processing system itself or indirectly improves face recognition via affective or social salience mechanisms. In a double-blind procedure, 60 participants received either an oxytocin or placebo nasal spray before completing the One-in-Ten task-a standardized test of unfamiliar face recognition containing target-present and target-absent line-ups. Participants in the oxytocin condition outperformed those in the placebo condition on target-present trials, yet were more likely to make false-positive errors on target-absent trials. Signal detection analyses indicated that oxytocin induced a more liberal response bias, rather than increasing accuracy per se. These findings support a social salience account of the effects of oxytocin on face recognition and indicate that oxytocin may impede face recognition in certain scenarios. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Enzymes involved in plastid-targeted phosphatidic acid synthesis are essential for Plasmodium yoelii liver stage development

PubMed Central

Lindner, Scott E.; Sartain, Mark J.; Hayes, Kiera; Harupa, Anke; Moritz, Robert L.; Kappe, Stefan H. I.; Vaughan, Ashley M.

2014-01-01

SUMMARY Malaria parasites scavenge nutrients from their host but also harbor enzymatic pathways for de novo macromolecule synthesis. One such pathway is apicoplast-targeted type II fatty acid synthesis, which is essential for late liver stage development in rodent malaria. It is likely that fatty acids synthesized in the apicoplast are ultimately incorporated into membrane phospholipids necessary for exoerythrocytic merozoite formation. We hypothesized that these synthesized fatty acids are being utilized for apicoplast-targeted phosphatidic acid synthesis, the phospholipid precursor. Phosphatidic acid is typically synthesized in a three-step reaction utilizing three enzymes: glycerol 3-phosphate dehydrogenase, glycerol 3-phosphate acyltransferase and lysophosphatidic acid acyltransferase. The Plasmodium genome is predicted to harbor genes for both apicoplast- and cytosol/endoplasmic reticulum-targeted phosphatidic synthesis. Our research shows that apicoplast-targeted P. yoelii glycerol 3-phosphate dehydrogenase and glycerol 3-phosphate acyltransferase are expressed only during liver stage development and deletion of the encoding genes resulted in late liver stage growth arrest and lack of merozoite differentiation. However, the predicted apicoplast-targeted lysophosphatidic acid acyltransferase gene was refractory to deletion and was expressed solely in the endoplasmic reticulum throughout the parasite lifecycle. Our results suggest that P. yoelii has an incomplete apicoplast-targeted phosphatidic acid synthesis pathway that is essential for liver stage maturation. PMID:24330260

Modeling guidance and recognition in categorical search: bridging human and computer object detection.

PubMed

Zelinsky, Gregory J; Peng, Yifan; Berg, Alexander C; Samaras, Dimitris

2013-10-08

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery.

Antibody-mediated enzyme replacement therapy targeting both lysosomal and cytoplasmic glycogen in Pompe disease.

PubMed

Yi, Haiqing; Sun, Tao; Armstrong, Dustin; Borneman, Scott; Yang, Chunyu; Austin, Stephanie; Kishnani, Priya S; Sun, Baodong

2017-05-01

Pompe disease is characterized by accumulation of both lysosomal and cytoplasmic glycogen primarily in skeletal and cardiac muscles. Mannose-6-phosphate receptor-mediated enzyme replacement therapy (ERT) with recombinant human acid α-glucosidase (rhGAA) targets the enzyme to lysosomes and thus is unable to digest cytoplasmic glycogen. Studies have shown that anti-DNA antibody 3E10 penetrates living cells and delivers "cargo" proteins to the cytosol or nucleus via equilibrative nucleoside transporter ENT2. We speculate that 3E10-mediated ERT with GAA will target both lysosomal and cytoplasmic glycogen in Pompe disease. A fusion protein (FabGAA) containing a humanized Fab fragment derived from the murine 3E10 antibody and the 110 kDa human GAA precursor was constructed and produced in CHO cells. Immunostaining with an anti-Fab antibody revealed that the Fab signals did not co-localize with the lysosomal marker LAMP2 in cultured L6 myoblasts or Pompe patient fibroblasts after incubation with FabGAA. Western blot with an anti-GAA antibody showed presence of the 150 kDa full-length FabGAA in the cell lysates, in addition to the 95- and 76 kDa processed forms of GAA that were also seen in the rhGAA-treated cells. Blocking of mannose-6-phosphate receptor with mannose-6-phosphate markedly reduced the 95- and the 76 kDa forms but not the 150 kDa form. In GAA-KO mice, FabGAA achieved similar treatment efficacy as rhGAA at an equal molar dose in reducing tissue glycogen contents. Our data suggest that FabGAA retains the ability of rhGAA to treat lysosomal glycogen accumulation and has the beneficial potential over rhGAA to reduce cytoplasmic glycogen storage in Pompe disease. FabGAA can be delivered to both the cytoplasm and lysosomes in cultured cells. FabGAA equally reduced lysosomal glycogen accumulation as rhGAA in GAA-KO mice. FabGAA has the beneficial potential over rhGAA to clear cytoplasmic glycogen. This study suggests a novel antibody-enzyme fusion protein therapy

Novel photoluminescence enzyme immunoassay based on supramolecular host-guest recognition using L-arginine/6-aza-2-thiothymine-stabilized gold nanocluster.

PubMed

Wang, Youmei; Lu, Minghua; Tang, Dianping

2018-06-30

A new photoluminescence (PL) enzyme immunoassay was designed for sensitive detection of aflatoxin B 1 (AFB 1 ) via an innovative enzyme substrate, 6-aza-2-thiothymine-stabilized gold nanocluster (AAT-AuNC) with L-arginine. The enzyme substrate with strong PL intensity was formed through supramolecular host-guest assembly between guanidine group of L-arginine and AAT capped on the surface of AuNC. Upon arginase introduction, the captured L-arginine was hydrolyzed into ornithine and urea, thus resulting in the decreasing PL intensity. Based on this principle, a novel competitive-type immunoreaction was first carried out on AFB 1 -bovine serum albumin (AFB 1 -BSA) conjugate-coated microplate, using arginase-labeled anti-AFB 1 antibody as the competitor. Under the optimum conditions, the PL intensity increased with the increment of target AFB 1 , and allowed the detection of the analyte at concentrations as low as 3.2 pg mL -1 (ppt). Moreover, L-arginine-AAT-AuNC-based PL enzyme immunoassay afforded good reproducibility and acceptable specificity. In addition, the accuracy of this methodology, referring to commercial AFB 1 ELISA kit, was evaluated to analyze naturally contaminated or spiked peanut samples, giving well-matched results between two methods, thus representing a useful scheme for practical application in quantitative monitoring of mycotoxins in foodstuff. Copyright © 2018 Elsevier B.V. All rights reserved.

The selenazal drug ebselen potently inhibits indoleamine 2,3-dioxygenase by targeting enzyme cysteine residues.

PubMed

Terentis, Andrew C; Freewan, Mohammed; Sempértegui Plaza, Tito S; Raftery, Mark J; Stocker, Roland; Thomas, Shane R

2010-01-26

The heme enzyme indoleamine 2,3-dioxygenase (IDO) plays an important immune regulatory role by catalyzing the oxidative degradation of l-tryptophan. Here we show that the selenezal drug ebselen is a potent IDO inhibitor. Exposure of human macrophages to ebselen inhibited IDO activity in a manner independent of changes in protein expression. Ebselen inhibited the activity of recombinant human IDO (rIDO) with an apparent inhibition constant of 94 +/- 17 nM. Optical and resonance Raman spectroscopy showed that ebselen altered the active site heme of rIDO by inducing a transition of the ferric heme iron from the predominantly high- to low-spin form and by lowering the vibrational frequency of the Fe-CO stretch of the CO complex, indicating an opening of the distal heme pocket. Substrate binding studies showed that ebselen enhanced nonproductive l-tryptophan binding, while circular dichroism indicated that the drug reduced the helical content and protein stability of rIDO. Thiol labeling and mass spectrometry revealed that ebselen reacted with multiple cysteine residues of IDO. Removal of cysteine-bound ebselen with dithiothreitol reversed the effects of the drug on the heme environment and significantly restored enzyme activity. These findings indicate that ebselen inhibits IDO activity by reacting with the enzyme's cysteine residues that result in changes to protein conformation and active site heme, leading to an increase in the level of nonproductive substrate binding. This study highlights that modification of cysteine residues is a novel and effective means of inhibiting IDO activity. It also suggests that IDO is under redox control and that the enzyme represents a previously unrecognized in vivo target of ebselen.

Targets for inhibition of HIV replication: entry, enzyme action, release and maturation.

PubMed

Sierra-Aragón, Saleta; Walter, Hauke

2012-01-01

Inhibition of HIV replication initially targeted viral enzymes, which are exclusively expressed by the virus and not present in the human cell. The development of reverse transcriptase (RT) inhibitors started with the discovery of antiretroviral activity of the nucleoside analog zidovudine in March 1987. Currently, six major classes of antiretroviral drugs are used for the treatment of HIV-infected patients: the RT inhibitors, nucleoside inhibitors and nonnucleoside inhibitors, the protease inhibitors, the integrase inhibitor raltegravir, the fusion inhibitor enfuvirtide (T-20), and the chemokine receptor 5 antagonist maraviroc. A seventh class, the maturation inhibitors, has not yet been approved as their effectiveness is impaired by HIV-1 polymorphisms naturally occurring in 30-40% of HIV-1 therapy-naive isolates. The use of antiretroviral combination therapy has proven to be effective in delaying progression to AIDS and to reconstitute the immune system of HIV-infected individuals. During the last 5 years, the introduction of the newest antiretrovirals has increased treatment efficacy tremendously. However, the development and accumulation of resistance to all antiretroviral drug classes are still a major problem. Additional targets will have to be defined to achieve the ultimate goal: the eradication of the virus from the infected human body. Copyright © 2012 S. Karger AG, Basel.

Efficient elimination of nonstoichiometric enzyme inhibitors from HTS hit lists.

PubMed

Habig, Michael; Blechschmidt, Anke; Dressler, Sigmar; Hess, Barbara; Patel, Viral; Billich, Andreas; Ostermeier, Christian; Beer, David; Klumpp, Martin

2009-07-01

High-throughput screening often identifies not only specific, stoichiometrically binding inhibitors but also undesired compounds that unspecifically interfere with the targeted activity by nonstoichiometrically binding, unfolding, and/or inactivating proteins. In this study, the effect of such unwanted inhibitors on several different enzyme targets was assessed based on screening results for over a million compounds. In particular, the shift in potency on variation of enzyme concentration was used as a means to identify nonstoichiometric inhibitors among the screening hits. These potency shifts depended on both compound structure and target enzyme. The approach was confirmed by statistical analysis of thousands of dose-response curves, which showed that the potency of competitive and therefore clearly stoichiometric inhibitors was not affected by increasing enzyme concentration. Light-scattering measurements of thermal protein unfolding further verified that compounds that stabilize protein structure by stoichiometric binding show the same potency irrespective of enzyme concentration. In summary, measuring inhibitor IC(50) values at different enzyme concentrations is a simple, cost-effective, and reliable method to identify and eliminate compounds that inhibit a specific target enzyme via nonstoichiometric mechanisms.

Potential protein targets of the peptidylarginine deiminase 2 and peptidylarginine deiminase 4 enzymes in rheumatoid synovial tissue and its possible meaning

PubMed Central

Badillo-Soto, Martha Adriana; Rodríguez-Rodríguez, Mayra; Pérez-Pérez, María Elena; Daza-Benitez, Leonel; Bollain-y-Goytia, Juan José; Carrillo-Jiménez, Miguel Angel; Avalos-Díaz, Esperanza; Herrera-Esparza, Rafael

2016-01-01

Objective The molecular mechanism of citrullination involves the calcium-dependent peptidylarginine deiminase (PAD) family of enzymes. These enzymes induce a stereochemical modification of normal proteins and transform them into autoantigens, which in rheumatoid arthritis trigger a complex cascade of joint inflammatory events followed by chronic synovitis, pannus formation, and finally, cartilage destruction. By hypothesizing that PAD2 and PAD4 enzymes produce autoantigens, we investigated five possible synovial protein targets of PAD enzymes. Material and Methods We measured PAD2, PAD4, and citrullinated proteins in 10 rheumatoid and 10 osteoarthritis synovial biopsies and then assessed the post-translational modifications of fibrinogen, cytokeratin, tubulin, IgG, and vimentin proteins using a double-fluorescence assay with specific antibodies and an affinity-purified anti-citrullinated peptide (CCP) antibody. The degree of co-localization was analyzed, and statistical significance was determined by ANOVA, Fisher’s exact test, and regression analysis. Results The principal results of this study demonstrated that citrullinated proteins, such as fibrinogen, IgG, and other probed proteins, were targets of PAD2 and PAD4 activity in rheumatoid synovial biopsies, whereas osteoarthritis biopsies were negative for this enzyme (p<0.0001). An analysis of citrullination sites using the UniProtKB/Swiss-Prot data bank predicts that the secondary structure of the analyzed proteins displays most of the sites for citrullination; a discussion regarding its possible meaning in terms of pathogenesis is made. Conclusion Our results support the conclusion that the synovial citrullination of proteins is PAD2 and PAD4 dependent. Furthermore, there is a collection of candidate proteins that can be citrullinated. PMID:27708970

A bio-recognition device developed onto nano-crystals of carbonate apatite for cell-targeted gene delivery.

PubMed

Chowdhury, E H; Akaike, Toshihiro

2005-05-20

The DNA delivery to mammalian cells is an essential tool for analyzing gene structure, regulation, and function. The approach holds great promise for the further development of gene therapy techniques and DNA vaccination strategies to treat and control diseases. Here, we report on the establishment of a cell-specific gene delivery and expression system by physical adsorption of a cell-recognition molecule on the nano-crystal surface of carbonate apatite. As a model, DNA/nano-particles were successfully coated with asialofetuin to facilitate uptake by hepatocyte-derived cell lines through the asialoglycoprotein receptor (ASGPr) and albumin to prevent non-specific interactions of the particles with cell-surface. The resulting composite particles with dual surface properties could accelerate DNA uptake and enhance expression to a notable extent. Nano-particles coated with transferrin in the same manner dramatically enhanced transgene expression in the corresponding receptor-bearing cells and thus our newly developed strategy represents a universal phenomenon for anchoring a bio-recognition macromolecule on the apatite crystal surface for targeted gene delivery, having immediate applications in basic research laboratories and great promise for gene therapy. (c) 2005 Wiley Periodicals, Inc.

Deubiquitinating enzymes in cancer stem cells: functions and targeted inhibition for cancer therapy.

PubMed

Kaushal, Kamini; Antao, Ainsley Mike; Kim, Kye-Seong; Ramakrishna, Suresh

2018-06-01

The ability of cancers to evade conventional treatments, such as chemotherapy and radiation therapy, has been attributed to a subpopulation of cancer stem cells (CSCs). CSCs are regulated by mechanisms similar to those that regulate normal stem cells (NSCs), including processes involving ubiquitination and deubiquitination enzymes (DUBs) that regulate the expression of various factors, such as Notch, Wnt, Sonic Hedgehog (Shh), and Hippo. In this review, we discuss the roles of various DUBs involved in the regulation of core stem cell transcription factors and CSC-related proteins that are implicated in the modulation of cellular processes and carcinogenesis. In addition, we discuss the various DUB inhibitors that have been designed to target processes relevant to cancer and CSC maintenance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structural basis for microRNA targeting

DOE PAGES

Schirle, Nicole T.; Sheu-Gruttadauria, Jessica; MacRae, Ian J.

2014-10-31

MicroRNAs (miRNAs) control expression of thousands of genes in plants and animals. miRNAs function by guiding Argonaute proteins to complementary sites in messenger RNAs (mRNAs) targeted for repression. In this paper, we determined crystal structures of human Argonaute-2 (Ago2) bound to a defined guide RNA with and without target RNAs representing miRNA recognition sites. These structures suggest a stepwise mechanism, in which Ago2 primarily exposes guide nucleotides (nt) 2 to 5 for initial target pairing. Pairing to nt 2 to 5 promotes conformational changes that expose nt 2 to 8 and 13 to 16 for further target recognition. Interactions withmore » the guide-target minor groove allow Ago2 to interrogate target RNAs in a sequence-independent manner, whereas an adenosine binding-pocket opposite guide nt 1 further facilitates target recognition. Spurious slicing of miRNA targets is avoided through an inhibitory coordination of one catalytic magnesium ion. Finally, these results explain the conserved nucleotide-pairing patterns in animal miRNA target sites first observed over two decades ago.« less

Enzymes involved in plastid-targeted phosphatidic acid synthesis are essential for Plasmodium yoelii liver-stage development.

PubMed

Lindner, Scott E; Sartain, Mark J; Hayes, Kiera; Harupa, Anke; Moritz, Robert L; Kappe, Stefan H I; Vaughan, Ashley M

2014-02-01

Malaria parasites scavenge nutrients from their host but also harbour enzymatic pathways for de novo macromolecule synthesis. One such pathway is apicoplast-targeted type II fatty acid synthesis, which is essential for late liver-stage development in rodent malaria. It is likely that fatty acids synthesized in the apicoplast are ultimately incorporated into membrane phospholipids necessary for exoerythrocytic merozoite formation. We hypothesized that these synthesized fatty acids are being utilized for apicoplast-targeted phosphatidic acid synthesis, the phospholipid precursor. Phosphatidic acid is typically synthesized in a three-step reaction utilizing three enzymes: glycerol 3-phosphate dehydrogenase, glycerol 3-phosphate acyltransferase and lysophosphatidic acid acyltransferase. The Plasmodium genome is predicted to harbour genes for both apicoplast- and cytosol/endoplasmic reticulum-targeted phosphatidic acid synthesis. Our research shows that apicoplast-targeted Plasmodium yoelii glycerol 3-phosphate dehydrogenase and glycerol 3-phosphate acyltransferase are expressed only during liver-stage development and deletion of the encoding genes resulted in late liver-stage growth arrest and lack of merozoite differentiation. However, the predicted apicoplast-targeted lysophosphatidic acid acyltransferase gene was refractory to deletion and was expressed solely in the endoplasmic reticulum throughout the parasite life cycle. Our results suggest that P. yoelii has an incomplete apicoplast-targeted phosphatidic acid synthesis pathway that is essential for liver-stage maturation. © 2013 John Wiley & Sons Ltd.

Modeling guidance and recognition in categorical search: Bridging human and computer object detection

PubMed Central

Zelinsky, Gregory J.; Peng, Yifan; Berg, Alexander C.; Samaras, Dimitris

2013-01-01

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery. PMID:24105460

Recognition and Binding of the PF2 Lectin to α-Amylase From Zabrotes subfasciatus (Coleoptera:Bruchidae) Larval Midgut

PubMed Central

Lagarda-Diaz, I.; Geiser, D.; Guzman-Partida, A.M.; Winzerling, J.; Vazquez-Moreno, L.

2014-01-01

Abstract Amylases are an important family of enzymes involved in insect carbohydrate metabolism that are required for the survival of insect larvae. For this reason, enzymes from starch-dependent insects are targets for insecticidal control. PF2 ( Olneya tesota ) is a lectin that is toxic to Zabrotes subfasciatus (Coleoptera: Bruchidae) larvae. In this study, we evaluated recognition of the PF2 lectin to α-amylases from Z. subfasciatus midgut and the effect of PF2 on α-amylase activity. PF2 caused a decrease of total amylase activity in vitro. Subsequently, several α-amylase isoforms were isolated from insect midgut tissues using ion exchange chromatography. Three enzyme isoforms were verified by an in-gel assay for amylase activity; however, only one isoform was recognized by antiamylase serum and PF2. The identity of this Z. subfasciatus α-amylase was confirmed by liquid chromatography−tandem mass spectrometry. The findings strongly suggest that a glycosylated α-amylase isoform from larval Z. subfasciatus midgut interacts with PF2, which interferes with starch digestion. PMID:25528751

ClpXP protease targets long-lived DNA translocation states of a helicase-like motor to cause restriction alleviation

PubMed Central

Simons, Michelle; Diffin, Fiona M.; Szczelkun, Mark D.

2014-01-01

We investigated how Escherichia coli ClpXP targets the helicase-nuclease (HsdR) subunit of the bacterial Type I restriction–modification enzyme EcoKI during restriction alleviation (RA). RA is a temporary reduction in endonuclease activity that occurs when Type I enzymes bind unmodified recognition sites on the host genome. These conditions arise upon acquisition of a new system by a naïve host, upon generation of new sites by genome rearrangement/mutation or during homologous recombination between hemimethylated DNA. Using recombinant DNA and proteins in vitro, we demonstrate that ClpXP targets EcoKI HsdR during dsDNA translocation on circular DNA but not on linear DNA. Protein roadblocks did not activate HsdR proteolysis. We suggest that DNA translocation lifetime, which is elevated on circular DNA relative to linear DNA, is important to RA. To identify the ClpX degradation tag (degron) in HsdR, we used bioinformatics and biochemical assays to design N- and C-terminal mutations that were analysed in vitro and in vivo. None of the mutants produced a phenotype consistent with loss of the degron, suggesting an as-yet-unidentified recognition pathway. We note that an EcoKI nuclease mutant still produces cell death in a clpx− strain, consistent with DNA damage induced by unregulated motor activity. PMID:25260590

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

2015-01-01

The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

The intrinsic flexibility of the aptamer targeting the ribosomal protein S8 is a key factor for the molecular recognition.

PubMed

Autiero, Ida; Ruvo, Menotti; Improta, Roberto; Vitagliano, Luigi

2018-04-01

Aptamers are RNA/DNA biomolecules representing an emerging class of protein interactors and regulators. Despite the growing interest in these molecules, current understanding of chemical-physical basis of their target recognition is limited. Recently, the characterization of the aptamer targeting the protein-S8 has suggested that flexibility plays important functional roles. We investigated the structural versatility of the S8-aptamer by molecular dynamics simulations. Five different simulations have been conducted by varying starting structures and temperatures. The simulation of S8-aptamer complex provides a dynamic view of the contacts occurring at the complex interface. The simulation of the aptamer in ligand-free state indicates that its central region is intrinsically endowed with a remarkable flexibility. Nevertheless, none of the trajectory structures adopts the structure observed in the S8-aptamer complex. The aptamer ligand-bound is very rigid in the simulation carried out at 300 K. A structural transition of this state, providing insights into the aptamer-protein recognition process, is observed in a simulation carried out at 400 K. These data indicate that a key event in the binding is linked to the widening of the central region of the aptamer. Particularly relevant is switch of the A26 base from its ligand-free state to a location that allows the G13-C28 base-pairing. Intrinsic flexibility of the aptamer is essential for partner recognition. Present data indicate that S8 recognizes the aptamer through an induced-fit rather than a population-shift mechanism. The present study provides deeper understanding of the structural basis of the structural versatility of aptamers. Copyright © 2018 Elsevier B.V. All rights reserved.

The nonverbal expression of pride: evidence for cross-cultural recognition.

PubMed

Tracy, Jessica L; Robins, Richard W

2008-03-01

The present research tests whether recognition for the nonverbal expression of pride generalizes across cultures. Study 1 provided the first evidence for cross-cultural recognition of pride, demonstrating that the expression generalizes across Italy and the United States. Study 2 found that the pride expression generalizes beyond Western cultures; individuals from a preliterate, highly isolated tribe in Burkina Faso, West Africa, reliably recognized pride, regardless of whether it was displayed by African or American targets. These Burkinabe participants were unlikely to have learned the pride expression through cross-cultural transmission, so their recognition suggests that pride may be a human universal. Studies 3 and 4 used drawn figures to systematically manipulate the ethnicity and gender of targets showing the expression, and demonstrated that pride recognition generalizes across male and female targets of African, Asian, and Caucasian descent. Discussion focuses on the implications of the findings for the universality of the pride expression.

Forward genetics screen coupled with whole-genome resequencing identifies novel gene targets for improving heterologous enzyme production in Aspergillus niger

DOE PAGES

Reilly, Morgann C.; Kim, Joonhoon; Lynn, Jed; ...

2018-01-06

Plant biomass, once reduced to its composite sugars, can be converted to fuel substitutes. One means of overcoming the recalcitrance of lignocellulose is pretreatment followed by enzymatic hydrolysis. However, currently available commercial enzyme cocktails are inhibited in the presence of residual pretreatment chemicals. Recent studies have identified a number of cellulolytic enzymes from bacteria that are tolerant to pretreatment chemicals such as ionic liquids. The challenge now is generation of these enzymes in copious amounts, an arena where fungal organisms such as Aspergillus niger have proven efficient. Fungal host strains still need to be engineered to increase production titers ofmore » heterologous protein over native enzymes, which has been a difficult task. Here, we developed a forward genetics screen coupled with whole-genome resequencing to identify specific lesions responsible for a protein hyper-production phenotype in A. niger. As a result, this strategy successfully identified novel targets, including a low-affinity glucose transporter, MstC, whose deletion significantly improved secretion of recombinant proteins driven by a glucoamylase promoter.« less

Forward genetics screen coupled with whole-genome resequencing identifies novel gene targets for improving heterologous enzyme production in Aspergillus niger

DOE PAGES

Reilly, Morgann C.; Kim, Joonhoon; Lynn, Jed; ...

2018-01-06

Plant biomass, once reduced to its composite sugars, can be converted to fuel substitutes. One means of overcoming the recalcitrance of lignocellulose is pretreatment followed by enzymatic hydrolysis. However, currently available commercial enzyme cocktails are inhibited in the presence of residual pretreatment chemicals. Recent studies have identified a number of cellulolytic enzymes from bacteria that are tolerant to pretreatment chemicals such as ionic liquids. The challenge now is generation of these enzymes in copious amounts, an arena where fungal organisms such as Aspergillus niger have proven efficient. Fungal host strains still need to be engineered to increase production titers ofmore » heterologous protein over native enzymes, which has been a difficult task. Here, we developed a forward genetics screen coupled with whole-genome resequencing to identify specific lesions responsible for a protein hyper-production phenotype in A. niger. This strategy successfully identified novel targets, including a low-affinity glucose transporter, MstC, whose deletion significantly improved secretion of recombinant proteins driven by a glucoamylase promoter.« less

Forward genetics screen coupled with whole-genome resequencing identifies novel gene targets for improving heterologous enzyme production in Aspergillus niger

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

Reilly, Morgann C.; Kim, Joonhoon; Lynn, Jed

Plant biomass, once reduced to its composite sugars, can be converted to fuel substitutes. One means of overcoming the recalcitrance of lignocellulose is pretreatment followed by enzymatic hydrolysis. However, currently available commercial enzyme cocktails are inhibited in the presence of residual pretreatment chemicals. Recent studies have identified a number of cellulolytic enzymes from bacteria that are tolerant to pretreatment chemicals such as ionic liquids. The challenge now is generation of these enzymes in copious amounts, an arena where fungal organisms such as Aspergillus niger have proven efficient. Fungal host strains still need to be engineered to increase production titers ofmore » heterologous protein over native enzymes, which has been a difficult task. Here, we developed a forward genetics screen coupled with whole-genome resequencing to identify specific lesions responsible for a protein hyper-production phenotype in A. niger. This strategy successfully identified novel targets, including a low-affinity glucose transporter, MstC, whose deletion significantly improved secretion of recombinant proteins driven by a glucoamylase promoter.« less

Forward genetics screen coupled with whole-genome resequencing identifies novel gene targets for improving heterologous enzyme production in Aspergillus niger

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

Reilly, Morgann C.; Kim, Joonhoon; Lynn, Jed

Plant biomass, once reduced to its composite sugars, can be converted to fuel substitutes. One means of overcoming the recalcitrance of lignocellulose is pretreatment followed by enzymatic hydrolysis. However, currently available commercial enzyme cocktails are inhibited in the presence of residual pretreatment chemicals. Recent studies have identified a number of cellulolytic enzymes from bacteria that are tolerant to pretreatment chemicals such as ionic liquids. The challenge now is generation of these enzymes in copious amounts, an arena where fungal organisms such as Aspergillus niger have proven efficient. Fungal host strains still need to be engineered to increase production titers ofmore » heterologous protein over native enzymes, which has been a difficult task. Here, we developed a forward genetics screen coupled with whole-genome resequencing to identify specific lesions responsible for a protein hyper-production phenotype in A. niger. As a result, this strategy successfully identified novel targets, including a low-affinity glucose transporter, MstC, whose deletion significantly improved secretion of recombinant proteins driven by a glucoamylase promoter.« less

Using eye movements as an index of implicit face recognition in autism spectrum disorder.

PubMed

Hedley, Darren; Young, Robyn; Brewer, Neil

2012-10-01

Individuals with an autism spectrum disorder (ASD) typically show impairment on face recognition tasks. Performance has usually been assessed using overt, explicit recognition tasks. Here, a complementary method involving eye tracking was used to examine implicit face recognition in participants with ASD and in an intelligence quotient-matched non-ASD control group. Differences in eye movement indices between target and foil faces were used as an indicator of implicit face recognition. Explicit face recognition was assessed using old-new discrimination and reaction time measures. Stimuli were faces of studied (target) or unfamiliar (foil) persons. Target images at test were either identical to the images presented at study or altered by changing the lighting, pose, or by masking with visual noise. Participants with ASD performed worse than controls on the explicit recognition task. Eye movement-based measures, however, indicated that implicit recognition may not be affected to the same degree as explicit recognition. Autism Res 2012, 5: 363-379. © 2012 International Society for Autism Research, Wiley Periodicals, Inc. © 2012 International Society for Autism Research, Wiley Periodicals, Inc.

Allosteric regulation of epigenetic modifying enzymes.

PubMed

Zucconi, Beth E; Cole, Philip A

2017-08-01

Epigenetic enzymes including histone modifying enzymes are key regulators of gene expression in normal and disease processes. Many drug development strategies to target histone modifying enzymes have focused on ligands that bind to enzyme active sites, but allosteric pockets offer potentially attractive opportunities for therapeutic development. Recent biochemical studies have revealed roles for small molecule and peptide ligands binding outside of the active sites in modulating the catalytic activities of histone modifying enzymes. Here we highlight several examples of allosteric regulation of epigenetic enzymes and discuss the biological significance of these findings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Leucine zipper-mediated targeting of multi-enzyme cascade reactions to inclusion bodies in Escherichia coli for enhanced production of 1-butanol.

PubMed

Han, Gui Hwan; Seong, Wonjae; Fu, Yaoyao; Yoon, Paul K; Kim, Seong Keun; Yeom, Soo-Jin; Lee, Dae-Hee; Lee, Seung-Goo

2017-03-01

Metabolons in nature have evolved to facilitate more efficient catalysis of multistep reactions through the co-localization of functionally related enzymes to cellular organelles or membrane structures. To mimic the natural metabolon architecture, we present a novel artificial metabolon that was created by targeting multi-enzyme cascade reactions onto inclusion body (IB) in Escherichia coli. The utility of this system was examined by co-localizing four heterologous enzymes of the 1-butanol pathway onto an IB that was formed in E. coli through overexpression of the cellulose binding domain (CBD) of Cellulomonas fimi exoglucanase. To target the 1-butanol pathway enzymes to the CBD IB, we utilized a peptide-peptide interaction between leucine zipper (LZ) peptides. We genetically fused the LZ peptide to the N-termini of four heterologous genes involved in the synthetic 1-butanol pathway, whereas an antiparallel LZ peptide was fused to the CBD gene. The in vivo activity of the CBD IB-based metabolon was examined through the determination of 1-butanol synthesis using E. coli transformed with two plasmids containing the LZ-fused CBD and LZ-fused 1-butanol pathway genes, respectively. In vivo synthesis of 1-butanol using the engineered E. coli yielded 1.98g/L of 1-butanol from glucose, representing a 1.5-fold increase over that obtained from E. coli expressing the LZ-fused 1-butanol pathway genes alone. In an attempt to examine the in vitro 1-butanol productivity, we reconstituted CBD IB-based metabolon using CBD IB and individual enzymes of 1-butanol pathway. The 1-butanol productivity of in vitro reconstituted CBD IB-based metabolon using acetoacetyl-CoA as the starting material was 2.29mg/L/h, 7.9-fold higher than that obtained from metabolon-free enzymes of 1-butanol pathway. Therefore, this novel CBD-based artificial metabolon may prove useful in metabolic engineering both in vivo and in vitro for the efficient production of desired products. Copyright © 2017

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

Insight towards the conserved water mediated recognition of catalytic and structural Zn(+2) ions in human Matrix Metalloproteinase-8 enzyme: A study by MD-simulation methods.

PubMed

Chakrabarti, Bornali; Bairagya, Hridoy R; Mishra, Deepak Kr; Chatterjee, Pradip Kumar; Mukhopadhyay, Bishnu P

2013-01-01

Human matrix metalloproteinase-8 (hMMP-8) plays a important role in the progression of colorectal cancer, metastasis, multiple sclerosis and rheumetoid arthritis. Extensive MD-simulation of the PDB and solvated structures of hMMP-8 has revealed the presence of few conserved water molecules around the catalytic and structural zinc (ZnC and ZnS) ions. The coordination of two conserved water molecules (W and WS) to ZnS and the H-bonding interaction of WS to S151 have indicated the plausible involvement of that metal ion in the catalytic process. Beside this the coupling of ZnC and ZnS metal ions (ZnC - W(H) (W(1))…..W(2) ….H(162) - ZnS) through two conserved hydrophilic centers (occupied by water molecules) may also provide some rational on the recognition of two zinc ions which were separated by ~13 Å in their X-ray structures. This unique recognition of both the Zn(+2) ions in the enzyme through conserved water molecules may be implemented/ exploited for the design of antiproteolytic agent using water mimic drug design protocol.

Fluorescent carbon dot-gated multifunctional mesoporous silica nanocarriers for redox/enzyme dual-responsive targeted and controlled drug delivery and real-time bioimaging.

PubMed

Wang, Ying; Cui, Yu; Zhao, Yating; He, Bing; Shi, Xiaoli; Di, Donghua; Zhang, Qiang; Wang, Siling

2017-08-01

A distinctive and personalized nanocarrier is described here for controlled and targeted antitumor drug delivery and real-time bioimaging by combining a redox/enzyme dual-responsive disulfide-conjugated carbon dot with mesoporous silica nanoparticles (MSN-SS-CD HA ). The carbon dot with controlling and targeting abilities was prepared through a polymerizing reaction by applying citric acid and HA as starting materials (named CD HA ). The as-prepared MSN-SS-CD HA exhibited not only superior photostability and excellent biocompatibility, but also the ability to target A549 cells with overexpression of CD44 receptors. Upon loading the antitumor drug, doxorubicin (DOX), into the mesoporous channels of MSN nanoparticles, CD HA with a diameter size of 3nm completely blocked the pore entrance of DOX-encapsulated MSN nanoparticles with a pore size of about 3nm, thus preventing the premature leakage of DOX and increasing the antitumor activity until being triggered by specific stimuli in the tumor environment. The results of the cell imaging and cytotoxicity studies demonstrated that the redox/enzyme dual-responsive DOX-encapsulated MSN-SS-CD HA nanoparticles can selectively deliver and control the release of DOX into tumor cells. Ex vivo fluorescence images showed a much stronger fluorescence of MSN-SS-CD HA -DOX in the tumor site than in normal tissues, greatly facilitating the accumulation of DOX in the target tissue. However, its counterpart, MSN-SH-DOX exhibited no or much lower tumor cytotoxicity and drug accumulation in tumor tissue. In addition, MSN-SS-CD was also used as a control to investigate the ability of MSN-SS-CD HA to target A549 cells. The results obtained indicated that MSN-SS-CD HA possessed a higher cellular uptake through the CD44 receptor-mediated endocytosis compared with MSN-SS-CD in the A549 cells. Such specific redox/enzyme dual-responsive targeted nanocarriers are a useful strategy achieving selective controlled and targeted delivery of

The CreB deubiquitinating enzyme does not directly target the CreA repressor protein in Aspergillus nidulans.

PubMed

Alam, Md Ashiqul; Kamlangdee, Niyom; Kelly, Joan M

2017-08-01

Ubiquitination/deubiquitination pathways are now recognized as key components of gene regulatory mechanisms in eukaryotes. The major transcriptional repressor for carbon catabolite repression in Aspergillus nidulans is CreA, and mutational analysis led to the suggestion that a regulatory ubiquitination/deubiquitination pathway is involved. A key unanswered question is if and how this pathway, comprising CreB (deubiquitinating enzyme) and HulA (ubiquitin ligase) and other proteins, is involved in the regulatory mechanism. Previously, missense alleles of creA and creB were analysed for genetic interactions, and here we extended this to complete loss-of-function alleles of creA and creB, and compared morphological and biochemical phenotypes, which confirmed genetic interaction between the genes. We investigated whether CreA, or a protein in a complex with it, is a direct target of the CreB deubiquitination enzyme, using co-purifications of CreA and CreB, first using strains that overexpress the proteins and then using strains that express the proteins from their native promoters. The Phos-tag system was used to show that CreA is a phosphorylated protein, but no ubiquitination was detected using anti-ubiquitin antibodies and Western analysis. These findings were confirmed using mass spectrometry, which confirmed that CreA was differentially phosphorylated but not ubiquitinated. Thus, CreA is not a direct target of CreB, and nor are proteins that form part of a stable complex with CreA a target of CreB. These results open up new questions regarding the molecular mechanism of CreA repressing activity, and how the ubiquitination pathway involving CreB interacts with this regulatory network.

Indoleamine 2,3-dioxygenase-dependent neurotoxic kynurenine metabolism mediates inflammation-induced deficit in recognition memory

PubMed Central

Heisler, Jillian M.; O’Connor, Jason C.

2015-01-01

Cognitive dysfunction in depression is a prevalent and debilitating symptom that is poorly treated by the currently available pharmacotherapies. Research over the past decade has provided evidence for proinflammatory involvement in the neurobiology of depressive disorders and symptoms associated with these disorders, including aspects of memory dysfunction. Recent clinical studies implicate inflammation-related changes in kynurenine metabolism as a potential pathogenic factor in the development of a range of depressive symptoms, including deficits in cognition and memory. Additionally, preclinical work has demonstrated a number of mood-related depressive-like behaviors to be dependent on indoleamine 2,3-dioxygenase-1 (IDO1), the inflammation-induced rate-limiting enzyme of the kynurenine pathway. Here, we demonstrate in a mouse model, that peripheral administration of endotoxin induced a deficit in recognition memory. Mice deficient in IDO were protected from cognitive impairment. Furthermore, endotoxin-induced inflammation increased kynurenine metabolism within the perirhinal/entorhinal cortices, brain regions which have been implicated in recognition memory. A single peripheral injection of kynurenine, the metabolic product of IDO1, was sufficient to induce a deficit in recognition memory in both control and IDO null mice. Finally, kynurenine monooxygenase (KMO) deficient mice were also protected from inflammation-induced deficits on novel object recognition. These data implicate IDO-dependent neurotoxic kynurenine metabolism as a pathogenic factor for cognitive dysfunction in inflammation-induced depressive disorders and a potential novel target for the treatment of these disorders. PMID:26130057

Dose response of bone-targeted enzyme replacement for murine hypophosphatasia.

PubMed

Yadav, Manisha C; Lemire, Isabelle; Leonard, Pierre; Boileau, Guy; Blond, Laurent; Beliveau, Martin; Cory, Esther; Sah, Robert L; Whyte, Michael P; Crine, Philippe; Millán, José Luis

2011-08-01

Hypophosphatasia (HPP) features rickets or osteomalacia from tissue-nonspecific alkaline phosphatase (TNSALP) deficiency due to deactivating mutations within the ALPL gene. Enzyme replacement therapy with a bone-targeted, recombinant TNSALP (sALP-FcD(10), renamed ENB-0040) prevents manifestations of HPP when initiated at birth in TNSALP knockout (Akp2(-/-)) mice. Here, we evaluated the dose-response relationship of ENB-0040 to various phenotypic traits of Akp2(-/-) mice receiving daily subcutaneous (SC) injections of ENB-0040 from birth at 0.5, 2.0, or 8.2mg/kg for 43days. Radiographs, μCT, and histomorphometric analyses documented better bone mineralization with increasing doses of ENB-0040. We found a clear, positive correlation between ENB-0040 dose and prevention of mineralization defects of the feet, rib cage, lower limbs, and jaw bones. According to a dose-response model, the ED(80) (the dose that prevents bone defects in 80% of mice) was 3.2, 2.8 and 2.9mg/kg/day for these sites, respectively. Long bones seemed to respond to lower daily doses of ENB-0040. There was also a positive relationship between ENB-0040 dose and survival. Median survival, body weight, and bone length all improved with increasing doses of ENB-0040. Urinary PP(i) concentrations remained elevated in all treatment groups, indicating that while this parameter is a good biochemical marker for diagnosing HPP in patients, it may not be a good follow up marker for evaluating response to treatment when administering bone-targeted TNSALP to mice. These dose-response relationships strongly support the pharmacological efficacy of ENB-0040 for HPP, and provide the experimental basis for the therapeutic range of ENB-0040 chosen for clinical trials. Copyright © 2011 Elsevier Inc. All rights reserved.

Dose response of bone-targeted enzyme replacement for murine hypophosphatasia

PubMed Central

Yadav, Manisha C.; Lemire, Isabelle; Leonard, Pierre; Boileau, Guy; Blond, Laurent; Beliveau, Martin; Cory, Esther; Sah, Robert L.; Whyte, Michael P.; Crine, Philippe; Millán, José Luis

2011-01-01

Hypophosphatasia (HPP) features rickets or osteomalacia from tissue-nonspecific alkaline phosphatase (TNSALP) deficiency due to deactivating mutations within the ALPL gene. Enzyme replacement therapy with a bone-targeted, recombinant TNSALP (sALP-FcD10, renamed ENB-0040) prevents manifestations of HPP when initiated at birth in TNSALP knockout (Akp2−/−) mice. Here, we evaluated the dose-response relationship of ENB-0040 to various phenotypic traits of Akp2−/− mice receiving daily subcutaneous (SC) injections of ENB-0040 from birth at 0.5, 2.0, or 8.2 mg/kg for 43 days. Radiographs, μCT, and histomorphometric analyses documented better bone mineralization with increasing doses of ENB-0040. We found a clear, positive correlation between ENB-0040 dose and prevention of mineralization defects of the feet, rib cage, lower limbs, and jaw bones. According to a dose-response model, the ED80 (the dose prevents the bone defects in 80% of mice) was 3.2, 2.8 and 2.9 mg/kg/day for these sites, respectively. Long bones seemed to respond to lower daily doses of ENB-0040. There was also a positive relationship between ENB-0040 dose and survival. Median survival, body weight, and bone length all improved with increasing doses of ENB-0040. Urinary PPi concentrations remained elevated in all treatment groups, indicating that while this parameter is a good biochemical marker for diagnosing HPP, it may not be a good follow up marker for evaluating response to treatment when administering bone-targeted TNSALP. These dose-response relationships strongly support the pharmacological efficacy of ENB-0040 for HPP, and provide the experimental basis for the therapeutic range of ENB-0040 chosen for clinical trials. PMID:21458605

A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework.

PubMed

Wei, Shengjing; Chen, Xiang; Yang, Xidong; Cao, Shuai; Zhang, Xu

2016-04-19

Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL) sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set) suggested by two reference subjects, (82.6 ± 13.2)% and (79.7 ± 13.4)% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7)% and (86.3 ± 13.7)% when the training set included 50~60 gestures (about half of the target gesture set). The proposed framework can significantly reduce the user's training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.

Automatic integration of social information in emotion recognition.

PubMed

Mumenthaler, Christian; Sander, David

2015-04-01

This study investigated the automaticity of the influence of social inference on emotion recognition. Participants were asked to recognize dynamic facial expressions of emotion (fear or anger in Experiment 1 and blends of fear and surprise or of anger and disgust in Experiment 2) in a target face presented at the center of a screen while a subliminal contextual face appearing in the periphery expressed an emotion (fear or anger) or not (neutral) and either looked at the target face or not. Results of Experiment 1 revealed that recognition of the target emotion of fear was improved when a subliminal angry contextual face gazed toward-rather than away from-the fearful face. We replicated this effect in Experiment 2, in which facial expression blends of fear and surprise were more often and more rapidly categorized as expressing fear when the subliminal contextual face expressed anger and gazed toward-rather than away from-the target face. With the contextual face appearing for 30 ms in total, including only 10 ms of emotion expression, and being immediately masked, our data provide the first evidence that social influence on emotion recognition can occur automatically. (c) 2015 APA, all rights reserved).

Protospacer Adjacent Motif (PAM)-Distal Sequences Engage CRISPR Cas9 DNA Target Cleavage

PubMed Central

Ethier, Sylvain; Schmeing, T. Martin; Dostie, Josée; Pelletier, Jerry

2014-01-01

The clustered regularly interspaced short palindromic repeat (CRISPR)-associated enzyme Cas9 is an RNA-guided nuclease that has been widely adapted for genome editing in eukaryotic cells. However, the in vivo target specificity of Cas9 is poorly understood and most studies rely on in silico predictions to define the potential off-target editing spectrum. Using chromatin immunoprecipitation followed by sequencing (ChIP-seq), we delineate the genome-wide binding panorama of catalytically inactive Cas9 directed by two different single guide (sg) RNAs targeting the Trp53 locus. Cas9:sgRNA complexes are able to load onto multiple sites with short seed regions adjacent to 5′NGG3′ protospacer adjacent motifs (PAM). Yet among 43 ChIP-seq sites harboring seed regions analyzed for mutational status, we find editing only at the intended on-target locus and one off-target site. In vitro analysis of target site recognition revealed that interactions between the 5′ end of the guide and PAM-distal target sequences are necessary to efficiently engage Cas9 nucleolytic activity, providing an explanation for why off-target editing is significantly lower than expected from ChIP-seq data. PMID:25275497

Epigenetics of prostate cancer and the prospect of identification of novel drug targets by RNAi screening of epigenetic enzymes.

PubMed

Björkman, Mari; Rantala, Juha; Nees, Matthias; Kallioniemi, Olli

2010-10-01

Alterations in epigenetic processes probably underlie most human malignancies. Novel genome-wide techniques, such as chromatin immunoprecipitation and high-throughput sequencing, have become state-of-the-art methods to map the epigenomic landscape of development and disease, such as in cancers. Despite these advances, the functional significance of epigenetic enzymes in cancer progression, such as prostate cancer, remain incompletely understood. A comprehensive mapping and functional understanding of the cancer epigenome will hopefully help to facilitate development of novel cancer therapy targets and improve future diagnostics. The authors have developed a novel cell microarray-based high-content siRNA screening technique suitable to address the putative functional role and impact of all known putative and novel epigenetic enzymes in cancer, including prostate cancer.

Laser range profiling for small target recognition

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Tulldahl, Michael

2017-03-01

Long range identification (ID) or ID at closer range of small targets has its limitations in imaging due to the demand for very high-transverse sensor resolution. This is, therefore, a motivation to look for one-dimensional laser techniques for target ID. These include laser vibrometry and laser range profiling. Laser vibrometry can give good results, but is not always robust as it is sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angularly resolved. Our laser range profiler is based on a laser with a pulse width of 6 ns (full width half maximum). This paper will show both experimental and simulated results for laser range profiling of small boats out to a 6 to 7-km range and a unmanned arrial vehicle (UAV) mockup at close range (1.3 km). The naval experiments took place in the Baltic Sea using many other active and passive electro-optical sensors in addition to the profiling system. The UAV experiments showed the need for a high-range resolution, thus we used a photon counting system in addition to the more conventional profiler used in the naval experiments. This paper shows the influence of target pose and range resolution on the capability of classification. The typical resolution (in our case 0.7 m) obtainable with a conventional range finder type of sensor can be used for large target classification with a depth structure over 5 to 10 m or more, but for smaller targets such as a UAV a high resolution (in our case 7.5 mm) is needed to reveal depth structures and surface shapes. This paper also shows the need for 3-D target information to build libraries for comparison of measured and simulated range profiles. At closer ranges

Recognition Imaging of Acetylated Chromatin Using a DNA Aptamer

PubMed Central

Lin, Liyun; Fu, Qiang; Williams, Berea A.R.; Azzaz, Abdelhamid M.; Shogren-Knaak, Michael A.; Chaput, John C.; Lindsay, Stuart

2009-01-01

Histone acetylation plays an important role in the regulation of gene expression. A DNA aptamer generated by in vitro selection to be highly specific for histone H4 protein acetylated at lysine 16 was used as a recognition element for atomic force microscopy-based recognition imaging of synthetic nucleosomal arrays with precisely controlled acetylation. The aptamer proved to be reasonably specific at recognizing acetylated histones, with recognition efficiencies of 60% on-target and 12% off-target. Though this selectivity is much poorer than the >2000:1 equilibrium specificity of the aptamer, it is a large improvement on the performance of a ChIP-quality antibody, which is not selective at all in this application, and it should permit high-fidelity recognition with repeated imaging. The ability to image the precise location of posttranslational modifications may permit nanometer-scale investigation of their effect on chromatin structure. PMID:19751687

Glucose enhancement of a facial recognition task in young adults.

PubMed

Metzger, M M

2000-02-01

Numerous studies have reported that glucose administration enhances memory processes in both elderly and young adult subjects. Although these studies have utilized a variety of procedures and paradigms, investigations of both young and elderly subjects have typically used verbal tasks (word list recall, paragraph recall, etc.). In the present study, the effect of glucose consumption on a nonverbal, facial recognition task in young adults was examined. Lemonade sweetened with either glucose (50 g) or saccharin (23.7 mg) was consumed by college students (mean age of 21.1 years) 15 min prior to a facial recognition task. The task consisted of a familiarization phase in which subjects were presented with "target" faces, followed immediately by a recognition phase in which subjects had to identify the targets among a random array of familiar target and novel "distractor" faces. Statistical analysis indicated that there were no differences on hit rate (target identification) for subjects who consumed either saccharin or glucose prior to the test. However, further analyses revealed that subjects who consumed glucose committed significantly fewer false alarms and had (marginally) higher d-prime scores (a signal detection measure) compared to subjects who consumed saccharin prior to the test. These results parallel a previous report demonstrating glucose enhancement of a facial recognition task in probable Alzheimer's patients; however, this is believed to be the first demonstration of glucose enhancement for a facial recognition task in healthy, young adults.

Drug repositioning for enzyme modulator based on human metabolite-likeness.

PubMed

Lee, Yoon Hyeok; Choi, Hojae; Park, Seongyong; Lee, Boah; Yi, Gwan-Su

2017-05-31

Recently, the metabolite-likeness of the drug space has emerged and has opened a new possibility for exploring human metabolite-like candidates in drug discovery. However, the applicability of metabolite-likeness in drug discovery has been largely unexplored. Moreover, there are no reports on its applications for the repositioning of drugs to possible enzyme modulators, although enzyme-drug relations could be directly inferred from the similarity relationships between enzyme's metabolites and drugs. We constructed a drug-metabolite structural similarity matrix, which contains 1,861 FDA-approved drugs and 1,110 human intermediary metabolites scored with the Tanimoto similarity. To verify the metabolite-likeness measure for drug repositioning, we analyzed 17 known antimetabolite drugs that resemble the innate metabolites of their eleven target enzymes as the gold standard positives. Highly scored drugs were selected as possible modulators of enzymes for their corresponding metabolites. Then, we assessed the performance of metabolite-likeness with a receiver operating characteristic analysis and compared it with other drug-target prediction methods. We set the similarity threshold for drug repositioning candidates of new enzyme modulators based on maximization of the Youden's index. We also carried out literature surveys for supporting the drug repositioning results based on the metabolite-likeness. In this paper, we applied metabolite-likeness to repurpose FDA-approved drugs to disease-associated enzyme modulators that resemble human innate metabolites. All antimetabolite drugs were mapped with their known 11 target enzymes with statistically significant similarity values to the corresponding metabolites. The comparison with other drug-target prediction methods showed the higher performance of metabolite-likeness for predicting enzyme modulators. After that, the drugs scored higher than similarity score of 0.654 were selected as possible modulators of enzymes for

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

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

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

Transfer Learning for Activity Recognition: A Survey

PubMed Central

Cook, Diane; Feuz, Kyle D.; Krishnan, Narayanan C.

2013-01-01

Many intelligent systems that focus on the needs of a human require information about the activities being performed by the human. At the core of this capability is activity recognition, which is a challenging and well-researched problem. Activity recognition algorithms require substantial amounts of labeled training data yet need to perform well under very diverse circumstances. As a result, researchers have been designing methods to identify and utilize subtle connections between activity recognition datasets, or to perform transfer-based activity recognition. In this paper we survey the literature to highlight recent advances in transfer learning for activity recognition. We characterize existing approaches to transfer-based activity recognition by sensor modality, by differences between source and target environments, by data availability, and by type of information that is transferred. Finally, we present some grand challenges for the community to consider as this field is further developed. PMID:24039326

Cascaded automatic target recognition (Cascaded ATR)

NASA Astrophysics Data System (ADS)

Walls, Bradley

2010-04-01

The global war on terror has plunged US and coalition forces into a battle space requiring the continuous adaptation of tactics and technologies to cope with an elusive enemy. As a result, technologies that enhance the intelligence, surveillance, and reconnaissance (ISR) mission making the warfighter more effective are experiencing increased interest. In this paper we show how a new generation of smart cameras built around foveated sensing makes possible a powerful ISR technique termed Cascaded ATR. Foveated sensing is an innovative optical concept in which a single aperture captures two distinct fields of view. In Cascaded ATR, foveated sensing is used to provide a coarse resolution, persistent surveillance, wide field of view (WFOV) detector to accomplish detection level perception. At the same time, within the foveated sensor, these detection locations are passed as a cue to a steerable, high fidelity, narrow field of view (NFOV) detector to perform recognition level perception. Two new ISR mission scenarios, utilizing Cascaded ATR, are proposed.

Enzyme-Responsive Liposomes for the Delivery of Anticancer Drugs

PubMed Central

Fouladi, Farnaz; Steffen, Kristine J.; Mallik, Sanku

2017-01-01

Liposomes are nanocarriers that deliver the payloads at the target site, leading to therapeutic drug concentrations at the diseased site and reduced toxic effects in healthy tissues. Several approaches have been used to enhance the ability of the nanocarrier to target the specific tissues, including ligand-targeted liposomes and stimuli-responsive liposomes. Ligand-targeted liposomes exhibit higher uptake by the target tissue due to the targeting ligand attached to the surface, while, the stimuli-responsive liposomes do not release their cargo unless they expose to an endogenous or exogenous stimulant at the target site. In this review, we mainly focus on the liposomes that are responsive to pathologically increased levels of enzymes at the target site. Enzyme-responsive liposomes release their cargo upon contact with the enzyme through several destabilization mechanisms: a) structural perturbation in the lipid bilayer, b) removal of a shielding polymer from the surface and increased cellular uptake, c) cleavage of a lipopeptide or lipopolymer incorporated in the bilayer, and d) activation of a prodrug in the liposomes. PMID:28201868

Enzyme-Responsive Liposomes for the Delivery of Anticancer Drugs.

PubMed

Fouladi, Farnaz; Steffen, Kristine J; Mallik, Sanku

2017-04-19

Liposomes are nanocarriers that deliver the payloads at the target site, leading to therapeutic drug concentrations at the diseased site and reduced toxic effects in healthy tissues. Several approaches have been used to enhance the ability of the nanocarrier to target the specific tissues, including ligand-targeted liposomes and stimuli-responsive liposomes. Ligand-targeted liposomes exhibit higher uptake by the target tissue due to the targeting ligand attached to the surface, while the stimuli-responsive liposomes do not release their cargo unless they expose to an endogenous or exogenous stimulant at the target site. In this review, we mainly focus on the liposomes that are responsive to pathologically increased levels of enzymes at the target site. Enzyme-responsive liposomes release their cargo upon contact with the enzyme through several destabilization mechanisms: (1) structural perturbation in the lipid bilayer, (2) removal of a shielding polymer from the surface and increased cellular uptake, (3) cleavage of a lipopeptide or lipopolymer incorporated in the bilayer, and (4) activation of a prodrug in the liposomes.

Chalcone-based small-molecule inhibitors attenuate malignant phenotype via targeting deubiquitinating enzymes

PubMed Central

Issaenko, Olga A.; Amerik, Alexander Yu

2012-01-01

The ubiquitin-proteasome system (UPS) is usurped by many if not all cancers to regulate their survival, proliferation, invasion, angiogenesis and metastasis. Bioflavonoids curcumin and chalcones exhibit anti-neoplastic selectivity through inhibition of the 26S proteasome-activity within the UPS. Here, we provide evidence for a novel mechanism of action of chalcone-based derivatives AM146, RA-9 and RA-14, which exert anticancer activity by targeting deubiquitinating enzymes (DUB) without affecting 20S proteasome catalytic-core activity. The presence of the α,β-unsaturated carbonyl group susceptible to nucleophilic attack from the sulfhydryl of cysteines in the active sites of DUB determines the capacity of novel small-molecules to act as cell-permeable, partly selective DUB inhibitors and induce rapid accumulation of polyubiquitinated proteins and deplete the pool of free ubiquitin. These chalcone-derivatives directly suppress activity of DUB UCH-L1, UCH-L3, USP2, USP5 and USP8, which are known to regulate the turnover and stability of key regulators of cell survival and proliferation. Inhibition of DUB-activity mediated by these compounds downregulates cell-cycle promoters, e.g., cyclin D1 and upregulates tumor suppressors p53, p27Kip1 and p16Ink4A. These changes are associated with arrest in S-G2/M, abrogated anchorage-dependent growth and onset of apoptosis in breast, ovarian and cervical cancer cells without noticeable alterations in primary human cells. Altogether, this work provides evidence of antitumor activity of novel chalcone-based derivatives mediated by their DUB-targeting capacity; supports the development of pharmaceuticals to directly target DUB as a most efficient strategy compared with proteasome inhibition and also provides a clear rationale for the clinical evaluation of these novel small-molecule DUB inhibitors. PMID:22510564

Using Metadynamics to Understand the Mechanism of Calmodulin/Target Recognition at Atomic Detail

PubMed Central

Fiorin, G.; Pastore, A.; Carloni, P.; Parrinello, M.

2006-01-01

The ability of calcium-bound calmodulin (CaM) to recognize most of its target peptides is caused by its binding to two hydrophobic residues (‘anchors’). In most of the CaM complexes, the anchors pack against the hydrophobic pockets of the CaM domains and are surrounded by fully conserved Met side chains. Here, by using metadynamics simulations, we investigate quantitatively the energetics of the final step of this process using the M13 peptide, which has a high affinity and spans the sequence of the skeletal myosin light chain kinase, an important natural CaM target. We established the accuracy of our calculations by a comparison between calculated and NMR-derived structural and dynamical properties. Our calculations provide novel insights into the mechanism of protein/peptide recognition: we show that the process is associated with a free energy gain similar to that experimentally measured for the CaM complex with the homologous smooth muscle MLCK peptide (Ehrhardt et al., 1995, Biochemistry 34, 2731). We suggest that binding is dominated by the entropic effect, in agreement with previous proposals. Furthermore, we explain the role of conserved methionines by showing that the large flexibility of these side chains is a key feature of the binding mechanism. Finally, we provide a rationale for the experimental observation that in all CaM complexes the C-terminal domain seems to be hierarchically more important in establishing the interaction. PMID:16877506

New restriction enzymes discovered from Escherichia coli clinical strains using a plasmid transformation method

PubMed Central

Kasarjian, Julie K. A.; Iida, Masatake; Ryu, Junichi

2003-01-01

The presence of restriction enzymes in bacterial cells has been predicted by either classical phage restriction-modification (R-M) tests, direct in vitro enzyme assays or more recently from bacterial genome sequence analysis. We have applied phage R-M test principles to the transformation of plasmid DNA and established a plasmid R-M test. To validate this test, six plasmids that contain BamHI fragments of phage lambda DNA were constructed and transformed into Escherichia coli strains containing known R-M systems including: type I (EcoBI, EcoAI, Eco124I), type II (HindIII) and type III (EcoP1I). Plasmid DNA with a single recognition site showed a reduction of relative efficiency of transformation (EOT = 10–1–10–2). When multiple recognition sites were present, greater reductions in EOT values were observed. Once established in the cell, the plasmids were subjected to modification (EOT = 1.0). We applied this test to screen E.coli clinical strains and detected the presence of restriction enzymes in 93% (14/15) of cells. Using additional subclones and the computer program, RM Search, we identified four new restriction enzymes, Eco377I, Eco585I, Eco646I and Eco777I, along with their recognition sequences, GGA(8N)ATGC, GCC(6N)TGCG, CCA(7N)CTTC, and GGA(6N)TATC, respectively. Eco1158I, an isoschizomer of EcoBI, was also found in this study. PMID:12595571

Virulence-Associated Enzymes of Cryptococcus neoformans

PubMed Central

Almeida, Fausto; Wolf, Julie M.

2015-01-01

Enzymes play key roles in fungal pathogenesis. Manipulation of enzyme expression or activity can significantly alter the infection process, and enzyme expression profiles can be a hallmark of disease. Hence, enzymes are worthy targets for better understanding pathogenesis and identifying new options for combatting fungal infections. Advances in genomics, proteomics, transcriptomics, and mass spectrometry have enabled the identification and characterization of new fungal enzymes. This review focuses on recent developments in the virulence-associated enzymes from Cryptococcus neoformans. The enzymatic suite of C. neoformans has evolved for environmental survival, but several of these enzymes play a dual role in colonizing the mammalian host. We also discuss new therapeutic and diagnostic strategies that could be based on the underlying enzymology. PMID:26453651

Continued effects of context reinstatement in recognition.

PubMed

Hanczakowski, Maciej; Zawadzka, Katarzyna; Macken, Bill

2015-07-01

The context reinstatement effect refers to the enhanced memory performance found when the context information paired with a target item at study is re-presented at test. Here we investigated the consequences of the way that context information is processed in such a setting that gives rise to its beneficial effect on item recognition memory. Specifically, we assessed whether reinstating context in a recognition test facilitates subsequent memory for this context, beyond the facilitation conferred by presentation of the same context with a different study item. Reinstating the study context at test led to better accuracy in two-alternative forced choice recognition for target faces than did re-pairing those faces with another context encountered during the study phase. The advantage for reinstated over re-paired conditions occurred for both within-subjects (Exp. 1) and between-subjects (Exp. 2) manipulations. Critically, in a subsequent recognition test for the contexts themselves, contexts that had previously served in the reinstated condition were recognized better than contexts that had previously served in the re-paired context condition. This constitutes the first demonstration of continuous effects of context reinstatement on memory for context.

PHYSICAL MODEL FOR RECOGNITION TUNNELING

PubMed Central

Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart

2015-01-01

Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) We show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals. PMID:25650375

An Exquisitely Specific PDZ/Target Recognition Revealed by the Structure of INAD PDZ3 in Complex with TRP Channel Tail.

PubMed

Ye, Fei; Liu, Wei; Shang, Yuan; Zhang, Mingjie

2016-03-01

The vast majority of PDZ domains are known to bind to a few C-terminal tail residues of target proteins with modest binding affinities and specificities. Such promiscuous PDZ/target interactions are not compatible with highly specific physiological functions of PDZ domain proteins and their targets. Here, we report an unexpected PDZ/target binding occurring between the scaffold protein inactivation no afterpotential D (INAD) and transient receptor potential (TRP) channel in Drosophila photoreceptors. The C-terminal 15 residues of TRP are required for the specific interaction with INAD PDZ3. The INAD PDZ3/TRP peptide complex structure reveals that only the extreme C-terminal Leu of TRP binds to the canonical αB/βB groove of INAD PDZ3. The rest of the TRP peptide, by forming a β hairpin structure, binds to a surface away from the αB/βB groove of PDZ3 and contributes to the majority of the binding energy. Thus, the INAD PDZ3/TRP channel interaction is exquisitely specific and represents a new mode of PDZ/target recognitions. Copyright © 2016 Elsevier Ltd. All rights reserved.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

In vivo, cardiac-specific knockdown of target protein, Malic Enzyme-1, in rat via adenoviral delivery of DNA for non-native miRNA

PubMed Central

O'Donnell, J. Michael; Kalichira, Asha; Bi, Jian; Lewandowski, E. Douglas

2013-01-01

This study examines the feasibility of using the adenoviral delivery of DNA for a non-native microRNA to suppress expression of a target protein (cytosolic NADP+-dependent malic-enzyme 1, ME1) in whole heart in vivo, via an isolated-heart coronary perfusion approach. Complementary DNA constructs for ME1 microRNA were inserted into adenoviral vectors. Viral gene transfer to neonatal rat cardiomyocytes yielded 65% suppression of ME1 protein. This viral package was delivered to rat hearts in vivo (Adv.miR_ME1, 1013 vp/ml PBS) via coronary perfusion, using a cardiac-specific isolation technique. ME1 mRNA was reduced by 73% at 2-6 days post-surgery in heart receiving the Adv.miR_ME1. Importantly, ME1 protein was reduced by 66% (p<0.0002) at 5-6 days relative to sham-operated control hearts. Non-target protein expression for GAPDH, calsequestrin, and mitochondrial malic enzyme, ME3, were all unchanged. The non-target isoform, ME2, was unchanged at 2-5 days and reduced at day 6. This new approach demonstrates for the first time significant and acute silencing of target RNA translation and protein content in whole heart, in vivo, via non-native microRNA expression. PMID:22974418

Recognition and binding of the PF2 lectin to α-amylase from Zabrotes subfasciatus (Coleoptera:Bruchidae) larval midgut.

PubMed

Lagarda-Diaz, I; Geiser, D; Guzman-Partida, A M; Winzerling, J; Vazquez-Moreno, L

2014-01-01

Amylases are an important family of enzymes involved in insect carbohydrate metabolism that are required for the survival of insect larvae. For this reason, enzymes from starch-dependent insects are targets for insecticidal control. PF2 (Olneya tesota) is a lectin that is toxic to Zabrotes subfasciatus (Coleoptera: Bruchidae) larvae. In this study, we evaluated recognition of the PF2 lectin to α-amylases from Z. subfasciatus midgut and the effect of PF2 on α-amylase activity. PF2 caused a decrease of total amylase activity in vitro. Subsequently, several α-amylase isoforms were isolated from insect midgut tissues using ion exchange chromatography. Three enzyme isoforms were verified by an in-gel assay for amylase activity; however, only one isoform was recognized by antiamylase serum and PF2. The identity of this Z. subfasciatus α-amylase was confirmed by liquid chromatography-tandem mass spectrometry. The findings strongly suggest that a glycosylated α-amylase isoform from larval Z. subfasciatus midgut interacts with PF2, which interferes with starch digestion. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

Inhibitors of steroidal cytochrome p450 enzymes as targets for drug development.

PubMed

Baston, Eckhard; Leroux, Frédéric R

2007-01-01

Cytochrome P450's are enzymes which catalyze a large number of biological reactions, for example hydroxylation, N-, O-, S- dealkylation, epoxidation or desamination. Their substrates include fatty acids, steroids or prostaglandins. In addition, a high number of various xenobiotics are metabolized by these enzymes. The enzyme 17alpha-hydroxylase-C17,20-lyase (P450(17), CYP 17, androgen synthase), a cytochrome P450 monooxygenase, is the key enzyme for androgen biosynthesis. It catalyzes the last step of the androgen biosynthesis in the testes and adrenal glands and produces androstenedione and dehydroepiandrosterone from progesterone and pregnenolone. The microsomal enzyme aromatase (CYP19) transforms these androgens to estrone and estradiol. Estrogens stimulate tumor growth in hormone dependent breast cancer. In addition, about 80 percent of prostate cancers are androgen dependent. Selective inhibitors of these enzymes are thus important alternatives to treatment options like antiandrogens or antiestrogens. The present article deals with recent patents (focus on publications from 2000 - 2006) concerning P450 inhibitor design where steroidal substrates are involved. In this context a special focus is provided for CYP17 and CYP19. Mechanisms of action will also be discussed. Inhibitors of CYP11B2 (aldosterone synthase) will also be dealt with.

Learning target masks in infrared linescan imagery

NASA Astrophysics Data System (ADS)

Fechner, Thomas; Rockinger, Oliver; Vogler, Axel; Knappe, Peter

1997-04-01

In this paper we propose a neural network based method for the automatic detection of ground targets in airborne infrared linescan imagery. Instead of using a dedicated feature extraction stage followed by a classification procedure, we propose the following three step scheme: In the first step of the recognition process, the input image is decomposed into its pyramid representation, thus obtaining a multiresolution signal representation. At the lowest three levels of the Laplacian pyramid a neural network filter of moderate size is trained to indicate the target location. The last step consists of a fusion process of the several neural network filters to obtain the final result. To perform this fusion we use a belief network to combine the various filter outputs in a statistical meaningful way. In addition, the belief network allows the integration of further knowledge about the image domain. By applying this multiresolution recognition scheme, we obtain a nearly scale- and rotational invariant target recognition with a significantly decreased false alarm rate compared with a single resolution target recognition scheme.

Object recognition of ladar with support vector machine

NASA Astrophysics Data System (ADS)

Sun, Jian-Feng; Li, Qi; Wang, Qi

2005-01-01

Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

PubMed

Holdstock, J S; Mayes, A R; Roberts, N; Cezayirli, E; Isaac, C L; O'Reilly, R C; Norman, K A

2002-01-01

The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can

Dissociation from DNA of Type III Restriction–Modification enzymes during helicase-dependent motion and following endonuclease activity

PubMed Central

Tóth, Júlia; van Aelst, Kara; Salmons, Hannah; Szczelkun, Mark D.

2012-01-01

DNA cleavage by the Type III Restriction–Modification (RM) enzymes requires the binding of a pair of RM enzymes at two distant, inversely orientated recognition sequences followed by helicase-catalysed ATP hydrolysis and long-range communication. Here we addressed the dissociation from DNA of these enzymes at two stages: during long-range communication and following DNA cleavage. First, we demonstrated that a communicating species can be trapped in a DNA domain without a recognition site, with a non-specific DNA association lifetime of ∼200 s. If free DNA ends were present the lifetime became too short to measure, confirming that ends accelerate dissociation. Secondly, we observed that Type III RM enzymes can dissociate upon DNA cleavage and go on to cleave further DNA molecules (they can ‘turnover’, albeit inefficiently). The relationship between the observed cleavage rate and enzyme concentration indicated independent binding of each site and a requirement for simultaneous interaction of at least two enzymes per DNA to achieve cleavage. In light of various mechanisms for helicase-driven motion on DNA, we suggest these results are most consistent with a thermally driven random 1D search model (i.e. ‘DNA sliding’). PMID:22523084

Brain catechol-o-methyltransferase (COMT) inhibition by tolcapone counteracts recognition memory deficits in normal and chronic phencyclidine-treated rats and in COMT-Val transgenic mice

PubMed Central

Detrait, E.R.; Carr, G.V.; Ferraille, S.; Weinberger, D.R.; Lamberty, Y.

2015-01-01

The critical involvement of dopamine in cognitive processes has been well established, suggesting therapies targeting dopamine metabolism may alleviate cognitive dysfunction. COMT is a catecholamine-degrading enzyme, the substrates of which include dopamine, epinephrine, and norepinephrine. The present work illustrates the potential therapeutic efficacy of COMT inhibition for alleviating cognitive impairment. A brain penetrant COMT inhibitor, tolcapone, was tested in normal and phencyclidine (PCP)-treated rats and COMT–Val transgenic mice. In a Novel Object Recognition (NOR) procedure, tolcapone counteracted a 24h-dependent forgetting of a familiar object and counteracted PCP-induced recognition deficits in the rats at doses ranging from 7.5 to 30 mg/kg. In contrast, entacapone, a COMT inhibitor which does not readily cross the blood-brain barrier failed to show efficacy at doses up to 30mg/kg. Tolcapone at a dose of 30 mg/kg also improved NOR performance in the transgenic mice, which showed clear recognition deficits. Complementing earlier studies, our results indicate that central inhibition of COMT positively impacts recognition memory processes and might constitute an appealing treatment for cognitive dysfunction related to neuropsychiatric disorders. PMID:26919286

[Representation of letter position in visual word recognition process].

PubMed

Makioka, S

1994-08-01

Two experiments investigated the representation of letter position in visual word recognition process. In Experiment 1, subjects (12 undergraduates and graduates) were asked to detect a target word in a briefly-presented probe. Probes consisted of two kanji words. The latters which formed targets (critical letters) were always contained in probes. (e.g. target: [symbol: see text] probe: [symbol: see text]) High false alarm rate was observed when critical letters occupied the same within-word relative position (left or right within the word) in the probe words as in the target word. In Experiment 2 (subject were ten undergraduates and graduates), spaces adjacent to probe words were replaced by randomly chosen hiragana letters (e.g. [symbol: see text]), because spaces are not used to separate words in regular Japanese sentences. In addition to the effect of within-word relative position as in Experiment 1, the effect of between-word relative position (left or right across the probe words) was observed. These results suggest that information about within-word relative position of a letter is used in word recognition process. The effect of within-word relative position was explained by a connectionist model of word recognition.

Variability in the impairment of recognition memory in patients with frontal lobe lesions.

PubMed

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-10-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased false recognitions for synonyms only. Differences in terms of location of the damage and behavioral characteristics between these subgroups were examined. An encoding deficit was proposed to explain the performance of patients in subgroup I. The behavioral patterns of the patients in subgroups II and III could be interpreted as deficient post-retrieval verification processes and an inability to recollect item-specific information, respectively.

Alteration of gene expression by restriction enzymes electroporated into plant cells.

PubMed

Ashraf, M; Altschuler, M; Galasinski, S; Griffiths, T D

1993-06-01

The alteration in the expression of a beta-glucuronidase (GUS) reporter gene was used to monitor the effect of restriction endonucleases electroporated into the tobacco (Nicotiana tabacum L.) protoplasts. Restriction enzyme (RE) Hind III which does not have a recognition site within the gene cassette, had little effect on enzyme activity. In contrast restriction endonucleases Hae III and Sau3A1 which possess 8 and 16 recognition sites in the GUS cassette, were found to reduce the enzyme activity by 89% and 94% respectively when compared to control electroporations. Restriction-site mutation analysis (RSM) and Southern blot analysis indicated the enzymatic degradation of GUS coding sequence by the REs Hae III and Sau3A1. Results of this study suggest that on electroporation, REs can enter into plant cells and alter the expression of the GUS gene. The alteration of gene expression is thus correlated with the digestion of GUS template DNA. Future applications of this technique could include addressing fundamental questions with regard to DNA repair, site-specific recombination, identifying mutations, insertional mutagenesis, enhancement of stable transformation and gene tagging in plants.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

NASA Astrophysics Data System (ADS)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Face recognition increases during saccade preparation.

PubMed

Lin, Hai; Rizak, Joshua D; Ma, Yuan-ye; Yang, Shang-chuan; Chen, Lin; Hu, Xin-tian

2014-01-01

Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

The utility of multiple synthesized views in the recognition of unfamiliar faces.

PubMed

Jones, Scott P; Dwyer, Dominic M; Lewis, Michael B

2017-05-01

The ability to recognize an unfamiliar individual on the basis of prior exposure to a photograph is notoriously poor and prone to errors, but recognition accuracy is improved when multiple photographs are available. In applied situations, when only limited real images are available (e.g., from a mugshot or CCTV image), the generation of new images might provide a technological prosthesis for otherwise fallible human recognition. We report two experiments examining the effects of providing computer-generated additional views of a target face. In Experiment 1, provision of computer-generated views supported better target face recognition than exposure to the target image alone and equivalent performance to that for exposure of multiple photograph views. Experiment 2 replicated the advantage of providing generated views, but also indicated an advantage for multiple viewings of the single target photograph. These results strengthen the claim that identifying a target face can be improved by providing multiple synthesized views based on a single target image. In addition, our results suggest that the degree of advantage provided by synthesized views may be affected by the quality of synthesized material.

Recognition of Nucleoside Monophosphate Substrates by Haemophilus influenzae Class C Acid Phosphatase

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

Singh, Harkewal; Schuermann, Jonathan P.; Reilly, Thomas J.

2010-12-08

The e (P4) phosphatase from Haemophilus influenzae functions in a vestigial NAD{sup +} utilization pathway by dephosphorylating nicotinamide mononucleotide to nicotinamide riboside. P4 is also the prototype of class C acid phosphatases (CCAPs), which are nonspecific 5{prime},3{prime}-nucleotidases localized to the bacterial outer membrane. To understand substrate recognition by P4 and other class C phosphatases, we have determined the crystal structures of a substrate-trapping mutant P4 enzyme complexed with nicotinamide mononucleotide, 5{prime}-AMP, 3{prime}-AMP, and 2{prime}-AMP. The structures reveal an anchor-shaped substrate-binding cavity comprising a conserved hydrophobic box that clamps the nucleotide base, a buried phosphoryl binding site, and three solvent-filled pocketsmore » that contact the ribose and the hydrogen-bonding edge of the base. The span between the hydrophobic box and the phosphoryl site is optimal for recognizing nucleoside monophosphates, explaining the general preference for this class of substrate. The base makes no hydrogen bonds with the enzyme, consistent with an observed lack of base specificity. Two solvent-filled pockets flanking the ribose are key to the dual recognition of 5{prime}-nucleotides and 3{prime}-nucleotides. These pockets minimize the enzyme's direct interactions with the ribose and provide sufficient space to accommodate 5{prime} substrates in an anti conformation and 3{prime} substrates in a syn conformation. Finally, the structures suggest that class B acid phosphatases and CCAPs share a common strategy for nucleotide recognition.« less

Improved and targeted delivery of bioactive molecules to cells with magnetic layer-by-layer assembled microcapsules

NASA Astrophysics Data System (ADS)

Pavlov, Anton M.; Gabriel, Samantha A.; Sukhorukov, Gleb B.; Gould, David J.

2015-05-01

Despite our increasing knowledge of cell biology and the recognition of an increasing repertoire of druggable intracellular therapeutic targets, there remain a limited number of approaches to deliver bioactive molecules to cells and even fewer that enable targeted delivery. Layer-by-layer (LbL) microcapsules are assembled using alternate layers of oppositely charged molecules and are potential cell delivery vehicles for applications in nanomedicine. There are a wide variety of charged molecules that can be included in the microcapsule structure including metal nanoparticles that introduce physical attributes. Delivery of bioactive molecules to cells with LbL microcapsules has recently been demonstrated, so in this study we explore the delivery of bioactive molecules (luciferase enzyme and plasmid DNA) to cells using biodegradable microcapsules containing a layer of magnetite nanoparticles. Interestingly, significantly improved intracellular luciferase enzyme activity (25 fold) and increased transfection efficiency with plasmid DNA (3.4 fold) was observed with magnetic microcapsules. The use of a neodymium magnet enabled efficient targeting of magnetic microcapsules which further improved the delivery efficiency of the cargoes as a consequence of increased microcapsule concentration at the magnetic site. Microcapsules were well tolerated by cells in these experiments and only displayed signs of toxicity at a capsule : cell ratio of 100 : 1 and with extended exposure. These studies illustrate how multi-functionalization of LbL microcapsules can improve and target delivery of bioactive molecules to cells.

Research on autonomous identification of airport targets based on Gabor filtering and Radon transform

NASA Astrophysics Data System (ADS)

Yi, Juan; Du, Qingyu; Zhang, Hong jiang; Zhang, Yao lei

2017-11-01

Target recognition is a leading key technology in intelligent image processing and application development at present, with the enhancement of computer processing ability, autonomous target recognition algorithm, gradually improve intelligence, and showed good adaptability. Taking the airport target as the research object, analysis the airport layout characteristics, construction of knowledge model, Gabor filter and Radon transform based on the target recognition algorithm of independent design, image processing and feature extraction of the airport, the algorithm was verified, and achieved better recognition results.

Infrared vehicle recognition using unsupervised feature learning based on K-feature

NASA Astrophysics Data System (ADS)

Lin, Jin; Tan, Yihua; Xia, Haijiao; Tian, Jinwen

2018-02-01

Subject to the complex battlefield environment, it is difficult to establish a complete knowledge base in practical application of vehicle recognition algorithms. The infrared vehicle recognition is always difficult and challenging, which plays an important role in remote sensing. In this paper we propose a new unsupervised feature learning method based on K-feature to recognize vehicle in infrared images. First, we use the target detection algorithm which is based on the saliency to detect the initial image. Then, the unsupervised feature learning based on K-feature, which is generated by Kmeans clustering algorithm that extracted features by learning a visual dictionary from a large number of samples without label, is calculated to suppress the false alarm and improve the accuracy. Finally, the vehicle target recognition image is finished by some post-processing. Large numbers of experiments demonstrate that the proposed method has satisfy recognition effectiveness and robustness for vehicle recognition in infrared images under complex backgrounds, and it also improve the reliability of it.

Biochemical characterization of the bifunctional enzyme dihydrofolate reductase-thymidylate synthase from Leishmania (Viannia) and its evaluation as a drug target.

PubMed

Osorio, Edison; Aguilera, Carolina; Naranjo, Nelson; Marín, Marcel; Muskus, Carlos

2013-01-01

Dihydrofolate reductase (DHFR) has been used successfully as a drug target in the area of anti-bacterial, anti-cancer and anti-malarial therapy. Although this bifunctional enzyme is also a potential drug target for treatment of leishmaniasis, there have been no reports on its efficacy against Leishmania (Viannia) species. The gene encoding the bifunctional DHFR and thymidylate synthase (TS) of Le. (V.) braziliensis was isolated and expressed in E. coli. The enzyme was purified and characterized. The inhibitory effects of antifolates and four aporphine alkaloids on its activity were evaluated. The full-length gene consists of a 1560-bp open reading frame encoding a 58 kDa translated peptide containing DHFR and TS domains linked together in a single polypeptide chain. The recombinant DHFR-TS enzyme revealed Km and Vmax values of 55.35 ± 4.02 µ M (mean ± SE) and 0.02 ± 5.34 x 10 -4 µ M/min respectively for dihydrofolic acid (H₂F). The Le. braziliensis rDHFR-TS have Ki values for antimicrobial antifolates in the µM range. Methotrexate (MTX) was a more-potent inhibitor of enzymatic activity (Ki = 22.0 µM) than trimethoprim (Ki = 33 µM) and pyrimethamine (Ki = 68 µM). These Ki values are significantly lower than those obtained for the aporphine alkaloids. The results of the study show the inhibitory effect of antifolate drugs on enzymatic activity, indicating that Le. braziliensis rDHFR-TS could be a model to studying antifolate compounds as potential antiprotozoal drugs.

Expression, function and regulation of mouse cytochrome P450 enzymes: comparison with human P450 enzymes.

PubMed

Hrycay, E G; Bandiera, S M

2009-12-01

The present review focuses on the expression, function and regulation of mouse cytochrome P450 (Cyp) enzymes. Information compiled for mouse Cyp enzymes is compared with data collected for human CYP enzymes. To date, approximately 40 pairs of orthologous mouse-human CYP genes have been identified that encode enzymes performing similar metabolic functions. Recent knowledge concerning the tissue expression of mouse Cyp enzymes from families 1 to 51 is summarized. The catalytic activities of microsomal, mitochondrial and recombinant mouse Cyp enzymes are discussed and their involvement in the metabolism of exogenous and endogenous compounds is highlighted. The role of nuclear receptors, such as the aryl hydrocarbon receptor, constitutive androstane receptor and pregnane X receptor, in regulating the expression of mouse Cyp enzymes is examined. Targeted disruption of selected Cyp genes has generated numerous Cyp null mouse lines used to decipher the role of Cyp enzymes in metabolic, toxicological and biological processes. In conclusion, the laboratory mouse is an indispensable model for exploring human CYP-mediated activities.

Membrane Transporters: Structure, Function and Targets for Drug Design

NASA Astrophysics Data System (ADS)

Ravna, Aina W.; Sager, Georg; Dahl, Svein G.; Sylte, Ingebrigt

Current therapeutic drugs act on four main types of molecular targets: enzymes, receptors, ion channels and transporters, among which a major part (60-70%) are membrane proteins. This review discusses the molecular structures and potential impact of membrane transporter proteins on new drug discovery. The three-dimensional (3D) molecular structure of a protein contains information about the active site and possible ligand binding, and about evolutionary relationships within the protein family. Transporters have a recognition site for a particular substrate, which may be used as a target for drugs inhibiting the transporter or acting as a false substrate. Three groups of transporters have particular interest as drug targets: the major facilitator superfamily, which includes almost 4000 different proteins transporting sugars, polyols, drugs, neurotransmitters, metabolites, amino acids, peptides, organic and inorganic anions and many other substrates; the ATP-binding cassette superfamily, which plays an important role in multidrug resistance in cancer chemotherapy; and the neurotransmitter:sodium symporter family, which includes the molecular targets for some of the most widely used psychotropic drugs. Recent technical advances have increased the number of known 3D structures of membrane transporters, and demonstrated that they form a divergent group of proteins with large conformational flexibility which facilitates transport of the substrate.

Recognition of isotropic plane target from RCS diagram

NASA Astrophysics Data System (ADS)

Saillard, J.; Chassay, G.

1981-06-01

The use of electromagnetic waves for the recognition of a structure represented by point scatterers is seen as posing a fundamental problem. It is noted that much research has been done on this subject and that the study of aircraft observed in the yaw plane gives interesting results. To apply these methods, however, it is necessary to use many sophisticated acquisition systems. A method is proposed which can be applied to plane structures composed of isotropic scatterers. The method is considered to be of interest because it uses only power measurements and requires only a classical tracking radar.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

NASA Astrophysics Data System (ADS)

Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

2017-01-01

A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution.

PubMed

Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

2017-01-06

A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

PubMed Central

Girault, Mathias; Kim, Hyonchol; Arakawa, Hisayuki; Matsuura, Kenji; Odaka, Masao; Hattori, Akihiro; Terazono, Hideyuki; Yasuda, Kenji

2017-01-01

A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining. PMID:28059147

Preferential Targeting of a Signal Recognition Particle-dependent Precursor to the Ssh1p Translocon in Yeast♦

PubMed Central

Spiller, Michael P.; Stirling, Colin J.

2011-01-01

Protein translocation across the endoplasmic reticulum membrane occurs via a “translocon” channel formed by the Sec61p complex. In yeast, two channels exist: the canonical Sec61p channel and a homolog called Ssh1p. Here, we used trapped translocation intermediates to demonstrate that a specific signal recognition particle-dependent substrate, Sec71p, is targeted exclusively to Ssh1p. Strikingly, we found that, in the absence of Ssh1p, precursor could be successfully redirected to canonical Sec61p, demonstrating that the normal targeting reaction must involve preferential sorting to Ssh1p. Our data therefore demonstrate that Ssh1p is the primary translocon for Sec71p and reveal a novel sorting mechanism at the level of the endoplasmic reticulum membrane enabling precursors to be directed to distinct translocons. Interestingly, the Ssh1p-dependent translocation of Sec71p was found to be dependent upon Sec63p, demonstrating a previously unappreciated functional interaction between Sec63p and the Ssh1p translocon. PMID:21454595

Mitochondrial targeting of the human peptide methionine sulfoxide reductase (MSRA), an enzyme involved in the repair of oxidized proteins.

PubMed

Hansel, Alfred; Kuschel, Lioba; Hehl, Solveig; Lemke, Cornelius; Agricola, Hans-Jürgen; Hoshi, Toshinori; Heinemann, Stefan H

2002-06-01

Peptide methionine sulfoxide reductase (MSRA) catalyzes the reduction of methionine sulfoxide to methionine. This widely expressed enzyme constitutes an important repair mechanism for oxidatively damaged proteins, which accumulate during the manifestation of certain degenerative diseases and aging processes. In addition, it is discussed to be involved in regulatory processes. Here we address the question of how the enzyme's diverse functions are reflected in its subcellular localization. Using fusions of the human version of MSRA with the enhanced green fluorescence protein expressed in various mammalian cell lines, we show a distinct localization at mitochondria. The N-terminal 23 amino acid residues contain the signal for this mitochondrial targeting. Activity tests showed that they are not required for enzyme function. Mitochondrial localization of native MSRA in mouse and rat liver slices was verified with an MSRA-specific antibody by using immunohistochemical methods. The protein was located in the mitochondrial matrix, as demonstrated by using pre-embedding immunostaining and electron microscopy. Mitochondria are the major source of reactive oxygen species (ROS). Therefore, MSRA has to be considered an important means for the general reduction of ROS release from mitochondria.

Modularly assembled designer TAL effector nucleases for targeted gene knockout and gene replacement in eukaryotes

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

Li, T; Huang, S; Zhao, XF

Recent studies indicate that the DNA recognition domain of transcription activator-like (TAL) effectors can be combined with the nuclease domain of FokI restriction enzyme to produce TAL effector nucleases (TALENs) that, in pairs, bind adjacent DNA target sites and produce double-strand breaks between the target sequences, stimulating non-homologous end-joining and homologous recombination. Here, we exploit the four prevalent TAL repeats and their DNA recognition cipher to develop a 'modular assembly' method for rapid production of designer TALENs (dTALENs) that recognize unique DNA sequence up to 23 bases in any gene. We have used this approach to engineer 10 dTALENs tomore » target specific loci in native yeast chromosomal genes. All dTALENs produced high rates of site-specific gene disruptions and created strains with expected mutant phenotypes. Moreover, dTALENs stimulated high rates (up to 34%) of gene replacement by homologous recombination. Finally, dTALENs caused no detectable cytotoxicity and minimal levels of undesired genetic mutations in the treated yeast strains. These studies expand the realm of verified TALEN activity from cultured human cells to an intact eukaryotic organism and suggest that low-cost, highly dependable dTALENs can assume a significant role for gene modifications of value in human and animal health, agriculture and industry.« less

Kinetic recognition of the retinoblastoma tumor suppressor by a specific protein target.

PubMed

Chemes, Lucía B; Sánchez, Ignacio E; de Prat-Gay, Gonzalo

2011-09-16

The retinoblastoma tumor suppressor (Rb) plays a key role in cell cycle control and is linked to various types of human cancer. Rb binds to the LxCxE motif, present in a number of cellular and viral proteins such as AdE1A, SV40 large T-antigen and human papillomavirus (HPV) E7, all instrumental in revealing fundamental mechanisms of tumor suppression, cell cycle control and gene expression. A detailed kinetic study of RbAB binding to the HPV E7 oncoprotein shows that an LxCxE-containing E7 fragment binds through a fast two-state reaction strongly favored by electrostatic interactions. Conversely, full-length E7 binds through a multistep process involving a pre-equilibrium between E7 conformers, a fast electrostatically driven association step guided by the LxCxE motif and a slow conformational rearrangement. This kinetic complexity arises from the conformational plasticity and intrinsically disordered nature of E7 and from multiple interaction surfaces present in both proteins. Affinity differences between E7N domains from high- and low-risk types are explained by their dissociation rates. In fact, since Rb is at the center of a large protein interaction network, fast and tight recognition provides an advantage for disruption by the viral proteins, where the balance of physiological and pathological interactions is dictated by kinetic ligand competition. The localization of the LxCxE motif within an intrinsically disordered domain provides the fast, diffusion-controlled interaction that allows viral proteins to outcompete physiological targets. We describe the interaction mechanism of Rb with a protein ligand, at the same time an LxCxE-containing model target, and a paradigmatic intrinsically disordered viral oncoprotein. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Comparison of Two Flashcard Drill Methods Targeting Word Recognition

ERIC Educational Resources Information Center

Volpe, Robert J.; Mule, Christina M.; Briesch, Amy M.; Joseph, Laurice M.; Burns, Matthew K.

2011-01-01

Traditional drill and practice (TD) and incremental rehearsal (IR) are two flashcard drill instructional methods previously noted to improve word recognition. The current study sought to compare the effectiveness and efficiency of these two methods, as assessed by next day retention assessments, under 2 conditions (i.e., opportunities to respond…

DGAT enzymes and triacylglycerol biosynthesis

PubMed Central

Yen, Chi-Liang Eric; Stone, Scot J.; Koliwad, Suneil; Harris, Charles; Farese, Robert V.

2008-01-01

Triacylglycerols (triglycerides) (TGs) are the major storage molecules of metabolic energy and FAs in most living organisms. Excessive accumulation of TGs, however, is associated with human diseases, such as obesity, diabetes mellitus, and steatohepatitis. The final and the only committed step in the biosynthesis of TGs is catalyzed by acyl-CoA:diacylglycerol acyltransferase (DGAT) enzymes. The genes encoding two DGAT enzymes, DGAT1 and DGAT2, were identified in the past decade, and the use of molecular tools, including mice deficient in either enzyme, has shed light on their functions. Although DGAT enzymes are involved in TG synthesis, they have distinct protein sequences and differ in their biochemical, cellular, and physiological functions. Both enzymes may be useful as therapeutic targets for diseases. Here we review the current knowledge of DGAT enzymes, focusing on new advances since the cloning of their genes, including possible roles in human health and diseases. PMID:18757836

Interaction between chitosan and its related enzymes: A review.

PubMed

Shinya, Shoko; Fukamizo, Tamo

2017-11-01

Chitosan-related enzymes including chitosanases, exo-β-glucosaminidases, and enzymes having chitosan-binding modules recognize ligands through electrostatic interactions between the acidic amino acids in proteins and amino groups of chitosan polysaccharides. However, in GH8 chitosanases, several aromatic residues are also involved in substrate recognition through stacking interactions, and these enzymes consequently hydrolyze β-1,4-glucan as well as chitosan. The binding grooves of these chitosanases are extended and opened at both ends of the grooves, so that the enzymes can clamp a long chitosan polysaccharide. The association/dissociation of positively charged glucosamine residues to/from the binding pocket of a GH2 exo-β-glucosaminidase controls the p K a of the catalytic acid, thereby maintaining the high catalytic potency of the enzyme. In contrast to chitosanases, chitosan-binding modules only accommodate a couple of glucosamine residues, predominantly recognizing the non-reducing end glucosamine residue of chitosan by electrostatic interactions and a hydrogen-bonding network. These structural findings on chitosan-related enzymes may contribute to future applications for the efficient conversion of the chitin/chitosan biomass. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular recognition and regulation of human angiotensin-I converting enzyme (ACE) activity by natural inhibitory peptides

PubMed Central

Masuyer, Geoffrey; Schwager, Sylva L. U.; Sturrock, Edward D.; Isaac, R. Elwyn; Acharya, K. Ravi

2012-01-01

Angiotensin-I converting enzyme (ACE), a two-domain dipeptidylcarboxypeptidase, is a key regulator of blood pressure as a result of its critical role in the renin-angiotensin-aldosterone and kallikrein-kinin systems. Hence it is an important drug target in the treatment of cardiovascular diseases. ACE is primarily known for its ability to cleave angiotensin I (Ang I) to the vasoactive octapeptide angiotensin II (Ang II), but is also able to cleave a number of other substrates including the vasodilator bradykinin and N-acetyl-Ser-Asp-Lys-Pro (Ac-SDKP), a physiological modulator of hematopoiesis. For the first time we provide a detailed biochemical and structural basis for the domain selectivity of the natural peptide inhibitors of ACE, bradykinin potentiating peptide b and Ang II. Moreover, Ang II showed selective competitive inhibition of the carboxy-terminal domain of human somatic ACE providing evidence for a regulatory role in the human renin-angiotensin system (RAS). PMID:23056909

Individual differences in forced-choice recognition memory: Partitioning contributions of recollection and familiarity

PubMed Central

Migo, Ellen M.; Quamme, Joel R.; Holmes, Selina; Bendell, Andrew; Norman, Kenneth A.; Mayes, Andrew R.; Montaldi, Daniela

2014-01-01

In forced-choice recognition memory, two different testing formats are possible under conditions of high target-foil similarity: each target can be presented alongside foils similar to itself (forced-choice corresponding; FCC), or alongside foils similar to other targets (forced-choice non-corresponding; FCNC).Recent behavioural and neuropsychological studies suggest that FCC performance can be supported by familiarity whereas FCNC performance is supported primarily by recollection. In this paper, we corroborate this finding from an individual differences perspective. A group of older adults were given a test of FCC and FCNC recognition for object pictures, as well as standardised tests of recall, recognition and IQ. Recall measures were found to predict FCNC, but not FCC performance, consistent with a critical role for recollection in FCNC only. After the common influence of recall was removed, standardised tests of recognition predicted FCC, but not FCNC performance. This is consistent with a contribution of only familiarity in FCC. Simulations show that a two process model, where familiarity and recollection make separate contributions to recognition, is ten times more likely to give these results than a single-process model. This evidence highlights the importance of recognition memory test design when examining the involvement of recollection and familiarity. PMID:24796268

Individual differences in forced-choice recognition memory: partitioning contributions of recollection and familiarity.

PubMed

Migo, Ellen M; Quamme, Joel R; Holmes, Selina; Bendell, Andrew; Norman, Kenneth A; Mayes, Andrew R; Montaldi, Daniela

2014-01-01

In forced-choice recognition memory, two different testing formats are possible under conditions of high target-foil similarity: Each target can be presented alongside foils similar to itself (forced-choice corresponding; FCC), or alongside foils similar to other targets (forced-choice noncorresponding; FCNC). Recent behavioural and neuropsychological studies suggest that FCC performance can be supported by familiarity whereas FCNC performance is supported primarily by recollection. In this paper, we corroborate this finding from an individual differences perspective. A group of older adults were given a test of FCC and FCNC recognition for object pictures, as well as standardized tests of recall, recognition, and IQ. Recall measures were found to predict FCNC, but not FCC performance, consistent with a critical role for recollection in FCNC only. After the common influence of recall was removed, standardized tests of recognition predicted FCC, but not FCNC performance. This is consistent with a contribution of only familiarity in FCC. Simulations show that a two-process model, where familiarity and recollection make separate contributions to recognition, is 10 times more likely to give these results than a single-process model. This evidence highlights the importance of recognition memory test design when examining the involvement of recollection and familiarity.

Lexical Competition in Non-Native Spoken-Word Recognition

ERIC Educational Resources Information Center

Weber, Andrea; Cutler, Anne

2004-01-01

Four eye-tracking experiments examined lexical competition in non-native spoken-word recognition. Dutch listeners hearing English fixated longer on distractor pictures with names containing vowels that Dutch listeners are likely to confuse with vowels in a target picture name ("pencil," given target "panda") than on less confusable distractors…

Recent trends and perspectives in enzyme based biosensor development for the screening of triglycerides: a comprehensive review.

PubMed

Hooda, Vinita; Gahlaut, Anjum; Gothwal, Ashish; Hooda, Vikas

2018-04-27

Clinical manifestations of the elevated plasma triacylglycerol (TG) include a greater prevalence of atherosclerotic heart disease, acute pancreatitis, diabetes mellitus, hypertension, and ischemic vascular disease. Hence, these significant health troubles have attracted scientific attention for the precise detection of TG in biological samples. Numerous techniques have been employed to quantify TG over many decades, but biosensors hold the leading position owing to their superior traits such as highly specific recognition for target molecules, accuracy, minituarization, small sample requirement and rapid response. Enzyme-based electrochemical biosensors represent an instantaneous resolution for the foremost bottlenecks constraining laboratory prototypes to reach real time bedside applications. We highlight the choice of transducers and constructive strategies to design high-performance biosensor for the quantification of triglycerides in sera and early diagnosis of health problems related to it. In the present review, a small effort has been made to emphasize the significant role of enzymes, nanostructured metal oxides, graphene, conducting polypyrrole, nanoparticles, porous silicon, EISCAP and ENFET in enabling TG biosensors more proficient and taking a revolutionary step forward.

Artificial neural networks for acoustic target recognition

NASA Astrophysics Data System (ADS)

Robertson, James A.; Mossing, John C.; Weber, Bruce A.

1995-04-01

Acoustic sensors can be used to detect, track and identify non-line-of-sight targets passively. Attempts to alter acoustic emissions often result in an undesirable performance degradation. This research project investigates the use of neural networks for differentiating between features extracted from the acoustic signatures of sources. Acoustic data were filtered and digitized using a commercially available analog-digital convertor. The digital data was transformed to the frequency domain for additional processing using the FFT. Narrowband peak detection algorithms were incorporated to select peaks above a user defined SNR. These peaks were then used to generate a set of robust features which relate specifically to target components in varying background conditions. The features were then used as input into a backpropagation neural network. A K-means unsupervised clustering algorithm was used to determine the natural clustering of the observations. Comparisons between a feature set consisting of the normalized amplitudes of the first 250 frequency bins of the power spectrum and a set of 11 harmonically related features were made. Initial results indicate that even though some different target types had a tendency to group in the same clusters, the neural network was able to differentiate the targets. Successful identification of acoustic sources under varying operational conditions with high confidence levels was achieved.

Coupling between Catalytic Loop Motions and Enzyme Global Dynamics

PubMed Central

Kurkcuoglu, Zeynep; Bakan, Ahmet; Kocaman, Duygu; Bahar, Ivet; Doruker, Pemra

2012-01-01

Catalytic loop motions facilitate substrate recognition and binding in many enzymes. While these motions appear to be highly flexible, their functional significance suggests that structure-encoded preferences may play a role in selecting particular mechanisms of motions. We performed an extensive study on a set of enzymes to assess whether the collective/global dynamics, as predicted by elastic network models (ENMs), facilitates or even defines the local motions undergone by functional loops. Our dataset includes a total of 117 crystal structures for ten enzymes of different sizes and oligomerization states. Each enzyme contains a specific functional/catalytic loop (10–21 residues long) that closes over the active site during catalysis. Principal component analysis (PCA) of the available crystal structures (including apo and ligand-bound forms) for each enzyme revealed the dominant conformational changes taking place in these loops upon substrate binding. These experimentally observed loop reconfigurations are shown to be predominantly driven by energetically favored modes of motion intrinsically accessible to the enzyme in the absence of its substrate. The analysis suggests that robust global modes cooperatively defined by the overall enzyme architecture also entail local components that assist in suitable opening/closure of the catalytic loop over the active site. PMID:23028297

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

PubMed Central

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L.; Rufo, Elena

2013-01-01

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. PMID:23609804

Computational burden resulting from image recognition of high resolution radar sensors.

PubMed

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L; Rufo, Elena

2013-04-22

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

ZnO-Based Amperometric Enzyme Biosensors

PubMed Central

Zhao, Zhiwei; Lei, Wei; Zhang, Xiaobing; Wang, Baoping; Jiang, Helong

2010-01-01

Nanostructured ZnO with its unique properties could provide a suitable microenvironment for immobilization of enzymes while retaining their biological activity, and thus lead to an expanded use of this nanomaterial for the construction of electrochemical biosensors with enhanced analytical performance. ZnO-based enzyme electrochemical biosensors are summarized in several tables for an easy overview according to the target biosensing analyte (glucose, hydrogen peroxide, phenol and cholesterol), respectively. Moreover, recent developments in enzyme electrochemical biosensors based on ZnO nanomaterials are reviewed with an emphasis on the fabrications and features of ZnO, approaches for biosensor construction (e.g., modified electrodes and enzyme immobilization) and biosensor performances. PMID:22205864

Mapping DNA cleavage by the Type ISP restriction-modification enzymes following long-range communication between DNA sites in different orientations

PubMed Central

van Aelst, Kara; Saikrishnan, Kayarat; Szczelkun, Mark D.

2015-01-01

The prokaryotic Type ISP restriction-modification enzymes are single-chain proteins comprising an Mrr-family nuclease, a superfamily 2 helicase-like ATPase, a coupler domain, a methyltransferase, and a DNA-recognition domain. Upon recognising an unmodified DNA target site, the helicase-like domain hydrolyzes ATP to cause site release (remodeling activity) and to then drive downstream translocation consuming 1–2 ATP per base pair (motor activity). On an invading foreign DNA, double-strand breaks are introduced at random wherever two translocating enzymes form a so-called collision complex following long-range communication between a pair of target sites in inverted (head-to-head) repeat. Paradoxically, structural models for collision suggest that the nuclease domains are too far apart (>30 bp) to dimerise and produce a double-strand DNA break using just two strand-cleavage events. Here, we examined the organisation of different collision complexes and how these lead to nuclease activation. We mapped DNA cleavage when a translocating enzyme collides with a static enzyme bound to its site. By following communication between sites in both head-to-head and head-to-tail orientations, we could show that motor activity leads to activation of the nuclease domains via distant interactions of the helicase or MTase-TRD. Direct nuclease dimerization is not required. To help explain the observed cleavage patterns, we also used exonuclease footprinting to demonstrate that individual Type ISP domains can swing off the DNA. This study lends further support to a model where DNA breaks are generated by multiple random nicks due to mobility of a collision complex with an overall DNA-binding footprint of ∼30 bp. PMID:26507855

Cellulose and hemicellulose-degrading enzymes in Fusarium commune transcriptome and functional characterization of three identified xylanases.

PubMed

Huang, Yuhong; Busk, Peter Kamp; Lange, Lene

2015-06-01

Specific enzymes from plant-pathogenic microbes demonstrate high effectiveness for natural lignocellulosic biomass degradation and utilization. The secreted lignocellulolytic enzymes of Fusarium species have not been investigated comprehensively, however. In this study we compared cellulose and hemicellulose-degrading enzymes of classical fungal enzyme producers with those of Fusarium species. The results indicated that Fusarium species are robust cellulose and hemicellulose degraders. Wheat bran, carboxymethylcellulose and xylan-based growth media induced a broad spectrum of lignocellulolytic enzymes in Fusarium commune. Prediction of the cellulose and hemicellulose-degrading enzymes in the F. commune transcriptome using peptide pattern recognition revealed 147 genes encoding glycoside hydrolases and six genes encoding lytic polysaccharide monooxygenases (AA9 and AA11), including all relevant cellulose decomposing enzymes (GH3, GH5, GH6, GH7, GH9, GH45 and AA9), and abundant hemicellulases. We further applied peptide pattern recognition to reveal nine and seven subfamilies of GH10 and GH11 family enzymes, respectively. The uncharacterized XYL10A, XYL10B and XYL11 enzymes of F. commune were classified, respectively, into GH10 subfamily 1, subfamily 3 and GH11 subfamily 1. These xylanases were successfully expressed in the PichiaPink™ system with the following properties: the purified recombinant XYL10A had interesting high specific activity; XYL10B was active at alkaline conditions with both endo-1,4-β-d-xylanase and β-xylosidase activities; and XYL11 was a true xylanase characterized by high substrate specificity. These results indicate that F. commune with genetic modification is a promising source of enzymes for the decomposition of lignocellulosic biomass. Copyright © 2015 Elsevier Inc. All rights reserved.

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

The Enzyme Function Initiative†

PubMed Central

Gerlt, John A.; Allen, Karen N.; Almo, Steven C.; Armstrong, Richard N.; Babbitt, Patricia C.; Cronan, John E.; Dunaway-Mariano, Debra; Imker, Heidi J.; Jacobson, Matthew P.; Minor, Wladek; Poulter, C. Dale; Raushel, Frank M.; Sali, Andrej; Shoichet, Brian K.; Sweedler, Jonathan V.

2011-01-01

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily-specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include: 1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation); 2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia; 3) computational and bioinformatic tools for using the strategy; 4) provision of experimental protocols and/or reagents for enzyme production and characterization; and 5) dissemination of data via the EFI’s website, enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal and pharmaceutical efforts. PMID

The Enzyme Function Initiative.

PubMed

Gerlt, John A; Allen, Karen N; Almo, Steven C; Armstrong, Richard N; Babbitt, Patricia C; Cronan, John E; Dunaway-Mariano, Debra; Imker, Heidi J; Jacobson, Matthew P; Minor, Wladek; Poulter, C Dale; Raushel, Frank M; Sali, Andrej; Shoichet, Brian K; Sweedler, Jonathan V

2011-11-22

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts. �

The effects of timbre on melody recognition are mediated by familiarity

NASA Astrophysics Data System (ADS)

McAuley, J. Devin; Ayala, Chris

2002-11-01

Two experiments examined the role of timbre in music recognition. In both experiments, participants rated the familiarity of a set of novel and well-known musical excerpts during a study phase and then were given a surprise old/new recognition test after a retention interval. The recognition test was comprised of the target melodies and an equal number of distractors; participants were instructed to respond yes to the targets and no to the distractors. In experiment 1, the timbre of the melodies was held constant throughout the study and then either stayed the same or switched to a different instrument sound during the test. In experiment 2, timbre varied randomly from trial to trial between the same two instruments used in experiment 1, yielding target melodies that were either mismatched or matched in their timbre. Switching timbre between study and test in experiment 1 was found to hurt the recognition of the novel melodies, but not the familiar melodies. The mediating effect of familiarity was eliminated in experiment 2 when timbre varied randomly from trial to trial rather than remaining constant. Possible reasons for the difference between studies will be discussed.

Enzyme-Responsive Nanomaterials for Controlled Drug Delivery

PubMed Central

Hu, Quanyin; Katti, Prateek S.; Gu, Zhen

2015-01-01

Enzymes underpin physiological function and exhibit dysregulation in many disease-associated microenvironments and aberrant cell processes. Exploiting altered enzyme activity and expression for diagnostics, drug targeting, and drug release is tremendously promising. When combined with booming research in nanobiotechnology, enzyme-responsive nanomaterials for controlled drug release have achieved significant development and been studied as an important class of drug delivery devices in nanomedicine. In this review, we describe enzymes such as proteases, phospholipase and oxidoreductases that serve as delivery triggers. Subsequently, we explore recently developed enzyme-responsive nanomaterials with versatile applications for extracellular and intracellular drug delivery. We conclude by discussing future opportunities and challenges in this area. PMID:25251024

Enzyme-responsive nanomaterials for controlled drug delivery

NASA Astrophysics Data System (ADS)

Hu, Quanyin; Katti, Prateek S.; Gu, Zhen

2014-10-01

Enzymes underpin physiological function and exhibit dysregulation in many disease-associated microenvironments and aberrant cell processes. Exploiting altered enzyme activity and expression for diagnostics, drug targeting, and drug release is tremendously promising. When combined with booming research in nanobiotechnology, enzyme-responsive nanomaterials used for controlled drug release have achieved significant development and have been studied as an important class of drug delivery strategies in nanomedicine. In this review, we describe enzymes such as proteases, phospholipases and oxidoreductases that serve as delivery triggers. Subsequently, we explore recently developed enzyme-responsive nanomaterials with versatile applications for extracellular and intracellular drug delivery. We conclude by discussing future opportunities and challenges in this area.

Effects of pre-experimental knowledge on recognition memory.

PubMed

Bird, Chris M; Davies, Rachel A; Ward, Jamie; Burgess, Neil

2011-01-01

The influence of pre-experimental autobiographical knowledge on recognition memory was investigated using as memoranda faces that were either personally known or unknown to the participant. Under a dual process theory, such knowledge boosted both recollection- and familiarity-based recognition judgements. Under an unequal variance signal detection model, pre-experimental knowledge increased both the variance and the separation of the target and foil memory strength distributions, boosting hits and correct rejections. Thus, pre-experimental knowledge has profound effects on the multiple, interacting processes that subserve recognition memory, and likely in the neural systems that underpin them.

[Recognition of visual objects under forward masking. Effects of cathegorial similarity of test and masking stimuli].

PubMed

Gerasimenko, N Iu; Slavutskaia, A V; Kalinin, S A; Kulikov, M A; Mikhaĭlova, E S

2013-01-01

In 38 healthy subjects accuracy and response time were examined during recognition of two categories of images--animals andnonliving objects--under forward masking. We revealed new data that masking effects depended of categorical similarity of target and masking stimuli. The recognition accuracy was the lowest and the response time was the most slow, when the target and masking stimuli belongs to the same category, that was combined with high dispersion of response times. The revealed effects were more clear in the task of animal recognition in comparison with the recognition of nonliving objects. We supposed that the revealed effects connected with interference between cortical representations of the target and masking stimuli and discussed our results in context of cortical interference and negative priming.

Shape recognition of microbial cells by colloidal cell imprints

NASA Astrophysics Data System (ADS)

Borovička, Josef; Stoyanov, Simeon D.; Paunov, Vesselin N.

2013-08-01

We have engineered a class of colloids which can recognize the shape and size of targeted microbial cells and selectively bind to their surfaces. These imprinted colloid particles, which we called ``colloid antibodies'', were fabricated by partial fragmentation of silica shells obtained by templating the targeted microbial cells. We successfully demonstrated the shape and size recognition between such colloidal imprints and matching microbial cells. High percentage of binding events of colloidal imprints with the size matching target particles was achieved. We demonstrated selective binding of colloidal imprints to target microbial cells in a binary mixture of cells of different shapes and sizes, which also resulted in high binding selectivity. We explored the role of the electrostatic interactions between the target cells and their colloid imprints by pre-coating both of them with polyelectrolytes. Selective binding occurred predominantly in the case of opposite surface charges of the colloid cell imprint and the targeted cells. The mechanism of the recognition is based on the amplification of the surface adhesion in the case of shape and size match due to the increased contact area between the target cell and the colloidal imprint. We also tested the selective binding for colloid imprints of particles of fixed shape and varying sizes. The concept of cell recognition by colloid imprints could be used for development of colloid antibodies for shape-selective binding of microbes. Such colloid antibodies could be additionally functionalized with surface groups to enhance their binding efficiency to cells of specific shape and deliver a drug payload directly to their surface or allow them to be manipulated using external fields. They could benefit the pharmaceutical industry in developing selective antimicrobial therapies and formulations.

Mechanistic insight into the functional transition of the enzyme guanylate kinase induced by a single mutation

PubMed Central

Zhang, Yuebin; Niu, Huiyan; Li, Yan; Chu, Huiying; Shen, Hujun; Zhang, Dinglin; Li, Guohui

2015-01-01

Dramatic functional changes of enzyme usually require scores of alterations in amino acid sequence. However, in the case of guanylate kinase (GK), the functional novelty is induced by a single (S→P) mutation, leading to the functional transition of the enzyme from a phosphoryl transfer kinase into a phosphorprotein interaction domain. Here, by using molecular dynamic (MD) and metadynamics simulations, we provide a comprehensive description of the conformational transitions of the enzyme after mutating serine to proline. Our results suggest that the serine plays a crucial role in maintaining the closed conformation of wild-type GK and the GMP recognition. On the contrary, the S→P mutant exhibits a stable open conformation and loses the ability of ligand binding, which explains its functional transition from the GK enzyme to the GK domain. Furthermore, the free energy profiles (FEPs) obtained by metadymanics clearly demonstrate that the open-closed conformational transition in WT GK is positive correlated with the process of GMP binding, indicating the GMP-induced closing motion of GK enzyme, which is not observed in the mutant. In addition, the FEPs show that the S→P mutation can also leads to the mis-recognition of GMP, explaining the vanishing of catalytic activity of the mutant. PMID:25672880

Mechanistic insight into the functional transition of the enzyme guanylate kinase induced by a single mutation.

PubMed

Zhang, Yuebin; Niu, Huiyan; Li, Yan; Chu, Huiying; Shen, Hujun; Zhang, Dinglin; Li, Guohui

2015-02-12

Dramatic functional changes of enzyme usually require scores of alterations in amino acid sequence. However, in the case of guanylate kinase (GK), the functional novelty is induced by a single (S→P) mutation, leading to the functional transition of the enzyme from a phosphoryl transfer kinase into a phosphorprotein interaction domain. Here, by using molecular dynamic (MD) and metadynamics simulations, we provide a comprehensive description of the conformational transitions of the enzyme after mutating serine to proline. Our results suggest that the serine plays a crucial role in maintaining the closed conformation of wild-type GK and the GMP recognition. On the contrary, the S→P mutant exhibits a stable open conformation and loses the ability of ligand binding, which explains its functional transition from the GK enzyme to the GK domain. Furthermore, the free energy profiles (FEPs) obtained by metadymanics clearly demonstrate that the open-closed conformational transition in WT GK is positive correlated with the process of GMP binding, indicating the GMP-induced closing motion of GK enzyme, which is not observed in the mutant. In addition, the FEPs show that the S→P mutation can also leads to the mis-recognition of GMP, explaining the vanishing of catalytic activity of the mutant.

L2 Word Recognition: Influence of L1 Orthography on Multi-syllabic Word Recognition.

PubMed

Hamada, Megumi

2017-10-01

L2 reading research suggests that L1 orthographic experience influences L2 word recognition. Nevertheless, the findings on multi-syllabic words in English are still limited despite the fact that a vast majority of words are multi-syllabic. The study investigated whether L1 orthography influences the recognition of multi-syllabic words, focusing on the position of an embedded word. The participants were Arabic ESL learners, Chinese ESL learners, and native speakers of English. The task was a word search task, in which the participants identified a target word embedded in a pseudoword at the initial, middle, or final position. The search accuracy and speed indicated that all groups showed a strong preference for the initial position. The accuracy data further indicated group differences. The Arabic group showed higher accuracy in the final than middle, while the Chinese group showed the opposite and the native speakers showed no difference between the two positions. The findings suggest that L2 multi-syllabic word recognition involves unique processes.

Recognition intent and visual word recognition.

PubMed

Wang, Man-Ying; Ching, Chi-Le

2009-03-01

This study adopted a change detection task to investigate whether and how recognition intent affects the construction of orthographic representation in visual word recognition. Chinese readers (Experiment 1-1) and nonreaders (Experiment 1-2) detected color changes in radical components of Chinese characters. Explicit recognition demand was imposed in Experiment 2 by an additional recognition task. When the recognition was implicit, a bias favoring the radical location informative of character identity was found in Chinese readers (Experiment 1-1), but not nonreaders (Experiment 1-2). With explicit recognition demands, the effect of radical location interacted with radical function and word frequency (Experiment 2). An estimate of identification performance under implicit recognition was derived in Experiment 3. These findings reflect the joint influence of recognition intent and orthographic regularity in shaping readers' orthographic representation. The implication for the role of visual attention in word recognition was also discussed.

Application of virtual screening and molecular dynamics for the analysis of selectivity of inhibitors of HU proteins targeted to the DNA-recognition site

NASA Astrophysics Data System (ADS)

Talyzina, A. A.; Agapova, Yu. K.; Podshivalov, D. D.; Timofeev, V. I.; Sidorov-Biryukov, D. D.; Rakitina, T. V.

2017-11-01

DNA-Binding HU proteins are essential for the maintenance of genomic DNA supercoiling and compaction in prokaryotic cells and are promising pharmacological targets for the design of new antibacterial agents. The virtual screening for low-molecular-weight compounds capable of specifically interacting with the DNA-recognition loop of the HU protein from the mycoplasma Spiroplasma melliferum was performed. The ability of the initially selected ligands to form stable complexes with the protein target was assessed by molecular dynamics simulation. One compound, which forms an unstable complex, was eliminated by means of a combination of computational methods, resulting in a decrease in the number of compounds that will pass to the experimental test phase. This approach can be used to solve a wide range of problems related to the search for and validation of low-molecular-weight inhibitors specific for a particular protein target.

Bilingual Language Switching: Production vs. Recognition

PubMed Central

Mosca, Michela; de Bot, Kees

2017-01-01

This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing. PMID:28638361

Bilingual Language Switching: Production vs. Recognition.

PubMed

Mosca, Michela; de Bot, Kees

2017-01-01

This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing.

Novel concept of enzyme selective nicotinamide adenine dinucleotide (NAD)-modified inhibitors based on enzyme taxonomy from the diphosphate conformation of NAD.

PubMed

Fujii, Mikio; Kitagawa, Yasuyuki; Iida, Shui; Kato, Keisuke; Ono, Machiko

2015-11-15

The dihedral angle θ of the diphosphate part of NAD(P) were investigated to distinguish the differences in the binding-conformation of NAD(P) to enzymes and to create an enzyme taxonomy. Furthermore, new inhibitors with fixed dihedral angles showed that enzymes could recognize the differences in the dihedral angle θ. We suggest the taxonomy and the dihedral angle θ are important values for chemists to consider when designing inhibitors and drugs that target enzymes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enzyme activity assay of glycoprotein enzymes based on a boronate affinity molecularly imprinted 96-well microplate.

PubMed

Bi, Xiaodong; Liu, Zhen

2014-12-16

Enzyme activity assay is an important method in clinical diagnostics. However, conventional enzyme activity assay suffers from apparent interference from the sample matrix. Herein, we present a new format of enzyme activity assay that can effectively eliminate the effects of the sample matrix. The key is a 96-well microplate modified with molecularly imprinted polymer (MIP) prepared according to a newly proposed method called boronate affinity-based oriented surface imprinting. Alkaline phosphatase (ALP), a glycoprotein enzyme that has been routinely used as an indicator for several diseases in clinical tests, was taken as a representative target enzyme. The prepared MIP exhibited strong affinity toward the template enzyme (with a dissociation constant of 10(-10) M) as well as superb tolerance for interference. Thus, the enzyme molecules in a complicated sample matrix could be specifically captured and cleaned up for enzyme activity assay, which eliminated the interference from the sample matrix. On the other hand, because the boronate affinity MIP could well retain the enzymatic activity of glycoprotein enzymes, the enzyme captured by the MIP was directly used for activity assay. Thus, additional assay time and possible enzyme or activity loss due to an enzyme release step required by other methods were avoided. Assay of ALP in human serum was successfully demonstrated, suggesting a promising prospect of the proposed method in real-world applications.

The effects of age and divided attention on spontaneous recognition.

PubMed

Anderson, Benjamin A; Jacoby, Larry L; Thomas, Ruthann C; Balota, David A

2011-05-01

Studies of recognition typically involve tests in which the participant's memory for a stimulus is directly questioned. There are occasions however, in which memory occurs more spontaneously (e.g., an acquaintance seeming familiar out of context). Spontaneous recognition was investigated in a novel paradigm involving study of pictures and words followed by recognition judgments on stimuli with an old or new word superimposed over an old or new picture. Participants were instructed to make their recognition decision on either the picture or word and to ignore the distracting stimulus. Spontaneous recognition was measured as the influence of old vs. new distracters on target recognition. Across two experiments, older adults and younger adults placed under divided-attention showed a greater tendency to spontaneously recognize old distracters as compared to full-attention younger adults. The occurrence of spontaneous recognition is discussed in relation to ability to constrain retrieval to goal-relevant information.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

Spoken Word Recognition in Toddlers Who Use Cochlear Implants

PubMed Central

Grieco-Calub, Tina M.; Saffran, Jenny R.; Litovsky, Ruth Y.

2010-01-01

Purpose The purpose of this study was to assess the time course of spoken word recognition in 2-year-old children who use cochlear implants (CIs) in quiet and in the presence of speech competitors. Method Children who use CIs and age-matched peers with normal acoustic hearing listened to familiar auditory labels, in quiet or in the presence of speech competitors, while their eye movements to target objects were digitally recorded. Word recognition performance was quantified by measuring each child’s reaction time (i.e., the latency between the spoken auditory label and the first look at the target object) and accuracy (i.e., the amount of time that children looked at target objects within 367 ms to 2,000 ms after the label onset). Results Children with CIs were less accurate and took longer to fixate target objects than did age-matched children without hearing loss. Both groups of children showed reduced performance in the presence of the speech competitors, although many children continued to recognize labels at above-chance levels. Conclusion The results suggest that the unique auditory experience of young CI users slows the time course of spoken word recognition abilities. In addition, real-world listening environments may slow language processing in young language learners, regardless of their hearing status. PMID:19951921

Proteomic analyses for profiling regulated proteins/enzymes by Fucus vesiculosus fucoidan in B16 melanoma cells: A combination of enzyme kinetics functional study.

PubMed

Wang, Zhi-Jiang; Zheng, Li; Yang, Jun-Mo; Kang, Yani; Park, Yong-Doo

2018-06-01

Fucoidans are complex sulfated polysaccharides that have a wide range of biological activities. Previously, we reported the various effects of Fucus vesiculosus fucoidan on tyrosinase and B16 melanoma cells. In this study, to identify fucoidan-targeted proteins in B16 melanoma cells, we performed a proteomics study and integrated enzyme kinetics. We detected 19 candidate proteins dysregulated by fucoidan treatment. Among the probed proteins, the enzyme kinetics of two candidate enzymes, namely lactate dehydrogenase (LDH) as an upregulated protein and superoxide dismutase (SOD) as a downregulated enzyme, were determined. The enzyme kinetics results showed that Fucus vesiculosus fucoidan significantly inhibited LDH catalytic function while it did not affect SOD activity even at a high dose, while only slightly decreased activity (up to 10%) at a low dose. Based on our previous and present observations, fucoidan could inhibit B16 melanoma cells growth via regulating proteins/enzymes expression levels such as LDH and SOD known as cell survival biomarkers. Interestingly, both expression level and enzyme catalytic activity of LDH were regulated by fucoidan, which could directly induce the apoptotic effect on B16 melanoma cells along with SOD downregulation. This study highlights how combining proteomics with enzyme kinetics can yield valuable insights into fucoidan targets. Copyright © 2018 Elsevier B.V. All rights reserved.

Therapeutic Enzymes: Applications and Approaches to Pharmacological Improvement.

PubMed

Yari, Maryam; Ghoshoon, Mohammad B; Vakili, Bahareh; Ghasemi, Younes

2017-01-01

Among therapeutic proteins, enzymes represent small and of course profitable market. They can be used to treat important, rare, and deadly diseases. Enzyme therapy is the only available treatment for certain disorders. Here, pharmaceutical enzymes are reviewed. They are categorized in four main groups, enzymes in replacement therapy, enzymes in cancer treatment, enzymes for fibrinolysis, and finally enzymes that are used topically for various treatments. Furthermore, enzyme gene therapy and future perspective of therapeutic enzymes are mentioned in brief. There are many important approved enzymes in pharmaceutical market. Several approaches such as point mutation, fusion protein designing, glycoengineering, and PEGylation were used to achieve improved enzymes. Although sometimes enzymes were engineered to facilitate production and purification process, appropriate delivery to target sites, extending half-life, and reducing immunogenicity are among the main goals of engineering approaches. Overall, enzymes play a critical role in treatment of common and rare diseases. Evaluation of new enzymes as well as improvement of approved enzymes are of the most important challenges in biotechnology. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Young people's comparative recognition and recall of an Australian Government Sexual Health Campaign.

PubMed

Lim, Megan S C; Gold, Judy; Bowring, Anna L; Pedrana, Alisa E; Hellard, Margaret E

2015-05-01

In 2009, the Australian Government's National Sexually Transmitted Infection Prevention Program launched a multi-million dollar sexual health campaign targeting young people. We assessed campaign recognition among a community sample of young people. Individuals aged 16-29 years self-completed a questionnaire at a music festival. Participants were asked whether they recognised the campaign image and attempted to match the correct campaign message. Recognition of two concurrent campaigns, GlaxoSmithKline's The Facts genital herpes campaign (targeting young women) and the Drama Downunder campaign (targeting gay men) were assessed simultaneously. Among 471 participants, just 29% recognised the National Sexually Transmitted Infection Prevention Program campaign. This compared to 52% recognising The Facts and 27% recognising Drama Downunder. Of 134 who recognised the National Sexually Transmitted Infection Prevention Program campaign, 27% correctly recalled the campaign messages compared to 61% of those recognising the Facts campaign, and 25% of those recognising the Drama Downunder campaign. There was no difference in National Sexually Transmitted Infection Prevention Program campaign recognition by gender or age. Campaign recognition and message recall of the National Sexually Transmitted Infection Prevention Program campaign was comparatively low. Future mass media sexual health campaigns targeting young people can aim for higher recognition and recall rates than that achieved by the National Sexually Transmitted Infection Prevention Program campaign. Alternative distribution channels and message styles should be considered to increase these rates. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Image processing and recognition for biological images

PubMed Central

Uchida, Seiichi

2013-01-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

Image processing and recognition for biological images.

PubMed

Uchida, Seiichi

2013-05-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

Phage lytic enzymes: a history.

PubMed

Trudil, David

2015-02-01

There are many recent studies regarding the efficacy of bacteriophage-related lytic enzymes: the enzymes of 'bacteria-eaters' or viruses that infect bacteria. By degrading the cell wall of the targeted bacteria, these lytic enzymes have been shown to efficiently lyse Gram-positive bacteria without affecting normal flora and non-related bacteria. Recent studies have suggested approaches for lysing Gram-negative bacteria as well (Briersa Y, et al., 2014). These enzymes include: phage-lysozyme, endolysin, lysozyme, lysin, phage lysin, phage lytic enzymes, phageassociated enzymes, enzybiotics, muralysin, muramidase, virolysin and designations such as Ply, PAE and others. Bacteriophages are viruses that kill bacteria, do not contribute to antimicrobial resistance, are easy to develop, inexpensive to manufacture and safe for humans, animals and the environment. The current focus on lytic enzymes has been on their use as anti-infectives in humans and more recently in agricultural research models. The initial translational application of lytic enzymes, however, was not associated with treating or preventing a specific disease but rather as an extraction method to be incorporated in a rapid bacterial detection assay (Bernstein D, 1997).The current review traces the translational history of phage lytic enzymes-from their initial discovery in 1986 for the rapid detection of group A streptococcus in clinical specimens to evolving applications in the detection and prevention of disease in humans and in agriculture.

Antibody-Unfolding and Metastable-State Binding in Force Spectroscopy and Recognition Imaging

PubMed Central

Kaur, Parminder; Qiang-Fu; Fuhrmann, Alexander; Ros, Robert; Kutner, Linda Obenauer; Schneeweis, Lumelle A.; Navoa, Ryman; Steger, Kirby; Xie, Lei; Yonan, Christopher; Abraham, Ralph; Grace, Michael J.; Lindsay, Stuart

2011-01-01

Force spectroscopy and recognition imaging are important techniques for characterizing and mapping molecular interactions. In both cases, an antibody is pulled away from its target in times that are much less than the normal residence time of the antibody on its target. The distribution of pulling lengths in force spectroscopy shows the development of additional peaks at high loading rates, indicating that part of the antibody frequently unfolds. This propensity to unfold is reversible, indicating that exposure to high loading rates induces a structural transition to a metastable state. Weakened interactions of the antibody in this metastable state could account for reduced specificity in recognition imaging where the loading rates are always high. The much weaker interaction between the partially unfolded antibody and target, while still specific (as shown by control experiments), results in unbinding on millisecond timescales, giving rise to rapid switching noise in the recognition images. At the lower loading rates used in force spectroscopy, we still find discrepancies between the binding kinetics determined by force spectroscopy and those determined by surface plasmon resonance—possibly a consequence of the short tethers used in recognition imaging. Recognition imaging is nonetheless a powerful tool for interpreting complex atomic force microscopy images, so long as specificity is calibrated in situ, and not inferred from equilibrium binding kinetics. PMID:21190677

Age differences in accuracy and choosing in eyewitness identification and face recognition.

PubMed

Searcy, J H; Bartlett, J C; Memon, A

1999-05-01

Studies of aging and face recognition show age-related increases in false recognitions of new faces. To explore implications of this false alarm effect, we had young and senior adults perform (1) three eye-witness identification tasks, using both target present and target absent lineups, and (2) and old/new recognition task in which a study list of faces was followed by a test including old and new faces, along with conjunctions of old faces. Compared with the young, seniors had lower accuracy and higher choosing rates on the lineups, and they also falsely recognized more new faces on the recognition test. However, after screening for perceptual processing deficits, there was no age difference in false recognition of conjunctions, or in discriminating old faces from conjunctions. We conclude that the false alarm effect generalizes to lineup identification, but does not extend to conjunction faces. The findings are consistent with age-related deficits in recollection of context and relative age invariance in perceptual integrative processes underlying the experience of familiarity.

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Neural Dynamics Underlying Target Detection in the Human Brain

PubMed Central

Bansal, Arjun K.; Madhavan, Radhika; Agam, Yigal; Golby, Alexandra; Madsen, Joseph R.

2014-01-01

Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses. PMID:24553944

Production and purification of the multifunctional enzyme horseradish peroxidase

PubMed Central

Spadiut, Oliver; Herwig, Christoph

2014-01-01

The oxidoreductase horseradish peroxidase (HRP) is used in numerous industrial and medical applications. In this review, we briefly describe this well-studied enzyme and focus on its promising use in targeted cancer treatment. In combination with a plant hormone, HRP can be used in specific enzyme–prodrug therapies. Despite this outstanding application, HRP has not found its way as a biopharmaceutical into targeted cancer therapy yet. The reasons therefore lie in the present low-yield production and cumbersome purification of this enzyme from its natural source. However, surface glycosylation renders the recombinant production of HRP difficult. Here, we compare different production hosts for HRP and summarize currently used production and purification strategies for this enzyme. We further present our own strategy of glycoengineering this powerful enzyme to allow recombinant high-yield production in Pichia pastoris and subsequent simple downstream processing. PMID:24683473

Alleviating Cancer Drug Toxicity by Inhibiting a Bacterial Enzyme

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

Wallace, Bret D.; Wang, Hongwei; Lane, Kimberly T.

2011-08-12

The dose-limiting side effect of the common colon cancer chemotherapeutic CPT-11 is severe diarrhea caused by symbiotic bacterial {beta}-glucuronidases that reactivate the drug in the gut. We sought to target these enzymes without killing the commensal bacteria essential for human health. Potent bacterial {beta}-glucuronidase inhibitors were identified by high-throughput screening and shown to have no effect on the orthologous mammalian enzyme. Crystal structures established that selectivity was based on a loop unique to bacterial {beta}-glucuronidases. Inhibitors were highly effective against the enzyme target in living aerobic and anaerobic bacteria, but did not kill the bacteria or harm mammalian cells. Finally,more » oral administration of an inhibitor protected mice from CPT-11-induced toxicity. Thus, drugs may be designed to inhibit undesirable enzyme activities in essential microbial symbiotes to enhance chemotherapeutic efficacy.« less

Alleviating Cancer Drug Toxicity by Inhibiting a Bacterial Enzyme

PubMed Central

Wallace, Bret D.; Wang, Hongwei; Lane, Kimberly T.; Scott, John E.; Orans, Jillian; Koo, Ja Seol; Venkatesh, Madhukumar; Jobin, Christian; Yeh, Li-An; Mani, Sridhar; Redinbo, Matthew R.

2011-01-01

The dose-limiting side effect of the common colon cancer chemotherapeutic CPT-11 is severe diarrhea caused by symbiotic bacterial β-glucuronidases that reactivate the drug in the gut. We sought to target these enzymes without killing the commensal bacteria essential for human health. Potent bacterial β-glucuronidase inhibitors were identified by high-throughput screening and shown to have no effect on the orthologous mammalian enzyme. Crystal structures established that selectivity was based on a loop unique to bacterial β-glucuronidases. Inhibitors were highly effective against the enzyme target in living aerobic and anaerobic bacteria, but did not kill the bacteria or harm mammalian cells. Finally, oral administration of an inhibitor protected mice from CPT-11–induced toxicity. Thus, drugs may be designed to inhibit undesirable enzyme activities in essential microbial symbiotes to enhance chemotherapeutic efficacy. PMID:21051639

Alleviating cancer drug toxicity by inhibiting a bacterial enzyme.

PubMed

Wallace, Bret D; Wang, Hongwei; Lane, Kimberly T; Scott, John E; Orans, Jillian; Koo, Ja Seol; Venkatesh, Madhukumar; Jobin, Christian; Yeh, Li-An; Mani, Sridhar; Redinbo, Matthew R

2010-11-05

The dose-limiting side effect of the common colon cancer chemotherapeutic CPT-11 is severe diarrhea caused by symbiotic bacterial β-glucuronidases that reactivate the drug in the gut. We sought to target these enzymes without killing the commensal bacteria essential for human health. Potent bacterial β-glucuronidase inhibitors were identified by high-throughput screening and shown to have no effect on the orthologous mammalian enzyme. Crystal structures established that selectivity was based on a loop unique to bacterial β-glucuronidases. Inhibitors were highly effective against the enzyme target in living aerobic and anaerobic bacteria, but did not kill the bacteria or harm mammalian cells. Finally, oral administration of an inhibitor protected mice from CPT-11-induced toxicity. Thus, drugs may be designed to inhibit undesirable enzyme activities in essential microbial symbiotes to enhance chemotherapeutic efficacy.

Molecular recognition of pre-tRNA by Arabidopsis protein-only Ribonuclease P.

PubMed

Klemm, Bradley P; Karasik, Agnes; Kaitany, Kipchumba J; Shanmuganathan, Aranganathan; Henley, Matthew J; Thelen, Adam Z; Dewar, Allison J L; Jackson, Nathaniel D; Koutmos, Markos; Fierke, Carol A

2017-12-01

Protein-only ribonuclease P (PRORP) is an enzyme responsible for catalyzing the 5' end maturation of precursor transfer ribonucleic acids (pre-tRNAs) encoded by various cellular compartments in many eukaryotes. PRORPs from plants act as single-subunit enzymes and have been used as a model system for analyzing the function of the metazoan PRORP nuclease subunit, which requires two additional proteins for efficient catalysis. There are currently few molecular details known about the PRORP-pre-tRNA complex. Here, we characterize the determinants of substrate recognition by the single subunit Arabidopsis thaliana PRORP1 and PRORP2 using kinetic and thermodynamic experiments. The salt dependence of binding affinity suggests 4-5 contacts with backbone phosphodiester bonds on substrates, including a single phosphodiester contact with the pre-tRNA 5' leader, consistent with prior reports of short leader requirements. PRORPs contain an N-terminal pentatricopeptide repeat (PPR) domain, truncation of which results in a >30-fold decrease in substrate affinity. While most PPR-containing proteins have been implicated in single-stranded sequence-specific RNA recognition, we find that the PPR motifs of PRORPs recognize pre-tRNA substrates differently. Notably, the PPR domain residues most important for substrate binding in PRORPs do not correspond to positions involved in base recognition in other PPR proteins. Several of these residues are highly conserved in PRORPs from algae, plants, and metazoans, suggesting a conserved strategy for substrate recognition by the PRORP PPR domain. Furthermore, there is no evidence for sequence-specific interactions. This work clarifies molecular determinants of PRORP-substrate recognition and provides a new predictive model for the PRORP-substrate complex. © 2017 Klemm et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Effect of colour pop-out on the recognition of letters in crowding conditions.

PubMed

Põder, Endel

2007-11-01

The crowding effect of adjacent objects on the recognition of a target can be reduced when target and flankers differ in some feature, that is irrelevant to the recognition task. In this study, the mechanisms of this effect were explored using targets and flankers of the same and different colours. It was found that facilitation nearly equal to that of differently coloured targets and flankers can be observed with a differently coloured background blob in the location of the target. The different-colour effect does not require advance knowledge of the target and flanker colours, but the effect increases in the course of three trials with constant mapping of colours. The results are consistent with the notion of exogenous attention that facilitates the processing at the most salient locations in the visual field.

Activity-based proteomics of enzyme superfamilies: serine hydrolases as a case study.

PubMed

Simon, Gabriel M; Cravatt, Benjamin F

2010-04-09

Genome sequencing projects have uncovered thousands of uncharacterized enzymes in eukaryotic and prokaryotic organisms. Deciphering the physiological functions of enzymes requires tools to profile and perturb their activities in native biological systems. Activity-based protein profiling has emerged as a powerful chemoproteomic strategy to achieve these objectives through the use of chemical probes that target large swaths of enzymes that share active-site features. Here, we review activity-based protein profiling and its implementation to annotate the enzymatic proteome, with particular attention given to probes that target serine hydrolases, a diverse superfamily of enzymes replete with many uncharacterized members.

Recognition during recall failure: Semantic feature matching as a mechanism for recognition of semantic cues when recall fails.

PubMed

Cleary, Anne M; Ryals, Anthony J; Wagner, Samantha R

2016-01-01

Research suggests that a feature-matching process underlies cue familiarity-detection when cued recall with graphemic cues fails. When a test cue (e.g., potchbork) overlaps in graphemic features with multiple unrecalled studied items (e.g., patchwork, pitchfork, pocketbook, pullcork), higher cue familiarity ratings are given during recall failure of all of the targets than when the cue overlaps in graphemic features with only one studied target and that target fails to be recalled (e.g., patchwork). The present study used semantic feature production norms (McRae et al., Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005) to examine whether the same holds true when the cues are semantic in nature (e.g., jaguar is used to cue cheetah). Indeed, test cues (e.g., cedar) that overlapped in semantic features (e.g., a_tree, has_bark, etc.) with four unretrieved studied items (e.g., birch, oak, pine, willow) received higher cue familiarity ratings during recall failure than test cues that overlapped in semantic features with only two (also unretrieved) studied items (e.g., birch, oak), which in turn received higher familiarity ratings during recall failure than cues that did not overlap in semantic features with any studied items. These findings suggest that the feature-matching theory of recognition during recall failure can accommodate recognition of semantic cues during recall failure, providing a potential mechanism for conceptually-based forms of cue recognition during target retrieval failure. They also provide converging evidence for the existence of the semantic features envisaged in feature-based models of semantic knowledge representation and for those more concretely specified by the production norms of McRae et al. (Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005).

Pattern-Recognition System for Approaching a Known Target

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang

2008-01-01

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target

Recognition of visual stimuli and memory for spatial context in schizophrenic patients and healthy volunteers.

PubMed

Brébion, Gildas; David, Anthony S; Pilowsky, Lyn S; Jones, Hugh

2004-11-01

Verbal and visual recognition tasks were administered to 40 patients with schizophrenia and 40 healthy comparison subjects. The verbal recognition task consisted of discriminating between 16 target words and 16 new words. The visual recognition task consisted of discriminating between 16 target pictures (8 black-and-white and 8 color) and 16 new pictures (8 black-and-white and 8 color). Visual recognition was followed by a spatial context discrimination task in which subjects were required to remember the spatial location of the target pictures at encoding. Results showed that recognition deficit in patients was similar for verbal and visual material. In both schizophrenic and healthy groups, men, but not women, obtained better recognition scores for the colored than for the black-and-white pictures. However, men and women similarly benefited from color to reduce spatial context discrimination errors. Patients showed a significant deficit in remembering the spatial location of the pictures, independently of accuracy in remembering the pictures themselves. These data suggest that patients are impaired in the amount of visual information that they can encode. With regards to the perceptual attributes of the stimuli, memory for spatial information appears to be affected, but not processing of color information.

New hydroxamate inhibitors of neurotensin-degrading enzymes. Synthesis and enzyme active-site recognition.

PubMed

Bourdel, E; Doulut, S; Jarretou, G; Labbe-Jullie, C; Fehrentz, J A; Doumbia, O; Kitabgi, P; Martinez, J

1996-08-01

Selective and mixed inhibitors of the three zinc metallopeptidases that degrade neurotensin (NT), e.g. endopeptidase 24-16 (EC 3.4.24.16), endopeptidase 24-11 (EC 3.4.24.11 or neutral endopeptidase, NEP) and endopeptidase 24-15 (EC 3.4.24.15), and leucine-aminopeptidase (type IV-S), that degrades the NT-related peptides, Neuromedin N (NN), are of great interest. On the structural basis of compound JMV 390-1 (N-[3-[(hydroxyamino)carbonyl]-1-oxo-2(R)-benzylpropyl]-L- isoleucyl-L-leucine), which was a full inhibitor of the major NT degrading enzymes, several hydroxamate inhibitors corresponding to the general formula HONHCO-CH2-CH(CH2-C6H5)CO-X-Y-OH (with X-Y = dipeptide) have been synthesized. Compound 7a (X-Y = Ile-Ala) was nearly 40-times more potent in inhibiting EC 24-16 than NEP and more than 800-times more potent than EC 24-15, with an IC50 (12 nM) almost equivalent to that of compound JMV 390-1. Therefore, this compound is an interesting selective inhibitor of EC 24-16, and should be an interesting probe to explore the physiological involvement of EC 24-16 in the metabolism of neurotensin.

Metabolic enzymes dysregulation in heart failure: the prospective therapy.

PubMed

Parihar, Priyanka; Parihar, Mordhwaj Singh

2017-01-01

The heart failure accounts for the highest mortality rate all over the world. The development of preventive therapeutic approaches is still in their infancy. Owing to the extremely high energy demand of the heart, the bioenergetics pathways need to respond efficiently based on substrate availability. The metabolic regulation of such heart bioenergetics is mediated by various rate limiting enzymes involved in energy metabolism. Although all the pertinent mechanisms are not clearly understood, the progressive decline in the activity of metabolic enzymes leading to diminished ATP production is known to cause progression of the heart failure. Therefore, metabolic therapy that can maintain the appropriate activities of metabolic enzymes can be a promising approach for the prevention and treatment of the heart failure. The flavonoids that constitute various human dietary ingredients also effectively offer a variety of health benefits. The flavonoids target a variety of metabolic enzymes and facilitate effective management of the equilibrium between production and utilization of energy in the heart. This review discusses the broad impact of metabolic enzymes in the heart functions and explains how the dysregulated enzyme activity causes the heart failure. In addition, the prospects of targeting dysregulated metabolic enzymes by developing flavonoid-based metabolic approaches are discussed.

The Slow Developmental Time Course of Real-Time Spoken Word Recognition

ERIC Educational Resources Information Center

Rigler, Hannah; Farris-Trimble, Ashley; Greiner, Lea; Walker, Jessica; Tomblin, J. Bruce; McMurray, Bob

2015-01-01

This study investigated the developmental time course of spoken word recognition in older children using eye tracking to assess how the real-time processing dynamics of word recognition change over development. We found that 9-year-olds were slower to activate the target words and showed more early competition from competitor words than…

Crystal Structures of Trypanosoma cruzi UDP-Galactopyranose Mutase Implicate Flexibility of the Histidine Loop in Enzyme Activation

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

Dhatwalia, Richa; Singh, Harkewal; Oppenheimer, Michelle

2012-11-01

Chagas disease is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. Here we report crystal structures of the galactofuranose biosynthetic enzyme UDP-galactopyranose mutase (UGM) from T. cruzi, which are the first structures of this enzyme from a protozoan parasite. UGM is an attractive target for drug design because galactofuranose is absent in humans but is an essential component of key glycoproteins and glycolipids in trypanosomatids. Analysis of the enzyme-UDP noncovalent interactions and sequence alignments suggests that substrate recognition is exquisitely conserved among eukaryotic UGMs and distinct from that of bacterial UGMs. This observation has implications for inhibitormore » design. Activation of the enzyme via reduction of the FAD induces profound conformational changes, including a 2.3 {angstrom} movement of the histidine loop (Gly60-Gly61-His62), rotation and protonation of the imidazole of His62, and cooperative movement of residues located on the si face of the FAD. Interestingly, these changes are substantially different from those described for Aspergillus fumigatus UGM, which is 45% identical to T. cruzi UGM. The importance of Gly61 and His62 for enzymatic activity was studied with the site-directed mutant enzymes G61A, G61P, and H62A. These mutations lower the catalytic efficiency by factors of 10-50, primarily by decreasing k{sub cat}. Considered together, the structural, kinetic, and sequence data suggest that the middle Gly of the histidine loop imparts flexibility that is essential for activation of eukaryotic UGMs. Our results provide new information about UGM biochemistry and suggest a unified strategy for designing inhibitors of UGMs from the eukaryotic pathogens.« less

Crystal Structures of Trypanosoma cruzi UDP-Galactopyranose Mutase Implicate Flexibility of the Histidine Loop in Enzyme Activation

PubMed Central

Dhatwalia, Richa; Singh, Harkewal; Oppenheimer, Michelle; Sobrado, Pablo; Tanner, John J.

2012-01-01

Chagas disease is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. Here we report crystal structures of the galactofuranose biosynthetic enzyme UDP-galactopyranose mutase (UGM) from T. cruzi, which are the first structures of this enzyme from a protozoan parasite. UGM is an attractive target for drug design because galactofuranose is absent in humans but is an essential component of key glycoproteins and glycolipids in trypanosomatids. Analysis of the enzyme-UDP noncovalent interactions and sequence alignments suggests that substrate recognition is exquisitely conserved among eukaryotic UGMs and distinct from that of bacterial UGMs. This observation has implications for inhibitor design. Activation of the enzyme via reduction of the FAD induces profound conformational changes, including a 2.3-Å movement of the histidine loop (Gly60-Gly61-His62), rotation and protonation of the imidazole of His62, and cooperative movement of residues located on the si face of the FAD. Interestingly, these changes are substantially different from those described for Aspergillus fumigatus UGM, which is 45 % identical to T. cruzi UGM. The importance of Gly61 and His62 for enzymatic activity was studied with the site-directed mutant enzymes G61A, G61P, and H62A. These mutations lower the catalytic efficiency by factors of 10–50, primarily by decreasing kcat. Considered together, the structural, kinetic, and sequence data suggest that the middle Gly of the histidine loop imparts flexibility that is essential for activation of eukaryotic UGMs. Our results provide new information about UGM biochemistry and suggest a unified strategy for designing inhibitors of UGMs from the eukaryotic pathogens. PMID:22646091

Crystal structures of Trypanosoma cruzi UDP-galactopyranose mutase implicate flexibility of the histidine loop in enzyme activation.

PubMed

Dhatwalia, Richa; Singh, Harkewal; Oppenheimer, Michelle; Sobrado, Pablo; Tanner, John J

2012-06-19

Chagas disease is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi. Here we report crystal structures of the galactofuranose biosynthetic enzyme UDP-galactopyranose mutase (UGM) from T. cruzi, which are the first structures of this enzyme from a protozoan parasite. UGM is an attractive target for drug design because galactofuranose is absent in humans but is an essential component of key glycoproteins and glycolipids in trypanosomatids. Analysis of the enzyme-UDP noncovalent interactions and sequence alignments suggests that substrate recognition is exquisitely conserved among eukaryotic UGMs and distinct from that of bacterial UGMs. This observation has implications for inhibitor design. Activation of the enzyme via reduction of the FAD induces profound conformational changes, including a 2.3 Å movement of the histidine loop (Gly60-Gly61-His62), rotation and protonation of the imidazole of His62, and cooperative movement of residues located on the si face of the FAD. Interestingly, these changes are substantially different from those described for Aspergillus fumigatus UGM, which is 45% identical to T. cruzi UGM. The importance of Gly61 and His62 for enzymatic activity was studied with the site-directed mutant enzymes G61A, G61P, and H62A. These mutations lower the catalytic efficiency by factors of 10-50, primarily by decreasing k(cat). Considered together, the structural, kinetic, and sequence data suggest that the middle Gly of the histidine loop imparts flexibility that is essential for activation of eukaryotic UGMs. Our results provide new information about UGM biochemistry and suggest a unified strategy for designing inhibitors of UGMs from the eukaryotic pathogens.

Structures of the Signal Recognition Particle Receptor from the Archaeon Pyrococcus furiosus: Implications for the Targeting Step at the Membrane

PubMed Central

Egea, Pascal F.; Tsuruta, Hiro; de Leon, Gladys P.; Napetschnig, Johanna; Walter, Peter; Stroud, Robert M.

2008-01-01

In all organisms, a ribonucleoprotein called the signal recognition particle (SRP) and its receptor (SR) target nascent proteins from the ribosome to the translocon for secretion or membrane insertion. We present the first X-ray structures of an archeal FtsY, the receptor from the hyper-thermophile Pyrococcus furiosus (Pfu), in its free and GDP•magnesium-bound forms. The highly charged N-terminal domain of Pfu-FtsY is distinguished by a long N-terminal helix. The basic charges on the surface of this helix are likely to regulate interactions at the membrane. A peripheral GDP bound near a regulatory motif could indicate a site of interaction between the receptor and ribosomal or SRP RNAs. Small angle X-ray scattering and analytical ultracentrifugation indicate that the crystal structure of Pfu-FtsY correlates well with the average conformation in solution. Based on previous structures of two sub-complexes, we propose a model of the core of archeal and eukaryotic SRP•SR targeting complexes. PMID:18978942

Targeted metabolomics connects thioredoxin-interacting protein (TXNIP) to mitochondrial fuel selection and regulation of specific oxidoreductase enzymes in skeletal muscle.

PubMed

DeBalsi, Karen L; Wong, Kari E; Koves, Timothy R; Slentz, Dorothy H; Seiler, Sarah E; Wittmann, April H; Ilkayeva, Olga R; Stevens, Robert D; Perry, Christopher G R; Lark, Daniel S; Hui, Simon T; Szweda, Luke; Neufer, P Darrell; Muoio, Deborah M

2014-03-21

Thioredoxin-interacting protein (TXNIP) is an α-arrestin family member involved in redox sensing and metabolic control. Growing evidence links TXNIP to mitochondrial function, but the molecular nature of this relationship has remained poorly defined. Herein, we employed targeted metabolomics and comprehensive bioenergetic analyses to evaluate oxidative metabolism and respiratory kinetics in mouse models of total body (TKO) and skeletal muscle-specific (TXNIP(SKM-/-)) Txnip deficiency. Compared with littermate controls, both TKO and TXNIP(SKM-/-) mice had reduced exercise tolerance in association with muscle-specific impairments in substrate oxidation. Oxidative insufficiencies in TXNIP null muscles were not due to perturbations in mitochondrial mass, the electron transport chain, or emission of reactive oxygen species. Instead, metabolic profiling analyses led to the discovery that TXNIP deficiency causes marked deficits in enzymes required for catabolism of branched chain amino acids, ketones, and lactate, along with more modest reductions in enzymes of β-oxidation and the tricarboxylic acid cycle. The decrements in enzyme activity were accompanied by comparable deficits in protein abundance without changes in mRNA expression, implying dysregulation of protein synthesis or stability. Considering that TXNIP expression increases in response to starvation, diabetes, and exercise, these findings point to a novel role for TXNIP in coordinating mitochondrial fuel switching in response to nutrient availability.

Targeted Metabolomics Connects Thioredoxin-interacting Protein (TXNIP) to Mitochondrial Fuel Selection and Regulation of Specific Oxidoreductase Enzymes in Skeletal Muscle*

PubMed Central

DeBalsi, Karen L.; Wong, Kari E.; Koves, Timothy R.; Slentz, Dorothy H.; Seiler, Sarah E.; Wittmann, April H.; Ilkayeva, Olga R.; Stevens, Robert D.; Perry, Christopher G. R.; Lark, Daniel S.; Hui, Simon T.; Szweda, Luke; Neufer, P. Darrell; Muoio, Deborah M.

2014-01-01

Thioredoxin-interacting protein (TXNIP) is an α-arrestin family member involved in redox sensing and metabolic control. Growing evidence links TXNIP to mitochondrial function, but the molecular nature of this relationship has remained poorly defined. Herein, we employed targeted metabolomics and comprehensive bioenergetic analyses to evaluate oxidative metabolism and respiratory kinetics in mouse models of total body (TKO) and skeletal muscle-specific (TXNIPSKM−/−) Txnip deficiency. Compared with littermate controls, both TKO and TXNIPSKM−/− mice had reduced exercise tolerance in association with muscle-specific impairments in substrate oxidation. Oxidative insufficiencies in TXNIP null muscles were not due to perturbations in mitochondrial mass, the electron transport chain, or emission of reactive oxygen species. Instead, metabolic profiling analyses led to the discovery that TXNIP deficiency causes marked deficits in enzymes required for catabolism of branched chain amino acids, ketones, and lactate, along with more modest reductions in enzymes of β-oxidation and the tricarboxylic acid cycle. The decrements in enzyme activity were accompanied by comparable deficits in protein abundance without changes in mRNA expression, implying dysregulation of protein synthesis or stability. Considering that TXNIP expression increases in response to starvation, diabetes, and exercise, these findings point to a novel role for TXNIP in coordinating mitochondrial fuel switching in response to nutrient availability. PMID:24482226

Bio-recognitive photonics of a DNA-guided organic semiconductor.

PubMed

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor

NASA Astrophysics Data System (ADS)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Polyhydroxylated [60]fullerene binds specifically to functional recognition sites on a monomeric and a dimeric ubiquitin

NASA Astrophysics Data System (ADS)

Zanzoni, Serena; Ceccon, Alberto; Assfalg, Michael; Singh, Rajesh K.; Fushman, David; D'Onofrio, Mariapina

2015-04-01

The use of nanoparticles (NPs) in biomedical applications requires an in-depth understanding of the mechanisms by which NPs interact with biomolecules. NPs associating with proteins may interfere with protein-protein interactions and affect cellular communication pathways, however the impact of NPs on biomolecular recognition remains poorly characterized. In this respect, particularly relevant is the study of NP-induced functional perturbations of proteins implicated in the regulation of key biochemical pathways. Ubiquitin (Ub) is a prototypical protein post-translational modifier playing a central role in numerous essential biological processes. To contribute to the understanding of the interactions between this universally distributed biomacromolecule and NPs, we investigated the adsorption of polyhydroxylated [60]fullerene on monomeric Ub and on a minimal polyubiquitin chain in vitro at atomic resolution. Site-resolved chemical shift and intensity perturbations of Ub's NMR signals, together with 15N spin relaxation rate changes, exchange saturation transfer effects, and fluorescence quenching data were consistent with the reversible formation of soluble aggregates incorporating fullerenol clusters. The specific interaction epitopes were identified, coincident with functional recognition sites in a monomeric and lysine48-linked dimeric Ub. Fullerenol appeared to target the open state of the dynamic structure of a dimeric Ub according to a conformational selection mechanism. Importantly, the protein-NP association prevented the enzyme-catalyzed synthesis of polyubiquitin chains. Our findings provide an experiment-based insight into protein/fullerenol recognition, with implications in functional biomolecular communication, including regulatory protein turnover, and for the opportunity of therapeutic intervention in Ub-dependent cellular pathways.The use of nanoparticles (NPs) in biomedical applications requires an in-depth understanding of the mechanisms by which

Targeted modulation of reactive oxygen species in the vascular endothelium.

PubMed

Shuvaev, Vladimir V; Muzykantov, Vladimir R

2011-07-15

'Endothelial cells lining vascular luminal surface represent an important site of signaling and injurious effects of reactive oxygen species (ROS) produced by other cells and endothelium itself in ischemia, inflammation and other pathological conditions. Targeted delivery of ROS modulating enzymes conjugated with antibodies to endothelial surface molecules (vascular immunotargeting) provides site-specific interventions in the endothelial ROS, unattainable by other formulations including PEG-modified enzymes. Targeting of ROS generating enzymes (e.g., glucose oxidase) provides ROS- and site-specific models of endothelial oxidative stress, whereas targeting of antioxidant enzymes SOD and catalase offers site-specific quenching of superoxide anion and H(2)O(2). These targeted antioxidant interventions help to clarify specific role of endothelial ROS in vascular and pulmonary pathologies and provide basis for design of targeted therapeutics for treatment of these pathologies. In particular, antibody/catalase conjugates alleviate acute lung ischemia/reperfusion injury, whereas antibody/SOD conjugates inhibit ROS-mediated vasoconstriction and inflammatory endothelial signaling. Encapsulation in protease-resistant, ROS-permeable carriers targeted to endothelium prolongs protective effects of antioxidant enzymes, further diversifying the means for targeted modulation of endothelial ROS. Copyright © 2011 Elsevier B.V. All rights reserved.

Error Rates in Users of Automatic Face Recognition Software

PubMed Central

White, David; Dunn, James D.; Schmid, Alexandra C.; Kemp, Richard I.

2015-01-01

In recent years, wide deployment of automatic face recognition systems has been accompanied by substantial gains in algorithm performance. However, benchmarking tests designed to evaluate these systems do not account for the errors of human operators, who are often an integral part of face recognition solutions in forensic and security settings. This causes a mismatch between evaluation tests and operational accuracy. We address this by measuring user performance in a face recognition system used to screen passport applications for identity fraud. Experiment 1 measured target detection accuracy in algorithm-generated ‘candidate lists’ selected from a large database of passport images. Accuracy was notably poorer than in previous studies of unfamiliar face matching: participants made over 50% errors for adult target faces, and over 60% when matching images of children. Experiment 2 then compared performance of student participants to trained passport officers–who use the system in their daily work–and found equivalent performance in these groups. Encouragingly, a group of highly trained and experienced “facial examiners” outperformed these groups by 20 percentage points. We conclude that human performance curtails accuracy of face recognition systems–potentially reducing benchmark estimates by 50% in operational settings. Mere practise does not attenuate these limits, but superior performance of trained examiners suggests that recruitment and selection of human operators, in combination with effective training and mentorship, can improve the operational accuracy of face recognition systems. PMID:26465631

Optogenetic Stimulation of Prefrontal Glutamatergic Neurons Enhances Recognition Memory.

PubMed

Benn, Abigail; Barker, Gareth R I; Stuart, Sarah A; Roloff, Eva V L; Teschemacher, Anja G; Warburton, E Clea; Robinson, Emma S J

2016-05-04

Finding effective cognitive enhancers is a major health challenge; however, modulating glutamatergic neurotransmission has the potential to enhance performance in recognition memory tasks. Previous studies using glutamate receptor antagonists have revealed that the medial prefrontal cortex (mPFC) plays a central role in associative recognition memory. The present study investigates short-term recognition memory using optogenetics to target glutamatergic neurons within the rodent mPFC specifically. Selective stimulation of glutamatergic neurons during the online maintenance of information enhanced associative recognition memory in normal animals. This cognitive enhancing effect was replicated by local infusions of the AMPAkine CX516, but not CX546, which differ in their effects on EPSPs. This suggests that enhancing the amplitude, but not the duration, of excitatory synaptic currents improves memory performance. Increasing glutamate release through infusions of the mGluR7 presynaptic receptor antagonist MMPIP had no effect on performance. These results provide new mechanistic information that could guide the targeting of future cognitive enhancers. Our work suggests that improved associative-recognition memory can be achieved by enhancing endogenous glutamatergic neuronal activity selectively using an optogenetic approach. We build on these observations to recapitulate this effect using drug treatments that enhance the amplitude of EPSPs; however, drugs that alter the duration of the EPSP or increase glutamate release lack efficacy. This suggests that both neural and temporal specificity are needed to achieve cognitive enhancement. Copyright © 2016 Benn et al.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Biochemical and Structural Analysis of Inhibitors Targeting the ADC-7 Cephalosporinase of Acinetobacter baumannii

DOE PAGES

Powers, Rachel A.; Swanson, Hollister C.; Taracila, Magdalena A.; ...

2014-11-07

β-Lactam resistance in Acinetobacter baumannii presents one of the greatest challenges to contemporary antimicrobial chemotherapy. Much of this resistance to cephalosporins derives from the expression of the class C β-lactamase enzymes, known as Acinetobacter-derived cephalosporinases (ADCs). Currently, β-lactamase inhibitors are structurally similar to β-lactam substrates and are not effective inactivators of this class C cephalosporinase. Herein, two boronic acid transition state inhibitors (BATSIs S02030 and SM23) that are chemically distinct from β-lactams were designed and tested for inhibition of ADC enzymes. BATSIs SM23 and S02030 bind with high affinity to ADC-7, a chromosomal cephalosporinase from Acinetobacter baumannii (K i =more » 21.1 ± 1.9 nM and 44.5 ± 2.2 nM, respectively). The X-ray crystal structures of ADC-7 were determined in both the apo form (1.73 Å resolution) and in complex with S02030 (2.0 Å resolution). In the complex, S02030 makes several canonical interactions: the O1 oxygen of S02030 is bound in the oxyanion hole, and the R1 amide group makes key interactions with conserved residues Asn152 and Gln120. In addition, the carboxylate group of the inhibitor is meant to mimic the C 3/C 4 carboxylate found in β-lactams. The C 3/C 4 carboxylate recognition site in class C enzymes is comprised of Asn346 and Arg349 (AmpC numbering), and these residues are conserved in ADC-7. Interestingly, in the ADC-7/S02030 complex, the inhibitor carboxylate group is observed to interact with Arg340, a residue that distinguishes ADC-7 from the related class C enzyme AmpC. A thermodynamic analysis suggests that ΔH driven compounds may be optimized to generate new lead agents. In conclusion, the ADC-7/BATSI complex provides insight into recognition of non-β-lactam inhibitors by ADC enzymes and offers a starting point for the structure-based optimization of this class of novel β-lactamase inhibitors against a key resistance target.« less

Anticipatory coarticulation facilitates word recognition in toddlers.

PubMed

Mahr, Tristan; McMillan, Brianna T M; Saffran, Jenny R; Ellis Weismer, Susan; Edwards, Jan

2015-09-01

Children learn from their environments and their caregivers. To capitalize on learning opportunities, young children have to recognize familiar words efficiently by integrating contextual cues across word boundaries. Previous research has shown that adults can use phonetic cues from anticipatory coarticulation during word recognition. We asked whether 18-24 month-olds (n=29) used coarticulatory cues on the word "the" when recognizing the following noun. We performed a looking-while-listening eyetracking experiment to examine word recognition in neutral vs. facilitating coarticulatory conditions. Participants looked to the target image significantly sooner when the determiner contained facilitating coarticulatory cues. These results provide the first evidence that novice word-learners can take advantage of anticipatory sub-phonemic cues during word recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

"Inject-mix-react-separate-and-quantitate" (IMReSQ) method for screening enzyme inhibitors.

PubMed

Wong, Edmund; Okhonin, Victor; Berezovski, Maxim V; Nozaki, Tomoyoshi; Waldmann, Herbert; Alexandrov, Kirill; Krylov, Sergey N

2008-09-10

Many regulatory enzymes are considered attractive therapeutic targets, and their inhibitors are potential drug candidates. Screening combinatorial libraries for enzyme inhibitors is pivotal to identifying hit compounds for the development of drugs targeting regulatory enzymes. Here, we introduce the first inhibitor screening method that consumes only nanoliters of the reactant solutions and is applicable to regulatory enzymes. The method is termed inject-mix-react-separate-and-quantitate (IMReSQ) and includes five steps. First, nanoliter volumes of substrate, candidate inhibitor, and enzyme solutions are injected by pressure into a capillary as separate plugs. Second, the plugs are mixed inside this capillary microreactor by transverse diffusion of laminar flow profiles. Third, the reaction mixture is incubated to form the enzymatic product. Fourth, the product is separated from the substrate inside the capillary by electrophoresis. Fifth, the amounts of the product and substrate are quantitated. In this proof-of-principle work, we applied IMReSQ to study inhibition of recently cloned protein farnesyltransferase from parasite Entamoeba histolytica. This enzyme is a potential therapeutic target for antiparasitic drugs. We identified three previously unknown inhibitors of this enzyme and proved that IMReSQ could be used for quantitatively ranking the potencies of inhibitors.

Regulation of Ubiquitin Enzymes in the TGF-β Pathway.

PubMed

Iyengar, Prasanna Vasudevan

2017-04-20

The transforming growth factor-β (TGF-β) pathway has a tumor suppressor role in normal and premalignant cells but promotes oncogenesis in advanced cancer cells. Components of the pathway are tightly controlled by ubiquitin modifying enzymes and aberrations in these enzymes are frequently observed to dysregulate the pathway causing diseases such as bone disorders, cancer and metastasis. These enzymes and their counterparts are increasingly being tested as druggable targets, and thus a deeper understanding of the enzymes is required. This review summarizes the roles of specific ubiquitin modifying enzymes in the TGF-β pathway and how they are regulated.

Virtual reality method to analyze visual recognition in mice.

PubMed

Young, Brent Kevin; Brennan, Jayden Nicole; Wang, Ping; Tian, Ning

2018-01-01

Behavioral tests have been extensively used to measure the visual function of mice. To determine how precisely mice perceive certain visual cues, it is necessary to have a quantifiable measurement of their behavioral responses. Recently, virtual reality tests have been utilized for a variety of purposes, from analyzing hippocampal cell functionality to identifying visual acuity. Despite the widespread use of these tests, the training requirement for the recognition of a variety of different visual targets, and the performance of the behavioral tests has not been thoroughly characterized. We have developed a virtual reality behavior testing approach that can essay a variety of different aspects of visual perception, including color/luminance and motion detection. When tested for the ability to detect a color/luminance target or a moving target, mice were able to discern the designated target after 9 days of continuous training. However, the quality of their performance is significantly affected by the complexity of the visual target, and their ability to navigate on a spherical treadmill. Importantly, mice retained memory of their visual recognition for at least three weeks after the end of their behavioral training.

Influence of Emotional Facial Expressions on 3-5-Year-Olds' Face Recognition

ERIC Educational Resources Information Center

Freitag, Claudia; Schwarzer, Gudrun

2011-01-01

Three experiments examined 3- and 5-year-olds' recognition of faces in constant and varied emotional expressions. Children were asked to identify repeatedly presented target faces, distinguishing them from distractor faces, during an immediate recognition test and during delayed assessments after 10 min and one week. Emotional facial expression…

Individual differences in online spoken word recognition: Implications for SLI

PubMed Central

McMurray, Bob; Samelson, Vicki M.; Lee, Sung Hee; Tomblin, J. Bruce

2012-01-01

Thirty years of research has uncovered the broad principles that characterize spoken word processing across listeners. However, there have been few systematic investigations of individual differences. Such an investigation could help refine models of word recognition by indicating which processing parameters are likely to vary, and could also have important implications for work on language impairment. The present study begins to fill this gap by relating individual differences in overall language ability to variation in online word recognition processes. Using the visual world paradigm, we evaluated online spoken word recognition in adolescents who varied in both basic language abilities and non-verbal cognitive abilities. Eye movements to target, cohort and rhyme objects were monitored during spoken word recognition, as an index of lexical activation. Adolescents with poor language skills showed fewer looks to the target and more fixations to the cohort and rhyme competitors. These results were compared to a number of variants of the TRACE model (McClelland & Elman, 1986) that were constructed to test a range of theoretical approaches to language impairment: impairments at sensory and phonological levels; vocabulary size, and generalized slowing. None were strongly supported, and variation in lexical decay offered the best fit. Thus, basic word recognition processes like lexical decay may offer a new way to characterize processing differences in language impairment. PMID:19836014

Enzyme decorated drug carriers: Targeted swords to cleave and overcome the mucus barrier.

PubMed

Menzel, Claudia; Bernkop-Schnürch, Andreas

2018-01-15

The use of mucus permeating drug carrier systems being able to overcome the mucus barrier can lead to a remarkable enhancement in bioavailability. One promising approach is the design of mucolytic enzyme decorated carrier systems (MECS). These systems include micro- and nanoparticles as well as self-emulsifying drug delivery systems (SEDDS) decorated with mucin cleaving enzymes such as papain (PAP) or bromelain (BRO). MECS are able to cross the mucus barrier in a comparatively efficient manner by cleaving mucus substructures in front of them on their way to the epithelium. Thereby these enzymes hydrolyze peptide bonds of mucus glycoproteins forming tiny holes or passages through the mucus. In various in vitro and in vivo studies MECS proved to be superior in their mucus permeating properties over nanocarriers without enzyme decoration. PAP decorated nanoparticles, for instance, remained 3h after oral administration to an even 2.5-fold higher extend in rat small intestine than the corresponding undecorated nanoparticles permeating the intestinal mucus gel layer to a much lower degree. As MECS break up the mucus network only locally without destroying its overall protective barrier function, even long term treatments with such systems seem feasible. Within this review article we address different drug carrier systems decorated with various types of enzymes, their particular pros and cons and potential applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Enzyme/indicator optrodes for detection of heavy metal ions and pesticides

NASA Astrophysics Data System (ADS)

Nabok, Alexei V.; Ray, Asim K.; Starodub, Nickolaj F.; Dowker, Kenneth P.

2000-12-01

Composite films containing enzyme and indicator molecules were produced by means of polyelectrolyte self-assembly. These membranes provide two functions: (i) molecular recognition of the substratum by respective enzyme, and (ii) optrode transducing, when the products o the substratum decomposition affect optical spectra of indicator molecules. Apart from direct registration of enzyme reactions, inhibition reactions can also be monitored with this method. Particularly, heavy metal salts and phosphor organic pesticides acting as inhibitors for Urease and Cholinesterase, respectively, were registered. Composite PESA films were deposited onto glass slides and consisted of several layers of poly(alylamine) hydrochloride (PAA) alternated with indicator molecules, either Cyclo-tetra- chromotropylene or Thymol Blue, both containing SO3- Na+ groups. Then a few layers of PAA/enzyme were deposited on top. A typical structure of the samples was (PAA/Indicator)n/(PAA/Enzyme)m/PAA with n equals 1-5. The obtained films were characterized with UV-visible absorption spectroscopy. The effect of the substrate decomposition on the UV-vis spectra of respective indicator molecules was studied. The inhibition of enzymes Urease and Cholinesterase by heavy metal ions and phosphor organic pesticide, respectively was found. The results obtained show the prospects towards development of optical enzyme sensor arrays.

Superoxide poisons mononuclear iron enzymes by causing mismetallation

PubMed Central

Gu, Mianzhi; Imlay, James A.

2013-01-01

Summary Superoxide (O2−) is a primary agent of intracellular oxidative stress. Genetic studies in many organisms have confirmed that excess O2− disrupts metabolism, but to date only a small family of [4Fe-4S] dehydratases have been identified as direct targets. This investigation reveals that in Escherichia coli O2− also poisons a broader cohort of non-redox enzymes that employ ferrous iron atoms as catalytic cofactors. These enzymes were inactivated by O2− both in vitro and in vivo. Although the enzymes are known targets of hydrogen peroxide, the outcome with O2− differs substantially. When purified enzymes were damaged by O2− in vitro, activity could be completely restored by iron addition, indicating that the O2− treatment generated an apoprotein without damaging the protein polypeptide. Superoxide stress inside cells caused the progressive mismetallation of these enzymes with zinc, which confers little activity. When O2− stress was terminated, cells gradually restored activity by extracting zinc from the proteins. The overloading of cells with zinc caused mismetallation even without O2− stress. These results support a model in which O2− repeatedly excises iron from these enzymes, allowing zinc to compete with iron for remetallation of their apoprotein forms. This action substantially expands the physiological imprint of O2− stress. PMID:23678969

Heme-containing enzymes and inhibitors for tryptophan metabolism.

PubMed

Yan, Daojing; Lin, Ying-Wu; Tan, Xiangshi

2017-09-20

Iron-containing enzymes such as heme enzymes play crucial roles in biological systems. Three distinct heme-containing dioxygenase enzymes, tryptophan 2,3-dioxygenase (TDO), indoleamine 2,3-dioxygenase 1 (IDO1) and indoleamine 2,3-dioxygenase 2 (IDO2) catalyze the initial and rate-limiting step of l-tryptophan catabolism through the kynurenine pathway in mammals. Overexpression of these enzymes causes depletion of tryptophan and the accumulation of metabolic products, which contributes to tumor immune tolerance and immune dysregulation in a variety of disease pathologies. In the past few decades, IDO1 has garnered the most attention as a therapeutic target with great potential in cancer immunotherapy. Many potential inhibitors of IDO1 have been designed, synthesized and evaluated, among which indoximod (d-1-MT), INCB024360, GDC-0919 (formerly NLG-919), and an IDO1 peptide-based vaccine have advanced to the clinical trial stage. However, recently, the roles of TDO and IDO2 have been elucidated in immune suppression. In this review, the current drug discovery landscape for targeting TDO, IDO1 and IDO2 is highlighted, with particular attention to the recent use of drugs in clinical trials. Moreover, the crystal structures of these enzymes, in complex with inhibitors, and the mechanisms of Trp catabolism in the first step, are summarized to provide information for facilitating the discovery of new enzyme inhibitors.