A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

Science.gov (United States)

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

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Qi Huang

2017-06-01

Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

Science.gov (United States)

Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

2017-12-01

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.

Adaptive Self-Occlusion Behavior Recognition Based on pLSA

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Hong-bin Tu

2013-01-01

Full Text Available Human action recognition is an important area of human action recognition research. Focusing on the problem of self-occlusion in the field of human action recognition, a new adaptive occlusion state behavior recognition approach was presented based on Markov random field and probabilistic Latent Semantic Analysis (pLSA. Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms an occlusion state variable by phase space obtained. Then, we proposed a hierarchical area variety model. Finally, we use the topic model of pLSA to recognize the human behavior. Experiments were performed on the KTH, Weizmann, and Humaneva dataset to test and evaluate the proposed method. The compared experiment results showed that what the proposed method can achieve was more effective than the compared methods.

Cluster-Based Adaptation Using Density Forest for HMM Phone Recognition

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

2014-01-01

The dissimilarity between the training and test data in speech recognition systems is known to have a considerable effect on the recognition accuracy. To solve this problem, we use density forest to cluster the data and use maximum a posteriori (MAP) method to build a cluster-based adapted Gaussian...... mixture models (GMMs) in HMM speech recognition. Specifically, a set of bagged versions of the training data for each state in the HMM is generated, and each of these versions is used to generate one GMM and one tree in the density forest. Thereafter, an acoustic model forest is built by replacing...... the data of each leaf (cluster) in each tree with the corresponding GMM adapted by the leaf data using the MAP method. The results show that the proposed approach achieves 3:8% (absolute) lower phone error rate compared with the standard HMM/GMM and 0:8% (absolute) lower PER compared with bagged HMM/GMM....

A five-amino-acid motif in the undefined region of the TLR8 ectodomain is required for species-specific ligand recognition.

Science.gov (United States)

Liu, Jin; Xu, Congfeng; Hsu, Li-Chung; Luo, Yunping; Xiang, Rong; Chuang, Tsung-Hsien

2010-02-01

Toll-like receptors play important roles in regulating immunity against microbial infections. Toll-like receptor 8 (TLR8) belongs to a subfamily comprising TLR7, TLR8 and TLR9. Human TLR8 mediates anti-viral immunity by recognizing ssRNA viruses, and triggers potent anti-viral and antitumor immune responses upon ligation by synthetic small molecular weight ligands. Interestingly, distinct from human TLR8, mouse TLR8 was not responsive to ligand stimulation in the absence of polyT-oligodeoxynucleotides (polyT-ODN). The molecular basis for this distinct ligand recognition is still unclear. In the present study, we compared the activation of TLR8 from different species including mouse, rat, human, bovine, porcine, horse, sheep, and cat by ligand ligations. Only the TLR8s from the rodent species (i.e., mouse and rat TLR8s) failed to respond to ligand stimulation in the absence of polyT-ODN. Multiple sequence alignment analysis suggested that these two rodent TLR8s lack a five-amino-acid motif that is conserved in the non-rodent species with varied sequence. This small motif is located in an undefined region of the hTLR8 ectodomain, immediately following LRR-14. Deletion mutation analysis suggested that this motif is essential for the species-specific ligand recognition of hTLR8, whereas it is not required for self-dimerization and intracellular localization of this receptor. (c) 2009 Elsevier Ltd. All rights reserved.

AN ILLUMINATION INVARIANT FACE RECOGNITION BY ENHANCED CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION

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A. Thamizharasi

2016-05-01

Full Text Available Face recognition system is gaining more importance in social networks and surveillance. The face recognition task is complex due to the variations in illumination, expression, occlusion, aging and pose. The illumination variations in image are due to changes in lighting conditions, poor illumination, low contrast or increased brightness. The variations in illumination adversely affect the quality of image and recognition accuracy. The illumination variations in face image have to be pre-processed prior to face recognition. The Contrast Limited Adaptive Histogram Equalization (CLAHE is an image enhancement technique popular in enhancing medical images. The proposed work is to create illumination invariant face recognition system by enhancing Contrast Limited Adaptive Histogram Equalization technique. This method is termed as “Enhanced CLAHE”. The efficiency of Enhanced CLAHE is tested using Fuzzy K Nearest Neighbour classifier and fisher face subspace projection method. The face recognition accuracy percentage rate, Equal Error Rate and False Acceptance Rate at 1% are calculated. The performance of CLAHE and Enhanced CLAHE methods is compared. The efficiency of the Enhanced CLAHE method is tested with three public face databases AR, Yale and ORL. The Enhanced CLAHE has very high recognition accuracy percentage rate when compared to CLAHE.

Investigation of ‘Head-to-Tail’-Connected Oligoaryl N,O-Ligands as Recognition Motifs for Cancer-Relevant G-Quadruplexes

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Natalia Rizeq

2017-12-01

Full Text Available Oligomeric compounds, constituted of consecutive N,O-heteroaromatic rings, introduce useful and tunable properties as alternative ligands for biomolecular recognition. In this study, we have explored a synthetic scheme relying on Van Leusen oxazole formation, in conjunction with C–H activation of the formed oxazoles and their subsequent C–C cross-coupling to 2-bromopyridines in order to assemble a library of variable-length, ‘head-to-tail’-connected, pyridyl-oxazole ligands. Through investigation of the interaction of the three longer ligands (5-mer, 6-mer, 7-mer with cancer-relevant G-quadruplex structures (human telomeric/22AG and c-Myc oncogene promoter/Myc2345-Pu22, the asymmetric pyridyl-oxazole motif has been demonstrated to be a prominent recognition element for G-quadruplexes. Fluorescence titrations reveal excellent binding affinities of the 7-mer and 6-mer for a Na+-induced antiparallel 22AG G-quadruplex (KD = 0.6 × 10−7 M−1 and 0.8 × 10−7 M−1, respectively, and satisfactory (albeit lower affinities for the 22AG/K+ and Myc2345-Pu22/K+ G-quadruplexes. All ligands tested exhibit substantial selectivity for G-quadruplex versus duplex (ds26 DNA, as evidenced by competitive Förster resonance energy transfer (FRET melting assays. Additionally, the 7-mer and 6-mer are capable of promoting a sharp morphology transition of 22AG/K+ G-quadruplex.

Interrogating the Molecular Basis for Substrate Recognition in Serotonin and Dopamine Transporters with High-Affinity Substrate-Based Bivalent Ligands

DEFF Research Database (Denmark)

Andersen, Jacob; Ladefoged, Lucy Kate; Kristensen, Trine N. Bjerre

2016-01-01

insight into substrate recognition in SERT and DAT. An optimized bivalent ligand comprising two serotonin moieties binds SERT with 3,800-fold increased affinity compared to that of serotonin, suggesting that the human transporters have two distinct substrate binding sites. We show that the bivalent...... ligands are inhibitors of SERT and an experimentally validated docking model suggests that the bivalent compounds bind with one substrate moiety in the central binding site (the S1 site), whereas the other substrate moiety binds in a distinct binding site (the S2 site). A systematic study of nonconserved...

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

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Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

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He-Yuan Lin

2008-03-01

Full Text Available A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

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Li Hsin-Te

2008-01-01

Full Text Available Abstract A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

ADAPTIVE CONTEXT PROCESSING IN ON-LINE HANDWRITTEN CHARACTER RECOGNITION

NARCIS (Netherlands)

Iwayama, N.; Ishigaki, K.

2004-01-01

We propose a new approach to context processing in on-line handwritten character recognition (OLCR). Based on the observation that writers often repeat the strings that they input, we take the approach of adaptive context processing. (ACP). In ACP, the strings input by a writer are automatically

Action recognition and movement direction discrimination tasks are associated with different adaptation patterns

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Stephan eDe La Rosa

2016-02-01

Full Text Available The ability to discriminate between different actions is essential for action recognition and social interaction. Surprisingly previous research has often probed action recognition mechanisms with tasks that did not require participants to discriminate between actions, e.g. left-right direction discrimination tasks. It is not known to what degree visual processes in direction discrimination tasks are also involved in the discrimination of actions, e.g. when telling apart a handshake from a high-five. Here, we examined whether action discrimination is influenced by movement direction and whether direction discrimination depends on the type of action. We used an action adaptation paradigm to target action and direction discrimination specific visual processes. In separate conditions participants visually adapted to forward and backward moving handshake and high-five actions. Participants subsequently either categorized the action or the movement direction of an ambiguous action. The results showed that direction discrimination adaptation effects were modulated by the type of action but action discrimination adaptation effects were unaffected by movement direction. These results suggest that action discrimination and direction categorization rely on partly different visual information. We propose that action discrimination tasks should be considered for the exploration of visual action recognition mechanisms.

Selectivity in ligand recognition of G-quadruplex loops.

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Campbell, Nancy H; Patel, Manisha; Tofa, Amina B; Ghosh, Ragina; Parkinson, Gary N; Neidle, Stephen

2009-03-03

A series of disubstituted acridine ligands have been cocrystallized with a bimolecular DNA G-quadruplex. The ligands have a range of cyclic amino end groups of varying size. The crystal structures show that the diagonal loop in this quadruplex results in a large cavity for these groups, in contrast to the steric constraints imposed by propeller loops in human telomeric quadruplexes. We conclude that the nature of the loop has a significant influence on ligand selectivity for particular quadruplex folds.

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human–Robot Interaction

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Juan M. Gandarias

2018-02-01

Full Text Available The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM. Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more, with a lower mean of pressure values (up to 72% less than when using a rigid sensor, with a softer grip, which is needed in physical human–robot interaction (pHRI. A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78% with a rigid sensor.

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

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Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

2018-02-26

The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

Endogenous ligands for C-type lectin receptors: the true regulators of immune homeostasis.

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García-Vallejo, Juan J; van Kooyk, Yvette

2009-07-01

C-type lectin receptors (CLRs) have long been known as pattern-recognition receptors implicated in the recognition of pathogens by the innate immune system. However, evidence is accumulating that many CLRs are also able to recognize endogenous 'self' ligands and that this recognition event often plays an important role in immune homeostasis. In the present review, we focus on the human and mouse CLRs for which endogenous ligands have been described. Special attention is given to the signaling events initiated upon recognition of the self ligand and the regulation of glycosylation as a switch modulating CLR recognition, and therefore, immune homeostasis.

Crystal structure of LGR4-Rspo1 complex: insights into the divergent mechanisms of ligand recognition by leucine-rich repeat G-protein-coupled receptors (LGRs).

Science.gov (United States)

Xu, Jin-Gen; Huang, Chunfeng; Yang, Zhengfeng; Jin, Mengmeng; Fu, Panhan; Zhang, Ni; Luo, Jian; Li, Dali; Liu, Mingyao; Zhou, Yan; Zhu, Yongqun

2015-01-23

Leucine-rich repeat G-protein-coupled receptors (LGRs) are a unique class of G-protein-coupled receptors characterized by a large extracellular domain to recognize ligands and regulate many important developmental processes. Among the three groups of LGRs, group B members (LGR4-6) recognize R-spondin family proteins (Rspo1-4) to stimulate Wnt signaling. In this study, we successfully utilized the "hybrid leucine-rich repeat technique," which fused LGR4 with the hagfish VLR protein, to obtain two recombinant human LGR4 proteins, LGR415 and LGR49. We determined the crystal structures of ligand-free LGR415 and the LGR49-Rspo1 complex. LGR4 exhibits a twisted horseshoe-like structure. Rspo1 adopts a flat and β-fold architecture and is bound in the concave surface of LGR4 in the complex through electrostatic and hydrophobic interactions. All the Rspo1-binding residues are conserved in LGR4-6, suggesting that LGR4-6 bind R-spondins through an identical surface. Structural analysis of our LGR4-Rspo1 complex with the previously determined LGR4 and LGR5 structures revealed that the concave surface of LGR4 is the sole binding site for R-spondins, suggesting a one-site binding model of LGR4-6 in ligand recognition. The molecular mechanism of LGR4-6 is distinct from the two-step mechanism of group A receptors LGR1-3 and the multiple-interface binding model of group C receptors LGR7-8, suggesting LGRs utilize the divergent mechanisms for ligand recognition. Our structures, together with previous reports, provide a comprehensive understanding of the ligand recognition by LGRs. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Supervised and Unsupervised Speaker Adaptation in the NIST 2005 Speaker Recognition Evaluation

National Research Council Canada - National Science Library

Hansen, Eric G; Slyh, Raymond E; Anderson, Timothy R

2006-01-01

Starting in 2004, the annual NIST Speaker Recognition Evaluation (SRE) has added an optional unsupervised speaker adaptation track where test files are processed sequentially and one may update the target model...

An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition

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Ming Liu

2017-09-01

Full Text Available Algorithms for locomotion mode recognition (LMR based on surface electromyography and mechanical sensors have recently been developed and could be used for the neural control of powered prosthetic legs. However, the variations in input signals, caused by physical changes at the sensor interface and human physiological changes, may threaten the reliability of these algorithms. This study aimed to investigate the effectiveness of applying adaptive pattern classifiers for LMR. Three adaptive classifiers, i.e., entropy-based adaptation (EBA, LearnIng From Testing data (LIFT, and Transductive Support Vector Machine (TSVM, were compared and offline evaluated using data collected from two able-bodied subjects and one transfemoral amputee. The offline analysis indicated that the adaptive classifier could effectively maintain or restore the performance of the LMR algorithm when gradual signal variations occurred. EBA and LIFT were recommended because of their better performance and higher computational efficiency. Finally, the EBA was implemented for real-time human-in-the-loop prosthesis control. The online evaluation showed that the applied EBA effectively adapted to changes in input signals across sessions and yielded more reliable prosthesis control over time, compared with the LMR without adaptation. The developed novel adaptive strategy may further enhance the reliability of neurally-controlled prosthetic legs.

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

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Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

THERMODYNAMICS OF PROTEIN-LIGAND INTERACTIONS AND THEIR ANALYSIS

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Rummi Devi Saini

2017-11-01

Full Text Available Physiological processes are controlled mainly by intermolecular recognition mechanisms which involve protein–protein and protein–ligand interactions with a high specificity and affinity to form a specific complex. Proteins being an important class of macromolecules in biological systems, it is important to understand their actions through binding to other molecules of proteins or ligands. In fact, the binding of low molecular weight ligands to proteins plays a significant role in regulating biological processes such as cellular metabolism and signal transmission. Therefore knowledge of the protein–ligand interactions and the knowledge of the mechanisms involved in the protein-ligand recognition and binding are key in understanding biology at molecular level which will facilitate the discovery, design, and development of drugs. In this review, the mechanisms involved in protein–ligand binding, the binding kinetics, thermodynamic concepts and binding driving forces are discussed. Thermodynamic mechanisms involved in a few important protein-ligand binding are described. Various spectroscopic, non-spectroscopic and computational method for analysis of protein–ligand binding are also discussed.

Action adaptation during natural unfolding social scenes influences action recognition and inferences made about actor beliefs.

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Keefe, Bruce D; Wincenciak, Joanna; Jellema, Tjeerd; Ward, James W; Barraclough, Nick E

2016-07-01

When observing another individual's actions, we can both recognize their actions and infer their beliefs concerning the physical and social environment. The extent to which visual adaptation influences action recognition and conceptually later stages of processing involved in deriving the belief state of the actor remains unknown. To explore this we used virtual reality (life-size photorealistic actors presented in stereoscopic three dimensions) to see how visual adaptation influences the perception of individuals in naturally unfolding social scenes at increasingly higher levels of action understanding. We presented scenes in which one actor picked up boxes (of varying number and weight), after which a second actor picked up a single box. Adaptation to the first actor's behavior systematically changed perception of the second actor. Aftereffects increased with the duration of the first actor's behavior, declined exponentially over time, and were independent of view direction. Inferences about the second actor's expectation of box weight were also distorted by adaptation to the first actor. Distortions in action recognition and actor expectations did not, however, extend across different actions, indicating that adaptation is not acting at an action-independent abstract level but rather at an action-dependent level. We conclude that although adaptation influences more complex inferences about belief states of individuals, this is likely to be a result of adaptation at an earlier action recognition stage rather than adaptation operating at a higher, more abstract level in mentalizing or simulation systems.

Individual differences in adaptive coding of face identity are linked to individual differences in face recognition ability.

Science.gov (United States)

Rhodes, Gillian; Jeffery, Linda; Taylor, Libby; Hayward, William G; Ewing, Louise

2014-06-01

Despite their similarity as visual patterns, we can discriminate and recognize many thousands of faces. This expertise has been linked to 2 coding mechanisms: holistic integration of information across the face and adaptive coding of face identity using norms tuned by experience. Recently, individual differences in face recognition ability have been discovered and linked to differences in holistic coding. Here we show that they are also linked to individual differences in adaptive coding of face identity, measured using face identity aftereffects. Identity aftereffects correlated significantly with several measures of face-selective recognition ability. They also correlated marginally with own-race face recognition ability, suggesting a role for adaptive coding in the well-known other-race effect. More generally, these results highlight the important functional role of adaptive face-coding mechanisms in face expertise, taking us beyond the traditional focus on holistic coding mechanisms. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Audiovisual cues benefit recognition of accented speech in noise but not perceptual adaptation.

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Banks, Briony; Gowen, Emma; Munro, Kevin J; Adank, Patti

2015-01-01

Perceptual adaptation allows humans to recognize different varieties of accented speech. We investigated whether perceptual adaptation to accented speech is facilitated if listeners can see a speaker's facial and mouth movements. In Study 1, participants listened to sentences in a novel accent and underwent a period of training with audiovisual or audio-only speech cues, presented in quiet or in background noise. A control group also underwent training with visual-only (speech-reading) cues. We observed no significant difference in perceptual adaptation between any of the groups. To address a number of remaining questions, we carried out a second study using a different accent, speaker and experimental design, in which participants listened to sentences in a non-native (Japanese) accent with audiovisual or audio-only cues, without separate training. Participants' eye gaze was recorded to verify that they looked at the speaker's face during audiovisual trials. Recognition accuracy was significantly better for audiovisual than for audio-only stimuli; however, no statistical difference in perceptual adaptation was observed between the two modalities. Furthermore, Bayesian analysis suggested that the data supported the null hypothesis. Our results suggest that although the availability of visual speech cues may be immediately beneficial for recognition of unfamiliar accented speech in noise, it does not improve perceptual adaptation.

Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

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Suzuki Motoyuki

2009-01-01

Full Text Available Abstract We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the "query relevance." Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

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Akinori Ito

2009-01-01

Full Text Available We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the “query relevance.” Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

Molecular recognition in a diverse set of protein-ligand interactions studied with molecular dynamics simulations and end-point free energy calculations.

Science.gov (United States)

Wang, Bo; Li, Liwei; Hurley, Thomas D; Meroueh, Samy O

2013-10-28

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein-ligand interactions. The binding free energy can be used to rank-order protein-ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal·mol(-1) highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman ρ of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (ρ = 0.91 for ε = 10), but larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the nonpolar and entropy components, rather than a better representation of the electrostatics. The SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 0.81). Calculations of the configurational entropy using normal-mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo, and ligand (MM-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by prescoring

FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

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T. Pasupathi

2014-05-01

Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

HMM Adaptation for Improving a Human Activity Recognition System

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Rubén San-Segundo

2016-09-01

Full Text Available When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs. This system segments and recognizes six different physical activities (walking, walking upstairs, walking downstairs, sitting, standing and lying down using inertial signals from a smartphone. The system is composed of a feature extractor for obtaining the most relevant characteristics from the inertial signals, a module for training the six HMMs (one per activity, and the last module for segmenting new activity sequences using these models. The user adaptation technique consists of a Maximum A Posteriori (MAP approach that adapts the activity HMMs to the user, using some activity examples from this specific user. The main results on a public dataset have reported a significant relative error rate reduction of more than 30%. In conclusion, adapting a HAR system to the user who is performing the physical activities provides significant improvement in the system’s performance.

Evolution of Recognition of Ligands from Gram-Positive Bacteria: Similarities and Differences in the TLR2-Mediated Response between Mammalian Vertebrates and Teleost Fish

NARCIS (Netherlands)

Ribeiro, Carla M. S.; Hermsen, Trudi; Taverne-Thiele, Anja J.; Savelkoul, Huub F. J.; Wiegertjes, Geert F.

2010-01-01

We investigated the role of the TLR2 receptor in the recognition of ligands from Gram-positive bacteria in fish. Comparative sequence analysis showed a highly conserved Toll/IL-1 receptor domain. Although the leucine-rich repeat domain was less conserved, the position of the critical peptidoglycan

The development of adaptive decision making: Recognition-based inference in children and adolescents.

Science.gov (United States)

Horn, Sebastian S; Ruggeri, Azzurra; Pachur, Thorsten

2016-09-01

Judgments about objects in the world are often based on probabilistic information (or cues). A frugal judgment strategy that utilizes memory (i.e., the ability to discriminate between known and unknown objects) as a cue for inference is the recognition heuristic (RH). The usefulness of the RH depends on the structure of the environment, particularly the predictive power (validity) of recognition. Little is known about developmental differences in use of the RH. In this study, the authors examined (a) to what extent children and adolescents recruit the RH when making judgments, and (b) around what age adaptive use of the RH emerges. Primary schoolchildren (M = 9 years), younger adolescents (M = 12 years), and older adolescents (M = 17 years) made comparative judgments in task environments with either high or low recognition validity. Reliance on the RH was measured with a hierarchical multinomial model. Results indicated that primary schoolchildren already made systematic use of the RH. However, only older adolescents adaptively adjusted their strategy use between environments and were better able to discriminate between situations in which the RH led to correct versus incorrect inferences. These findings suggest that the use of simple heuristics does not progress unidirectionally across development but strongly depends on the task environment, in line with the perspective of ecological rationality. Moreover, adaptive heuristic inference seems to require experience and a developed base of domain knowledge. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors

Science.gov (United States)

Gunasekaran, Prasad; Grandison, Scott; Cowtan, Kevin; Mak, Lora; Lawson, David M.; Morris, Richard J.

We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. These descriptors can be compared highly efficiently against large databases of descriptors computed from other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study on a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30 % of the cases, within the top five in a further 30 % of the cases, and giving rise to an 80 % probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.

A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

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Shizhen Zhao

2018-06-01

Full Text Available Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great extent by varying users. This means that the performance of an activity recognition classifier trained by one user’s dataset will degenerate when transferred to others. In this study, we focus on building a personalized classifier to detect four categories of human activities: light intensity activity, moderate intensity activity, vigorous intensity activity, and fall. In order to solve the problem caused by different distributions of inertial sensor signals, a user-adaptive algorithm based on K-Means clustering, local outlier factor (LOF, and multivariate Gaussian distribution (MGD is proposed. To automatically cluster and annotate a specific user’s activity data, an improved K-Means algorithm with a novel initialization method is designed. By quantifying the samples’ informative degree in a labeled individual dataset, the most profitable samples can be selected for activity recognition model adaption. Through experiments, we conclude that our proposed models can adapt to new users with good recognition performance.

Autistic traits are linked to reduced adaptive coding of face identity and selectively poorer face recognition in men but not women.

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Rhodes, Gillian; Jeffery, Linda; Taylor, Libby; Ewing, Louise

2013-11-01

Our ability to discriminate and recognize thousands of faces despite their similarity as visual patterns relies on adaptive, norm-based, coding mechanisms that are continuously updated by experience. Reduced adaptive coding of face identity has been proposed as a neurocognitive endophenotype for autism, because it is found in autism and in relatives of individuals with autism. Autistic traits can also extend continuously into the general population, raising the possibility that reduced adaptive coding of face identity may be more generally associated with autistic traits. In the present study, we investigated whether adaptive coding of face identity decreases as autistic traits increase in an undergraduate population. Adaptive coding was measured using face identity aftereffects, and autistic traits were measured using the Autism-Spectrum Quotient (AQ) and its subscales. We also measured face and car recognition ability to determine whether autistic traits are selectively related to face recognition difficulties. We found that men who scored higher on levels of autistic traits related to social interaction had reduced adaptive coding of face identity. This result is consistent with the idea that atypical adaptive face-coding mechanisms are an endophenotype for autism. Autistic traits were also linked with face-selective recognition difficulties in men. However, there were some unexpected sex differences. In women, autistic traits were linked positively, rather than negatively, with adaptive coding of identity, and were unrelated to face-selective recognition difficulties. These sex differences indicate that autistic traits can have different neurocognitive correlates in men and women and raise the intriguing possibility that endophenotypes of autism can differ in males and females. © 2013 Elsevier Ltd. All rights reserved.

Nanoparticle-based receptors mimic protein-ligand recognition

OpenAIRE

Riccardi, Laura; Gabrielli, Luca; Sun, Xiaohuan; Biasi, Federico De; Rastrelli, Federico; Mancin, Fabrizio; De Vivo, Marco

2017-01-01

Summary The self-assembly of a monolayer of ligands on the surface of noble-metal nanoparticles dictates the fundamental nanoparticle's behavior and its functionality. In this combined computational-experimental study, we analyze the structure, organization, and dynamics of functionalized coating thiols in monolayer-protected gold nanoparticles (AuNPs). We explain how functionalized coating thiols self-organize through a delicate and somehow counterintuitive balance of interactions within the...

A new crystal form of human tear lipocalin reveals high flexibility in the loop region and induced fit in the ligand cavity

International Nuclear Information System (INIS)

Breustedt, Daniel A.; Chatwell, Lorenz; Skerra, Arne

2009-01-01

The crystal structure of tear lipocalin determined in space group P2 1 revealed large structural deviations from the previously solved X-ray structure in space group C2, especially in the loop region and adjoining parts of the β-barrel which give rise to the ligand-binding site. These findings illustrate a novel mechanism for promiscuity in ligand recognition by the lipocalin protein family. Tear lipocalin (TLC) with the bound artificial ligand 1,4-butanediol has been crystallized in space group P2 1 with four protein molecules in the asymmetric unit and its X-ray structure has been solved at 2.6 Å resolution. TLC is a member of the lipocalin family that binds ligands with diverse chemical structures, such as fatty acids, phospholipids and cholesterol as well as microbial siderophores and the antibiotic rifampin. Previous X-ray structural analysis of apo TLC crystallized in space group C2 revealed a rather large bifurcated ligand pocket and a partially disordered loop region at the entrace to the cavity. Analysis of the P2 1 crystal form uncovered major conformational changes (i) in β-strands B, C and D, (ii) in loops 1, 2 and 4 at the open end of the β-barrel and (iii) in the extended C-terminal segment, which is attached to the β-barrel via a disulfide bridge. The structural comparison indicates high conformational plasticity of the loop region as well as of deeper parts of the ligand pocket, thus allowing adaptation to ligands that differ vastly in size and shape. This illustrates a mechanism for promiscuity in ligand recognition which may also be relevant for some other physiologically important members of the lipocalin protein family

Peptide–polymer ligands for a tandem WW-domain, an adaptive multivalent protein–protein interaction: lessons on the thermodynamic fitness of flexible ligands

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Katharina Koschek

2015-05-01

Full Text Available Three polymers, poly(N-(2-hydroxypropylmethacrylamide (pHPMA, hyperbranched polyglycerol (hPG, and dextran were investigated as carriers for multivalent ligands targeting the adaptive tandem WW-domain of formin-binding protein (FBP21. Polymer carriers were conjugated with 3–9 copies of the proline-rich decapeptide GPPPRGPPPR-NH2 (P1. Binding of the obtained peptide–polymer conjugates to the tandem WW-domain was investigated employing isothermal titration calorimetry (ITC to determine the binding affinity, the enthalpic and entropic contributions to free binding energy, and the stoichiometry of binding for all peptide–polymer conjugates. Binding affinities of all multivalent ligands were in the µM range, strongly amplified compared to the monovalent ligand P1 with a KD > 1 mM. In addition, concise differences were observed, pHPMA and hPG carriers showed moderate affinity and bound 2.3–2.8 peptides per protein binding site resulting in the formation of aggregates. Dextran-based conjugates displayed affinities down to 1.2 µM, forming complexes with low stoichiometry, and no precipitation. Experimental results were compared with parameters obtained from molecular dynamics simulations in order to understand the observed differences between the three carrier materials. In summary, the more rigid and condensed peptide–polymer conjugates based on the dextran scaffold seem to be superior to induce multivalent binding and to increase affinity, while the more flexible and dendritic polymers, pHPMA and hPG are suitable to induce crosslinking upon binding.

Distance Adaptive Tensor Discriminative Geometry Preserving Projection for Face Recognition

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Ziqiang Wang

2012-09-01

Full Text Available There is a growing interest in dimensionality reduction techniques for face recognition, however, the traditional dimensionality reduction algorithms often transform the input face image data into vectors before embedding. Such vectorization often ignores the underlying data structure and leads to higher computational complexity. To effectively cope with these problems, a novel dimensionality reduction algorithm termed distance adaptive tensor discriminative geometry preserving projection (DATDGPP is proposed in this paper. The key idea of DATDGPP is as follows: first, the face image data are directly encoded in high-order tensor structure so that the relationships among the face image data can be preserved; second, the data-adaptive tensor distance is adopted to model the correlation among different coordinates of tensor data; third, the transformation matrix which can preserve discrimination and local geometry information is obtained by an iteration algorithm. Experimental results on three face databases show that the proposed algorithm outperforms other representative dimensionality reduction algorithms.

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

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Stéphanie Pérot

Full Text Available Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

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Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket

Low-resolution expression recognition based on central oblique average CS-LBP with adaptive threshold

Science.gov (United States)

Han, Sheng; Xi, Shi-qiong; Geng, Wei-dong

2017-11-01

In order to solve the problem of low recognition rate of traditional feature extraction operators under low-resolution images, a novel algorithm of expression recognition is proposed, named central oblique average center-symmetric local binary pattern (CS-LBP) with adaptive threshold (ATCS-LBP). Firstly, the features of face images can be extracted by the proposed operator after pretreatment. Secondly, the obtained feature image is divided into blocks. Thirdly, the histogram of each block is computed independently and all histograms can be connected serially to create a final feature vector. Finally, expression classification is achieved by using support vector machine (SVM) classifier. Experimental results on Japanese female facial expression (JAFFE) database show that the proposed algorithm can achieve a recognition rate of 81.9% when the resolution is as low as 16×16, which is much better than that of the traditional feature extraction operators.

PANP is a novel O-glycosylated PILR{alpha} ligand expressed in neural tissues

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Kogure, Amane [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); Shiratori, Ikuo [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Wang, Jing [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); Lanier, Lewis L. [Department of Microbiology and Immunology and the Cancer Research Institute, University of California San Francisco, San Francisco, CA 94143 (United States); Arase, Hisashi, E-mail: arase@biken.osaka-u.ac.jp [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); JST CREST, Saitama 332-0012 (Japan)

2011-02-18

Research highlights: {yields} A Novel molecule, PANP, was identified to be a PILR{alpha} ligand. {yields} Sialylated O-glycan structures on PANP were required for PILR{alpha} recognition. {yields} Transcription of PANP was mainly observed in neural tissues. {yields} PANP seems to be involved in immune regulation as a ligand for PILR{alpha}. -- Abstract: PILR{alpha} is an immune inhibitory receptor possessing an immunoreceptor tyrosine-based inhibitory motif (ITIM) in its cytoplasmic domain enabling it to deliver inhibitory signals. Binding of PILR{alpha} to its ligand CD99 is involved in immune regulation; however, whether there are other PILR{alpha} ligands in addition to CD99 is not known. Here, we report that a novel molecule, PILR-associating neural protein (PANP), acts as an additional ligand for PILR{alpha}. Transcription of PANP was mainly observed in neural tissues. PILR{alpha}-Ig fusion protein bound cells transfected with PANP and the transfectants stimulated PILR{alpha} reporter cells. Specific O-glycan structures on PANP were found to be required for PILR recognition of this ligand. These results suggest that PANP is involved in immune regulation as a ligand of the PILR{alpha}.

How Mucosal Epithelia Deal with Stress: Role of NKG2D/NKG2D Ligands during Inflammation

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Fabrizio Antonangeli

2017-11-01

Full Text Available Mucosal epithelia encounter both physicochemical and biological stress during their life and have evolved several mechanisms to deal with them, including regulation of immune cell functions. Stressed and damaged cells need to be cleared to control local inflammation and trigger tissue healing. Engagement of the activating NKG2D receptor is one of the most direct mechanisms involved in the recognition of stressed cells by the immune system. Indeed, injured cells promptly express NKG2D ligands that in turn mediate the activation of lymphocytes of both innate and adaptive arms of the immune system. This review focuses on different conditions that are able to modulate NKG2D ligand expression on the epithelia. Special attention is given to the mechanisms of immunosurveillance mediated by natural killer cells, which are finely tuned by NKG2D. Different types of stress, including viral and bacterial infections, chronic inflammation, and cigarette smoke exposure, are discussed as paradigmatic conditions for NKG2D ligand modulation, and the implications for tissue homeostasis are discussed.

Identification of small heat shock protein B8 (HSP22) as a novel TLR4 ligand and potential involvement in the pathogenesis of rheumatoid arthritis.

NARCIS (Netherlands)

Roelofs, M.F.; Boelens, W.C.; Joosten, L.A.B.; Abdollahi-Roodsaz, S.; Geurts, J.; Wunderink, L.U.; Schreurs, B.W.; Berg, W.B. van den; Radstake, T.R.D.J.

2006-01-01

Dendritic cells (DCs) are specialized APCs that can be activated upon pathogen recognition as well as recognition of endogenous ligands, which are released during inflammation and cell stress. The recognition of exogenous and endogenous ligands depends on TLRs, which are abundantly expressed in

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

Science.gov (United States)

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

ADAPTIVE PARAMETER ESTIMATION OF PERSON RECOGNITION MODEL IN A STOCHASTIC HUMAN TRACKING PROCESS

OpenAIRE

W. Nakanishi; T. Fuse; T. Ishikawa

2015-01-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation ...

Dual Recognition of Human Telomeric G-quadruplex by Neomycin-anthraquinone Conjugate

Science.gov (United States)

Ranjan, Nihar; Davis, Erik; Xue, Liang

2013-01-01

The authors report the recognition of a G-quadruplex formed by four repeat human telomeric DNA with aminosugar intercalator conjugates. The recognition of G-quadruplex through dual binding mode ligands significantly increased the affinity of ligands for G-quadruplex. One such example is a neomycin-anthraquinone 2 which exhibited nanomolar affinity for the quadruplex, and the affinity of 2 is nearly 1000 fold higher for human telomeric G-quadruplex DNA than its constituent units, neomycin and anthraquinone. PMID:23698792

Molecular Mechanisms That Underlie the Dynamic Adaptation of Innate Monocyte Memory to Varying Stimulant Strength of TLR Ligands.

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Yuan, Ruoxi; Geng, Shuo; Li, Liwu

2016-01-01

In adaptation to rising stimulant strength, innate monocytes can be dynamically programed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programing may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS), the model stimulant of toll-like-receptor 4 (TLR4), we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor, interferon regulatory factor 5 (IRF5), and reduced levels of transcriptional modulator B lymphocyte-induced maturation protein-1 (Blimp-1). Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

Molecular mechanisms that underlie the dynamic adaptation of innate monocyte memory to varying stimulant strength of TLR ligands

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Ruoxi Yuan

2016-11-01

Full Text Available In adaptation to rising stimulant strength, innate monocytes can be dynamically programmed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programming may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS, the model stimulant of Toll-Like-Receptor 4 (TLR4, we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor IRF5 and reduced levels of transcriptional modulator BLIMP-1. Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

Dynamical Binding Modes Determine Agonistic and Antagonistic Ligand Effects in the Prostate-Specific G-Protein Coupled Receptor (PSGR).

Science.gov (United States)

Wolf, Steffen; Jovancevic, Nikolina; Gelis, Lian; Pietsch, Sebastian; Hatt, Hanns; Gerwert, Klaus

2017-11-22

We analysed the ligand-based activation mechanism of the prostate-specific G-protein coupled receptor (PSGR), which is an olfactory receptor that mediates cellular growth in prostate cancer cells. Furthermore, it is an olfactory receptor with a known chemically near identic antagonist/agonist pair, α- and β-ionone. Using a combined theoretical and experimental approach, we propose that this receptor is activated by a ligand-induced rearrangement of a protein-internal hydrogen bond network. Surprisingly, this rearrangement is not induced by interaction of the ligand with the network, but by dynamic van der Waals contacts of the ligand with the involved amino acid side chains, altering their conformations and intraprotein connectivity. Ligand recognition in this GPCR is therefore highly stereo selective, but seemingly lacks any ligand recognition via polar contacts. A putative olfactory receptor-based drug design scheme will have to take this unique mode of protein/ligand action into account.

C-type lectins: their network and roles in pathogen recognition and immunity.

Science.gov (United States)

Mayer, Sabine; Raulf, Marie-Kristin; Lepenies, Bernd

2017-02-01

C-type lectins (CTLs) represent the most complex family of animal/human lectins that comprises 17 different groups. During evolution, CTLs have developed by diversification to cover a broad range of glycan ligands. However, ligand binding by CTLs is not necessarily restricted to glycans as some CTLs also bind to proteins, lipids, inorganic molecules, or ice crystals. CTLs share a common fold that harbors a Ca 2+ for contact to the sugar and about 18 invariant residues in a phylogenetically conserved pattern. In vertebrates, CTLs have numerous functions, including serum glycoprotein homeostasis, pathogen sensing, and the initiation of immune responses. Myeloid CTLs in innate immunity are mainly expressed by antigen-presenting cells and play a prominent role in the recognition of a variety of pathogens such as fungi, bacteria, viruses, and parasites. However, myeloid CTLs such as the macrophage inducible CTL (Mincle) or Clec-9a may also bind to self-antigens and thus contribute to immune homeostasis. While some CTLs induce pro-inflammatory responses and thereby lead to activation of adaptive immune responses, other CTLs act as inhibitory receptors and dampen cellular functions. Since CTLs are key players in pathogen recognition and innate immunity, targeting CTLs may be a promising strategy for cell-specific delivery of drugs or vaccine antigens and to modulate immune responses.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes.

Science.gov (United States)

Raschka, Sebastian; Wolf, Alex J; Bemister-Buffington, Joseph; Kuhn, Leslie A

2018-04-01

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes

Science.gov (United States)

Raschka, Sebastian; Wolf, Alex J.; Bemister-Buffington, Joseph; Kuhn, Leslie A.

2018-02-01

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Molecular recognition of naphthalene diimide ligands by telomeric quadruplex-DNA: the importance of the protonation state and mediated hydrogen bonds.

Science.gov (United States)

Spinello, A; Barone, G; Grunenberg, J

2016-01-28

In depth Monte Carlo conformational scans in combination with molecular dynamics (MD) simulations and electronic structure calculations were applied in order to study the molecular recognition process between tetrasubstituted naphthalene diimide (ND) guests and G-quadruplex (G4) DNA receptors. ND guests are a promising class of telomere stabilizers due to which they are used in novel anticancer therapeutics. Though several ND guests have been studied experimentally in the past, the protonation state under physiological conditions is still unclear. Based on chemical intuition, in the case of N-methyl-piperazine substitution, different protonation states are possible and might play a crucial role in the molecular recognition process by G4-DNA. Depending on the proton concentration, different nitrogen atoms of the N-methyl-piperazine might (or might not) be protonated. This fact was considered in our simulation in terms of a case by case analysis, since the process of molecular recognition is determined by possible donor or acceptor positions. The results of our simulations show that the electrostatic interactions between the ND ligands and the G4 receptor are maximized in the case of the protonation of the terminal nitrogen atoms, forming compact ND G4 complexes inside the grooves. The influence of different protonation states in terms of the ability to form hydrogen bonds with the sugar-phosphate backbone, as well as the importance of mediated vs. direct hydrogen bonding, was analyzed in detail by MD and relaxed force constant (compliance constant) simulations.

Face Recognition by Bunch Graph Method Using a Group Based Adaptive Tolerant Neural Network

OpenAIRE

Aradhana D.; Girish H.; Karibasappa K.; Reddy A. Chennakeshava

2011-01-01

This paper presents a new method for feature extraction from the facial image by using bunch graph method. These extracted geometric features of the face are used subsequently for face recognition by utilizing the group based adaptive neural network. This method is suitable, when the facial images are rotation and translation invariant. Further the technique also free from size invariance of facial image and is capable of identifying the facial images correctly when corrupted w...

Natural Cytotoxicity Receptors: Pattern Recognition and Involvement of Carbohydrates

Directory of Open Access Journals (Sweden)

Angel Porgador

2005-01-01

Full Text Available Natural cytotoxicity receptors (NCRs, expressed by natural killer (NK cells, trigger NK lysis of tumor and virus-infected cells on interaction with cell-surface ligands of these target cells. We have determined that viral hemagglutinins expressed on the surface of virus-infected cells are involved in the recognition by the NCRs, NKp44 and NKp46. Recognition of tumor cells by the NCRs NKp30 and NKp46 involves heparan sulfate epitopes expressed on the tumor cell membrane. Our studies provide new evidence for the identity of the ligands for NCRs and indicate that a broader definition should be applied to pathological patterns recognized by innate immune receptors. Since nonmicrobial endogenous carbohydrate structures contribute significantly to this recognition, there is an imperative need to develop appropriate tools for the facile sequencing of carbohydrate moieties.

Selecting Informative Features of the Helicopter and Aircraft Acoustic Signals in the Adaptive Autonomous Information Systems for Recognition

Directory of Open Access Journals (Sweden)

V. K. Hohlov

2017-01-01

Full Text Available The article forms the rationale for selecting the informative features of the helicopter and aircraft acoustic signals to solve a problem of their recognition and shows that the most informative ones are the counts of extrema in the energy spectra of the input signals, which represent non-centered random variables. An apparatus of the multiple initial regression coefficients was selected as a mathematical tool of research. The application of digital re-circulators with positive and negative feedbacks, which have the comb-like frequency characteristics, solves the problem of selecting informative features. A distinguishing feature of such an approach is easy agility of the comb frequency characteristics just through the agility of a delay value of digital signal in the feedback circuit. Adding an adaptation block to the selection block of the informative features enables us to ensure the invariance of used informative feature and counts of local extrema of the spectral power density to the airspeed of a helicopter. The paper gives reasons for the principle of adaptation and the structure of the adaptation block. To form the discriminator characteristics are used the cross-correlation statistical characteristics of the quadrature components of acoustic signal realizations, obtained by Hilbert transform. The paper proposes to provide signal recognition using a regression algorithm that allows handling the non-centered informative features and using a priori information about coefficients of initial regression of signal and noise.The simulation in Matlab Simulink has shown that selected informative features of signals in regressive processing of signal realizations of 0.5 s duration have good separability, and based on a set of 100 acoustic signal realizations in each class in full-scale conditions, has proved ensuring a correct recognition probability of 0.975, at least. The considered principles of informative features selection and adaptation can

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

Science.gov (United States)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

Mycobacterium tuberculosis Transfer RNA Induces IL-12p70 via Synergistic Activation of Pattern Recognition Receptors within a Cell Network.

Science.gov (United States)

Keegan, Caroline; Krutzik, Stephan; Schenk, Mirjam; Scumpia, Philip O; Lu, Jing; Pang, Yan Ling Joy; Russell, Brandon S; Lim, Kok Seong; Shell, Scarlet; Prestwich, Erin; Su, Dan; Elashoff, David; Hershberg, Robert M; Bloom, Barry R; Belisle, John T; Fortune, Sarah; Dedon, Peter C; Pellegrini, Matteo; Modlin, Robert L

2018-05-01

Upon recognition of a microbial pathogen, the innate and adaptive immune systems are linked to generate a cell-mediated immune response against the foreign invader. The culture filtrate of Mycobacterium tuberculosis contains ligands, such as M. tuberculosis tRNA, that activate the innate immune response and secreted Ags recognized by T cells to drive adaptive immune responses. In this study, bioinformatics analysis of gene-expression profiles derived from human PBMCs treated with distinct microbial ligands identified a mycobacterial tRNA-induced innate immune network resulting in the robust production of IL-12p70, a cytokine required to instruct an adaptive Th1 response for host defense against intracellular bacteria. As validated by functional studies, this pathway contained a feed-forward loop, whereby the early production of IL-18, type I IFNs, and IL-12p70 primed NK cells to respond to IL-18 and produce IFN-γ, enhancing further production of IL-12p70. Mechanistically, tRNA activates TLR3 and TLR8, and this synergistic induction of IL-12p70 was recapitulated by the addition of a specific TLR8 agonist with a TLR3 ligand to PBMCs. These data indicate that M. tuberculosis tRNA activates a gene network involving the integration of multiple innate signals, including types I and II IFNs, as well as distinct cell types to induce IL-12p70. Copyright © 2018 by The American Association of Immunologists, Inc.

Thermodynamic fingerprints of ligand binding to human telomeric G-quadruplexes

OpenAIRE

Bon?ina, Matja?; Podlipnik, ?rtomir; Piantanida, Ivo; Eilmes, Julita; Teulade-Fichou, Marie-Paule; Vesnaver, Gorazd; Lah, Jurij

2015-01-01

Thermodynamic studies of ligand binding to human telomere (ht) DNA quadruplexes, as a rule, neglect the involvement of various ht-DNA conformations in the binding process. Therefore, the thermodynamic driving forces and the mechanisms of ht-DNA G-quadruplex-ligand recognition remain poorly understood. In this work we characterize thermodynamically and structurally binding of netropsin (Net), dibenzotetraaza[14]annulene derivatives (DP77, DP78), cationic porphyrin (TMPyP4) and two bisquinolini...

Molecular mechanism of ligand recognition by NR3 subtype glutamate receptors

Energy Technology Data Exchange (ETDEWEB)

Yao, Yongneng; Harrison, Chris B.; Freddolino, Peter L.; Schulten, Klaus; Mayer, Mark L. (UIUC); (NIH)

2008-10-27

NR3 subtype glutamate receptors have a unique developmental expression profile, but are the least well-characterized members of the NMDA receptor gene family, which have key roles in synaptic plasticity and brain development. Using ligand binding assays, crystallographic analysis, and all atom MD simulations, we investigate mechanisms underlying the binding by NR3A and NR3B of glycine and D-serine, which are candidate neurotransmitters for NMDA receptors containing NR3 subunits. The ligand binding domains of both NR3 subunits adopt a similar extent of domain closure as found in the corresponding NR1 complexes, but have a unique loop 1 structure distinct from that in all other glutamate receptor ion channels. Within their ligand binding pockets, NR3A and NR3B have strikingly different hydrogen bonding networks and solvent structures from those found in NR1, and fail to undergo a conformational rearrangement observed in NR1 upon binding the partial agonist ACPC. MD simulations revealed numerous interdomain contacts, which stabilize the agonist-bound closed-cleft conformation, and a novel twisting motion for the loop 1 helix that is unique in NR3 subunits.

Enantioselective recognition of an isomeric ligand by a biomolecule: mechanistic insights into static and dynamic enantiomeric behavior and structural flexibility.

Science.gov (United States)

Peng, Wei; Ding, Fei

2017-10-24

Chirality is a ubiquitous basic attribute of nature, which inseparably relates to the life activity of living organisms. However, enantiomeric differences have still failed to arouse enough attention during the biological evaluation and practical application of chiral substances, and this poses a large threat to human health. In the current study, we explore the enantioselective biorecognition of a chiral compound by an asymmetric biomolecule, and then decipher the molecular basis of such a biological phenomenon on the static and, in particular, the dynamic scale. In light of the wet experiments, in silico docking results revealed that the orientation of the latter part of the optical isomer structures in the recognition domain can be greatly affected by the chiral carbon center in a model ligand molecule, and this event may induce large disparities between the static chiral bioreaction modes and noncovalent interactions (especially hydrogen bonding). Dynamic stereoselective biorecognition assays indicated that the conformational stability of the protein-(S)-diclofop system is clearly greater than the protein-(R)-diclofop adduct; and moreover, the conformational alterations of the diclofop enantiomers in the dynamic process will directly influence the conformational flexibility of the key residues found in the biorecognition region. These points enable the changing trends of biopolymer structural flexibility and free energy to exhibit significant distinctions when proteins sterically recognize the (R)-/(S)-stereoisomers. The outcomes of the energy decomposition further showed that the van der Waals' energy has roughly the same contribution to the chiral recognition biosystems, whereas the contribution of electrostatic energy to the protein-(R)-diclofop complex is notably smaller than to the protein-(S)-diclofop bioconjugate. This proves that differences in the noncovalent bonds would have a serious impact on the stereoselective biorecognition between a

Characteristic molecular vibrations of adenosine receptor ligands.

Science.gov (United States)

Chee, Hyun Keun; Yang, Jin-San; Joung, Je-Gun; Zhang, Byoung-Tak; Oh, S June

2015-02-13

Although the regulation of membrane receptor activation is known to be crucial for molecular signal transduction, the molecular mechanism underlying receptor activation is not fully elucidated. Here we study the physicochemical nature of membrane receptor behavior by investigating the characteristic molecular vibrations of receptor ligands using computational chemistry and informatics methods. By using information gain, t-tests, and support vector machines, we have identified highly informative features of adenosine receptor (AdoR) ligand and corresponding functional amino acid residues such as Asn (6.55) of AdoR that has informative significance and is indispensable for ligand recognition of AdoRs. These findings may provide new perspectives and insights into the fundamental mechanism of class A G protein-coupled receptor activation. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

General Linker Diversification Approach to Bivalent Ligand Assembly: Generation of an Array of Ligands for the Cation-Independent Mannose 6-Phosphate Receptor.

Science.gov (United States)

Fei, Xiang; Zavorka, Megan E; Malik, Guillaume; Connelly, Christopher M; MacDonald, Richard G; Berkowitz, David B

2017-08-18

A generalized strategy is presented for the rapid assembly of a set of bivalent ligands with a variety of linking functionalities from a common monomer. Herein, an array of phosphatase-inert mannose-6-phosphonate-presenting ligands for the cation-independent-mannose 6-phosphate receptor (CI-MPR) is constructed. Receptor binding affinity varies with linking functionality-the simple amide and 1,5-triazole(tetrazole) being preferred over the 1,4-triazole. This approach is expected to find application across chemical biology, particularly in glycoscience, wherein multivalency often governs molecular recognition.

Analytical developments for screening of lanthanides/ligands interactions

International Nuclear Information System (INIS)

Varenne, F.

2012-01-01

This work investigates the potential of hyphenated capillary electrophoresis and inductively coupled mass spectrometry to classify different ligands according to their europium binding affinity in a hydro-organic medium. On the one hand, this method enables to evaluate the affinity of phosphorus-containing ligands in less than two hours and using less than 15 ng of ligand. On the other hand, complexation constants could be determined. The results are in excellent agreement with the values obtained by spectrophotometric titrations.Moreover, a library of copolymers for solid/liquid extraction of europium is investigated. The extraction protocol enables to classify copolymers according to their europium affinity in a hydro-organic medium. This screening requires 60 mg of copolymers. For the most promising recognition properties and selectivity La 3+ /Eu 3+ /Lu 3+ are evaluated. (author)

Transfer of the human NKG2D ligands UL16 binding proteins (ULBP) 1-3 is related to lytic granule release and leads to ligand retransfer and killing of ULBP-recipient natural killer cells.

Science.gov (United States)

López-Cobo, Sheila; Romera-Cárdenas, Gema; García-Cuesta, Eva M; Reyburn, Hugh T; Valés-Gómez, Mar

2015-09-01

After immune interactions, membrane fragments can be transferred between cells. This fast transfer of molecules is transient and shows selectivity for certain proteins; however, the constraints underlying acquisition of a protein are unknown. To characterize the mechanism and functional consequences of this process in natural killer (NK) cells, we have compared the transfer of different NKG2D ligands. We show that human NKG2D ligands can be acquired by NK cells with different efficiencies. The main findings are that NKG2D ligand transfer is related to immune activation and receptor-ligand interaction and that NK cells acquire these proteins during interactions with target cells that lead to degranulation. Our results further demonstrate that NK cells that have acquired NKG2D ligands can stimulate activation of autologous NK cells. Surprisingly, NK cells can also re-transfer the acquired molecule to autologous effector cells during this immune recognition that leads to their death. These data demonstrate that transfer of molecules occurs as a consequence of immune recognition and imply that this process might play a role in homeostatic tuning-down of the immune response or be used as marker of interaction. © 2015 John Wiley & Sons Ltd.

Incremental Learning for Place Recognition in Dynamic Environments

OpenAIRE

Luo, Jie; Pronobis, Andrzej; Caputo, Barbara; Jensfelt, Patric

2007-01-01

This paper proposes a discriminative approach to template-based Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be adaptive, i.e. should be able to learn from experience and adapt continuously to changes in the environment. This paper presents a discriminative incremental learning approach to place recognition. We use a recently introduced version of the incremental SVM, which ...

Adapted all-numerical correlator for face recognition applications

Science.gov (United States)

Elbouz, M.; Bouzidi, F.; Alfalou, A.; Brosseau, C.; Leonard, I.; Benkelfat, B.-E.

2013-03-01

In this study, we suggest and validate an all-numerical implementation of a VanderLugt correlator which is optimized for face recognition applications. The main goal of this implementation is to take advantage of the benefits (detection, localization, and identification of a target object within a scene) of correlation methods and exploit the reconfigurability of numerical approaches. This technique requires a numerical implementation of the optical Fourier transform. We pay special attention to adapt the correlation filter to this numerical implementation. One main goal of this work is to reduce the size of the filter in order to decrease the memory space required for real time applications. To fulfil this requirement, we code the reference images with 8 bits and study the effect of this coding on the performances of several composite filters (phase-only filter, binary phase-only filter). The saturation effect has for effect to decrease the performances of the correlator for making a decision when filters contain up to nine references. Further, an optimization is proposed based for an optimized segmented composite filter. Based on this approach, we present tests with different faces demonstrating that the above mentioned saturation effect is significantly reduced while minimizing the size of the learning data base.

Entropy in molecular recognition by proteins.

Science.gov (United States)

Caro, José A; Harpole, Kyle W; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G; Sharp, Kim A; Wand, A Joshua

2017-06-20

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein-ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein-ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein-ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or "entropy meter" also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water-protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins.

An automatic system for Turkish word recognition using Discrete Wavelet Neural Network based on adaptive entropy

International Nuclear Information System (INIS)

Avci, E.

2007-01-01

In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of Discrete Wavelet Transform (DWT) and wavelet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the used system is evaluated by using noisy Turkish word signals. Test results showing the effectiveness of the proposed automatic system are presented in this paper. The rate of correct recognition is about 92.5% for the sample speech signals. (author)

Compact Acoustic Models for Embedded Speech Recognition

Directory of Open Access Journals (Sweden)

Lévy Christophe

2009-01-01

Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

Flexible Piezoelectric Sensor-Based Gait Recognition

Directory of Open Access Journals (Sweden)

Youngsu Cha

2018-02-01

Full Text Available Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

Estimation of kinetic and thermodynamic ligand-binding parameters using computational strategies.

Science.gov (United States)

Deganutti, Giuseppe; Moro, Stefano

2017-04-01

Kinetic and thermodynamic ligand-protein binding parameters are gaining growing importance as key information to consider in drug discovery. The determination of the molecular structures, using particularly x-ray and NMR techniques, is crucial for understanding how a ligand recognizes its target in the final binding complex. However, for a better understanding of the recognition processes, experimental studies of ligand-protein interactions are needed. Even though several techniques can be used to investigate both thermodynamic and kinetic profiles for a ligand-protein complex, these procedures are very often laborious, time consuming and expensive. In the last 10 years, computational approaches have enormous potential in providing insights into each of the above effects and in parsing their contributions to the changes in both kinetic and thermodynamic binding parameters. The main purpose of this review is to summarize the state of the art of computational strategies for estimating the kinetic and thermodynamic parameters of a ligand-protein binding.

Evaluation of Speech Recognition of Cochlear Implant Recipients Using Adaptive, Digital Remote Microphone Technology and a Speech Enhancement Sound Processing Algorithm.

Science.gov (United States)

Wolfe, Jace; Morais, Mila; Schafer, Erin; Agrawal, Smita; Koch, Dawn

2015-05-01

Cochlear implant recipients often experience difficulty with understanding speech in the presence of noise. Cochlear implant manufacturers have developed sound processing algorithms designed to improve speech recognition in noise, and research has shown these technologies to be effective. Remote microphone technology utilizing adaptive, digital wireless radio transmission has also been shown to provide significant improvement in speech recognition in noise. There are no studies examining the potential improvement in speech recognition in noise when these two technologies are used simultaneously. The goal of this study was to evaluate the potential benefits and limitations associated with the simultaneous use of a sound processing algorithm designed to improve performance in noise (Advanced Bionics ClearVoice) and a remote microphone system that incorporates adaptive, digital wireless radio transmission (Phonak Roger). A two-by-two way repeated measures design was used to examine performance differences obtained without these technologies compared to the use of each technology separately as well as the simultaneous use of both technologies. Eleven Advanced Bionics (AB) cochlear implant recipients, ages 11 to 68 yr. AzBio sentence recognition was measured in quiet and in the presence of classroom noise ranging in level from 50 to 80 dBA in 5-dB steps. Performance was evaluated in four conditions: (1) No ClearVoice and no Roger, (2) ClearVoice enabled without the use of Roger, (3) ClearVoice disabled with Roger enabled, and (4) simultaneous use of ClearVoice and Roger. Speech recognition in quiet was better than speech recognition in noise for all conditions. Use of ClearVoice and Roger each provided significant improvement in speech recognition in noise. The best performance in noise was obtained with the simultaneous use of ClearVoice and Roger. ClearVoice and Roger technology each improves speech recognition in noise, particularly when used at the same time

Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

Science.gov (United States)

Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

2017-09-01

Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

Reptile Toll-like receptor 5 unveils adaptive evolution of bacterial flagellin recognition.

Science.gov (United States)

Voogdt, Carlos G P; Bouwman, Lieneke I; Kik, Marja J L; Wagenaar, Jaap A; van Putten, Jos P M

2016-01-07

Toll-like receptors (TLR) are ancient innate immune receptors crucial for immune homeostasis and protection against infection. TLRs are present in mammals, birds, amphibians and fish but have not been functionally characterized in reptiles despite the central position of this animal class in vertebrate evolution. Here we report the cloning, characterization, and function of TLR5 of the reptile Anolis carolinensis (Green Anole lizard). The receptor (acTLR5) displays the typical TLR protein architecture with 22 extracellular leucine rich repeats flanked by a N- and C-terminal leucine rich repeat domain, a membrane-spanning region, and an intracellular TIR domain. The receptor is phylogenetically most similar to TLR5 of birds and most distant to fish TLR5. Transcript analysis revealed acTLR5 expression in multiple lizard tissues. Stimulation of acTLR5 with TLR ligands demonstrated unique responsiveness towards bacterial flagellin in both reptile and human cells. Comparison of acTLR5 and human TLR5 using purified flagellins revealed differential sensitivity to Pseudomonas but not Salmonella flagellin, indicating development of species-specific flagellin recognition during the divergent evolution of mammals and reptiles. Our discovery of reptile TLR5 fills the evolutionary gap regarding TLR conservation across vertebrates and provides novel insights in functional evolution of host-microbe interactions.

The CC chemokine receptor 5 regulates olfactory and social recognition in mice.

Science.gov (United States)

Kalkonde, Y V; Shelton, R; Villarreal, M; Sigala, J; Mishra, P K; Ahuja, S S; Barea-Rodriguez, E; Moretti, P; Ahuja, S K

2011-12-01

Chemokines are chemotactic cytokines that regulate cell migration and are thought to play an important role in a broad range of inflammatory diseases. The availability of chemokine receptor blockers makes them an important therapeutic target. In vitro, chemokines are shown to modulate neurotransmission. However, it is not very clear if chemokines play a role in behavior and cognition. Here we evaluated the role of CC chemokine receptor 5 (CCR5) in various behavioral tasks in mice using Wt (Ccr5⁺/⁺) and Ccr5-null (Ccr5⁻/⁻)mice. Ccr5⁻/⁻ mice showed enhanced social recognition. Administration of CC chemokine ligand 3 (CCL3), one of the CCR5-ligands, impaired social recognition. Since the social recognition task is dependent on the sense of olfaction, we tested olfactory recognition for social and non-social scents in these mice. Ccr5⁻/⁻ mice had enhanced olfactory recognition for both these scents indicating that enhanced performance in social recognition task could be due to enhanced olfactory recognition in these mice. Spatial memory and aversive memory were comparable in Wt and Ccr5⁻/⁻ mice. Collectively, these results suggest that chemokines/chemokine receptors might play an important role in olfactory recognition tasks in mice and to our knowledge represents the first direct demonstration of an in vivo role of CCR5 in modulating social behavior in mice. These studies are important as CCR5 blockers are undergoing clinical trials and can potentially modulate behavior. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Simultaneous topography and recognition imaging: physical aspects and optimal imaging conditions

International Nuclear Information System (INIS)

Preiner, Johannes; Ebner, Andreas; Zhu Rong; Hinterdorfer, Peter; Chtcheglova, Lilia

2009-01-01

Simultaneous topography and recognition imaging (TREC) allows for the investigation of receptor distributions on natural biological surfaces under physiological conditions. Based on atomic force microscopy (AFM) in combination with a cantilever tip carrying a ligand molecule, it enables us to sense topography and recognition of receptor molecules simultaneously with nanometre accuracy. In this study we introduce optimized handling conditions and investigate the physical properties of the cantilever-tip-sample ensemble, which is essential for the interpretation of the experimental data gained from this technique. In contrast to conventional AFM methods, TREC is based on a more sophisticated feedback loop, which enables us to discriminate topographical contributions from recognition events in the AFM cantilever motion. The features of this feedback loop were investigated through a detailed analysis of the topography and recognition data obtained on a model protein system. Single avidin molecules immobilized on a mica substrate were imaged with an AFM tip functionalized with a biotinylated IgG. A simple procedure for adjusting the optimal amplitude for TREC imaging is described by exploiting the sharp localization of the TREC signal within a small range of oscillation amplitudes. This procedure can also be used for proving the specificity of the detected receptor-ligand interactions. For understanding and eliminating topographical crosstalk in the recognition images we developed a simple theoretical model, which nicely explains its origin and its dependence on the excitation frequency.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG-Based Emotion Recognition

Directory of Open Access Journals (Sweden)

Xin Chai

2017-05-01

Full Text Available Electroencephalography (EEG-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects. Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE, which

Composite organization of the cobalamin binding and cubilin recognition sites of intrinsic factor

DEFF Research Database (Denmark)

Fedosov, Sergey N; Fedosova, Natalya U; Berglund, Lars

2005-01-01

of the ligand. Each isolated fragment of IF was tested for the binding to the specific receptor cubilin in the presence or absence of Cbl. Neither apo nor holo forms of IF(20) and IF(30) were recognized by the receptor. When two fragments were mixed and incubated with Cbl, they associated into a stable complex......; however, efficient retention of the ligand required the presence of both fragments. Detailed schemes of the interaction of Cbl with IF(50) and with IF(30) and IF(20) are presented, where the sequential attachment of Cbl to the IF(20) and IF(30) domains plays the key role in recognition and retention......, IF(30+20).Cbl, which bound to cubilin as well as the noncleaved IF(50).Cbl complex. We suggest that formation of the cubilin recognition site on IF is caused by assembly of two distant domains, which allows the saturated protein to be recognized by the receptor. The obtained parameters for ligand...

User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control

Science.gov (United States)

He, Jiayuan; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Farina, Dario; Zhu, Xiangyang

2015-08-01

Objective. Recent studies have reported that the classification performance of electromyographic (EMG) signals degrades over time without proper classification retraining. This problem is relevant for the applications of EMG pattern recognition in the control of active prostheses. Approach. In this study we investigated the changes in EMG classification performance over 11 consecutive days in eight able-bodied subjects and two amputees. Main results. It was observed that, when the classifier was trained on data from one day and tested on data from the following day, the classification error decreased exponentially but plateaued after four days for able-bodied subjects and six to nine days for amputees. The between-day performance became gradually closer to the corresponding within-day performance. Significance. These results indicate that the relative changes in EMG signal features over time become progressively smaller when the number of days during which the subjects perform the pre-defined motions are increased. The performance of the motor tasks is thus more consistent over time, resulting in more repeatable EMG patterns, even if the subjects do not have any external feedback on their performance. The learning curves for both able-bodied subjects and subjects with limb deficiencies could be modeled as an exponential function. These results provide important insights into the user adaptation characteristics during practical long-term myoelectric control applications, with implications for the design of an adaptive pattern recognition system.

Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

Science.gov (United States)

Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

2016-09-01

Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Residue preference mapping of ligand fragments in the Protein Data Bank.

Science.gov (United States)

Wang, Lirong; Xie, Zhaojun; Wipf, Peter; Xie, Xiang-Qun

2011-04-25

The interaction between small molecules and proteins is one of the major concerns for structure-based drug design because the principles of protein-ligand interactions and molecular recognition are not thoroughly understood. Fortunately, the analysis of protein-ligand complexes in the Protein Data Bank (PDB) enables unprecedented possibilities for new insights. Herein, we applied molecule-fragmentation algorithms to split the ligands extracted from PDB crystal structures into small fragments. Subsequently, we have developed a ligand fragment and residue preference mapping (LigFrag-RPM) algorithm to map the profiles of the interactions between these fragments and the 20 proteinogenic amino acid residues. A total of 4032 fragments were generated from 71 798 PDB ligands by a ring cleavage (RC) algorithm. Among these ligand fragments, 315 unique fragments were characterized with the corresponding fragment-residue interaction profiles by counting residues close to these fragments. The interaction profiles revealed that these fragments have specific preferences for certain types of residues. The applications of these interaction profiles were also explored and evaluated in case studies, showing great potential for the study of protein-ligand interactions and drug design. Our studies demonstrated that the fragment-residue interaction profiles generated from the PDB ligand fragments can be used to detect whether these fragments are in their favorable or unfavorable environments. The algorithm for a ligand fragment and residue preference mapping (LigFrag-RPM) developed here also has the potential to guide lead chemistry modifications as well as binding residues predictions.

Molecular mechanism of ligand recognition by membrane transport protein, Mhp1

Science.gov (United States)

Simmons, Katie J; Jackson, Scott M; Brueckner, Florian; Patching, Simon G; Beckstein, Oliver; Ivanova, Ekaterina; Geng, Tian; Weyand, Simone; Drew, David; Lanigan, Joseph; Sharples, David J; Sansom, Mark SP; Iwata, So; Fishwick, Colin WG; Johnson, A Peter; Cameron, Alexander D; Henderson, Peter JF

2014-01-01

The hydantoin transporter Mhp1 is a sodium-coupled secondary active transport protein of the nucleobase-cation-symport family and a member of the widespread 5-helix inverted repeat superfamily of transporters. The structure of Mhp1 was previously solved in three different conformations providing insight into the molecular basis of the alternating access mechanism. Here, we elucidate detailed events of substrate binding, through a combination of crystallography, molecular dynamics, site-directed mutagenesis, biochemical/biophysical assays, and the design and synthesis of novel ligands. We show precisely where 5-substituted hydantoin substrates bind in an extended configuration at the interface of the bundle and hash domains. They are recognised through hydrogen bonds to the hydantoin moiety and the complementarity of the 5-substituent for a hydrophobic pocket in the protein. Furthermore, we describe a novel structure of an intermediate state of the protein with the external thin gate locked open by an inhibitor, 5-(2-naphthylmethyl)-L-hydantoin, which becomes a substrate when leucine 363 is changed to an alanine. We deduce the molecular events that underlie acquisition and transport of a ligand by Mhp1. PMID:24952894

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

Science.gov (United States)

Singer, M. S.; Oliveira, L.; Vriend, G.; Shepherd, G. M.

1995-01-01

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

A Bayesian classifier for symbol recognition

OpenAIRE

Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick

2007-01-01

URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

Science.gov (United States)

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Pattern Recognition via the Toll-Like Receptor System in the Human Female Genital Tract

Directory of Open Access Journals (Sweden)

Kaei Nasu

2010-01-01

Full Text Available The mucosal surface of the female genital tract is a complex biosystem, which provides a barrier against the outside world and participates in both innate and acquired immune defense systems. This mucosal compartment has adapted to a dynamic, non-sterile environment challenged by a variety of antigenic/inflammatory stimuli associated with sexual intercourse and endogenous vaginal microbiota. Rapid innate immune defenses against microbial infection usually involve the recognition of invading pathogens by specific pattern-recognition receptors recently attributed to the family of Toll-like receptors (TLRs. TLRs recognize conserved pathogen-associated molecular patterns (PAMPs synthesized by microorganisms including bacteria, fungi, parasites, and viruses as well as endogenous ligands associated with cell damage. Members of the TLR family, which includes 10 human TLRs identified to date, recognize distinct PAMPs produced by various bacterial, fungal, and viral pathogens. The available literature regarding the innate immune system of the female genital tract during human reproductive processes was reviewed in order to identify studies specifically related to the expression and function of TLRs under normal as well as pathological conditions. Increased understanding of these molecules may provide insight into site-specific immunoregulatory mechanisms in the female reproductive tract.

Sequence analysis of serum albumins reveals the molecular evolution of ligand recognition properties.

Science.gov (United States)

Fanali, Gabriella; Ascenzi, Paolo; Bernardi, Giorgio; Fasano, Mauro

2012-01-01

Serum albumin (SA) is a circulating protein providing a depot and carrier for many endogenous and exogenous compounds. At least seven major binding sites have been identified by structural and functional investigations mainly in human SA. SA is conserved in vertebrates, with at least 49 entries in protein sequence databases. The multiple sequence analysis of this set of entries leads to the definition of a cladistic tree for the molecular evolution of SA orthologs in vertebrates, thus showing the clustering of the considered species, with lamprey SAs (Lethenteron japonicum and Petromyzon marinus) in a separate outgroup. Sequence analysis aimed at searching conserved domains revealed that most SA sequences are made up by three repeated domains (about 600 residues), as extensively characterized for human SA. On the contrary, lamprey SAs are giant proteins (about 1400 residues) comprising seven repeated domains. The phylogenetic analysis of the SA family reveals a stringent correlation with the taxonomic classification of the species available in sequence databases. A focused inspection of the sequences of ligand binding sites in SA revealed that in all sites most residues involved in ligand binding are conserved, although the versatility towards different ligands could be peculiar of higher organisms. Moreover, the analysis of molecular links between the different sites suggests that allosteric modulation mechanisms could be restricted to higher vertebrates.

Handwritten Devanagari Character Recognition Using Layer-Wise Training of Deep Convolutional Neural Networks and Adaptive Gradient Methods

Directory of Open Access Journals (Sweden)

Mahesh Jangid

2018-02-01

Full Text Available Handwritten character recognition is currently getting the attention of researchers because of possible applications in assisting technology for blind and visually impaired users, human–robot interaction, automatic data entry for business documents, etc. In this work, we propose a technique to recognize handwritten Devanagari characters using deep convolutional neural networks (DCNN which are one of the recent techniques adopted from the deep learning community. We experimented the ISIDCHAR database provided by (Information Sharing Index ISI, Kolkata and V2DMDCHAR database with six different architectures of DCNN to evaluate the performance and also investigate the use of six recently developed adaptive gradient methods. A layer-wise technique of DCNN has been employed that helped to achieve the highest recognition accuracy and also get a faster convergence rate. The results of layer-wise-trained DCNN are favorable in comparison with those achieved by a shallow technique of handcrafted features and standard DCNN.

Urate is a ligand for the transcriptional regulator PecS.

Science.gov (United States)

Perera, Inoka C; Grove, Anne

2010-09-24

PecS is a member of the MarR (multiple antibiotic resistance regulator) family, which has been shown in Erwinia to regulate the expression of virulence genes. MarR homologs typically bind a small molecule ligand, resulting in attenuated DNA binding. For PecS, the natural ligand has not been identified. We have previously shown that urate is a ligand for the Deinococcus radiodurans-encoded MarR homolog HucR (hypothetical uricase regulator) and identified residues responsible for ligand binding. We show here that all four residues involved in urate binding and propagation of conformational changes to DNA recognition helices are conserved in PecS homologs, suggesting that urate is the ligand for PecS. Consistent with this prediction, Agrobacterium tumefaciens PecS specifically binds urate, and urate attenuates DNA binding in vitro. PecS binds two operator sites in the intergenic region between the divergent pecS gene and pecM genes, one of which features two partially overlapping repeats to which PecS binds as a dimer on opposite faces of the duplex. Notably, urate dissociates PecS from cognate DNA, allowing transcription of both genes in vivo. Taken together, our data show that urate is a ligand for PecS and suggest that urate serves a novel function in signaling the colonization of a host plant. Copyright © 2010 Elsevier Ltd. All rights reserved.

Structural Mechanism of the Oxygenase JMJD6 Recognition by the Extraterminal (ET) Domain of BRD4.

Science.gov (United States)

Konuma, Tsuyoshi; Yu, Di; Zhao, Chengcheng; Ju, Ying; Sharma, Rajal; Ren, Chunyan; Zhang, Qiang; Zhou, Ming-Ming; Zeng, Lei

2017-11-24

Jumonji domain-containing protein 6 (JMJD6) is a member of the Jumonji C family of Fe(II) and 2-oxoglutarate (2OG) dependent oxygenases. It possesses unique bi-functional oxygenase activities, acting as both an arginine demethylase and a lysyl-hydroxylase. JMJD6 has been reported to be over-expressed in oral, breast, lung, and colon cancers and plays important roles in regulation of transcription through interactions with transcription regulator BRD4, histones, U2AF65, Luc7L3, and SRSF11. Here, we report a structural mechanism revealed by NMR of JMJD6 recognition by the extraterminal (ET) domain of BRD4 in that a JMJD6 peptide (Lys84-Asn96) adapts an α-helix when bound to the ET domain. This intermolecular recognition is established through JMJD6 interactions with the conserved hydrophobic core of the ET domain, and reinforced by electrostatic interactions of JMJD6 with residues in the inter-helical α1-α2 loop of the ET domain. Notably, this mode of ligand recognition is different from that of ET domain recognition of NSD3, LANA of herpesvirus, and integrase of MLV, which involves formation of an intermolecular amphipathic two- or three- strand antiparallel β sheet. Furthermore, we demonstrate that the association between the BRD4 ET domain and JMJD6 likely requires a protein conformational change induced by single-stranded RNA binding.

A New Adaptive Structural Signature for Symbol Recognition by Using a Galois Lattice as a Classifier.

Science.gov (United States)

Coustaty, M; Bertet, K; Visani, M; Ogier, J

2011-08-01

In this paper, we propose a new approach for symbol recognition using structural signatures and a Galois lattice as a classifier. The structural signatures are based on topological graphs computed from segments which are extracted from the symbol images by using an adapted Hough transform. These structural signatures-that can be seen as dynamic paths which carry high-level information-are robust toward various transformations. They are classified by using a Galois lattice as a classifier. The performance of the proposed approach is evaluated based on the GREC'03 symbol database, and the experimental results we obtain are encouraging.

Structural hierarchy controlling dimerization and target DNA recognition in the AHR transcriptional complex

Energy Technology Data Exchange (ETDEWEB)

Seok, Seung-Hyeon; Lee, Woojong; Jiang, Li; Molugu, Kaivalya; Zheng, Aiping; Li, Yitong; Park, Sanghyun; Bradfield, Christopher A.; Xing, Yongna (UW)

2017-04-10

he aryl hydrocarbon receptor (AHR) belongs to the PAS (PER-ARNT-SIM) family transcription factors and mediates broad responses to numerous environmental pollutants and cellular metabolites, modulating diverse biological processes from adaptive metabolism, acute toxicity, to normal physiology of vascular and immune systems. The AHR forms a transcriptionally active heterodimer with ARNT (AHR nuclear translocator), which recognizes the dioxin response element (DRE) in the promoter of downstream genes. We determined the crystal structure of the mammalian AHR–ARNT heterodimer in complex with the DRE, in which ARNT curls around AHR into a highly intertwined asymmetric architecture, with extensive heterodimerization interfaces and AHR interdomain interactions. Specific recognition of the DRE is determined locally by the DNA-binding residues, which discriminates it from the closely related hypoxia response element (HRE), and is globally affected by the dimerization interfaces and interdomain interactions. Changes at the interdomain interactions caused either AHR constitutive nuclear localization or failure to translocate to nucleus, underlying an allosteric structural pathway for mediating ligand-induced exposure of nuclear localization signal. These observations, together with the global higher flexibility of the AHR PAS-A and its loosely packed structural elements, suggest a dynamic structural hierarchy for complex scenarios of AHR activation induced by its diverse ligands.

EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

Directory of Open Access Journals (Sweden)

Suwicha Jirayucharoensak

2014-01-01

Full Text Available Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN to discover unknown feature correlation between input signals that is crucial for the learning task. The DLN is implemented with a stacked autoencoder (SAE using hierarchical feature learning approach. Input features of the network are power spectral densities of 32-channel EEG signals from 32 subjects. To alleviate overfitting problem, principal component analysis (PCA is applied to extract the most important components of initial input features. Furthermore, covariate shift adaptation of the principal components is implemented to minimize the nonstationary effect of EEG signals. Experimental results show that the DLN is capable of classifying three different levels of valence and arousal with accuracy of 49.52% and 46.03%, respectively. Principal component based covariate shift adaptation enhances the respective classification accuracy by 5.55% and 6.53%. Moreover, DLN provides better performance compared to SVM and naive Bayes classifiers.

Ficolins and FIBCD1: Soluble and membrane bound pattern recognition molecules with acetyl group selectivity

DEFF Research Database (Denmark)

Thomsen, Theresa; Schlosser, Anders; Holmskov, Uffe

2011-01-01

as pattern recognition molecules. Ficolins are soluble oligomeric proteins composed of trimeric collagen-like regions linked to fibrinogen-related domains (FReDs) that have the ability to sense molecular patterns on both pathogens and apoptotic cell surfaces and activate the complement system. The ficolins......D-containing molecules, and discusses structural resemblance but also diversity in recognition of acetylated ligands....

Molecular basis for convergent evolution of glutamate recognition by pentameric ligand-gated ion channels

DEFF Research Database (Denmark)

Lynagh, Timothy; Beech, Robin N.; Lalande, Maryline J.

2015-01-01

that glutamate recognition requires an arginine residue in the base of the binding site, which originated at least three distinct times according to phylogenetic analysis. Most remarkably, the arginine emerged on the principal face of the binding site in the Lophotrochozoan lineage, but 65 amino acids upstream......Glutamate is an indispensable neurotransmitter, triggering postsynaptic signals upon recognition by postsynaptic receptors. We questioned the phylogenetic position and the molecular details of when and where glutamate recognition arose in the glutamate-gated chloride channels. Experiments revealed......, on the complementary face, in the Ecdysozoan lineage. This combined experimental and computational approach throws new light on the evolution of synaptic signalling....

Regulation mechanisms of the FLT3-ligand after irradiation; Mecanismes de regulation du FLT3-ligand apres irradiation

Energy Technology Data Exchange (ETDEWEB)

Prat-Lepesant, M

2005-06-15

The hematopoietic compartment is one of the most severely damaged after chemotherapy, radiotherapy or accidental irradiations. Whatever its origin, the resulting damage to the bone marrow remains difficult to evaluate. Thus, it would be of great interest to get a biological indicator of residual hematopoiesis in order to adapt the treatment to each clinical situation. Recent results indicated that the plasma Flt3 ligand concentration was increased in patients suffering from either acquired or induced aplasia, suggesting that Flt3 ligand might be useful as a biological indicator of bone marrow status. We thus followed in a mouse model as well as in several clinical situations the variations in plasma Flt3 ligand concentration, after either homogeneous or heterogeneous irradiations. These variations were correlated to the number of hematopoietic progenitors and to other parameters such as duration and depth of pancytopenia. The results indicated that the concentration of Flt3 ligand in the blood reflects the bone marrow status, and that the follow-up of plasma Flt3 ligand concentration could give predictive information about the bone marrow function and the duration and severity of pancytopenia and thrombocytopenia. Nevertheless, the clinical use of Flt3 ligand as a biological indicator of bone marrow damage require the knowledge of the mechanisms regulating the variations in plasma Flt3 ligand concentration. We thus developed a study in the mouse model. The results indicated that the variations in plasma Flt3 ligand variations were not solely due to a balance between its production by lymphoid cells and its consumption by hematopoietic cells. Moreover, we showed that T lymphocytes are not the main regulator of plasma Flt3 ligand concentration as previously suggested, and that other cell types, possibly including bone marrow stromal cells, might be strongly implicated. These results also suggest that the Flt3 ligand is a main systemic regulator of hematopoiesis

Adaptive pattern recognition in real-time video-based soccer analysis

DEFF Research Database (Denmark)

Schlipsing, Marc; Salmen, Jan; Tschentscher, Marc

2017-01-01

are taken into account. Our contribution is twofold: (1) the deliberate use of machine learning and pattern recognition techniques allows us to achieve high classification accuracy in varying environments. We systematically evaluate combinations of image features and learning machines in the given online......Computer-aided sports analysis is demanded by coaches and the media. Image processing and machine learning techniques that allow for "live" recognition and tracking of players exist. But these methods are far from collecting and analyzing event data fully autonomously. To generate accurate results......, human interaction is required at different stages including system setup, calibration, supervision of classifier training, and resolution of tracking conflicts. Furthermore, the real-time constraints are challenging: in contrast to other object recognition and tracking applications, we cannot treat data...

Ligand recognition and domain structure of Vps10p, a vacuolar protein sorting receptor in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Jørgensen, M U; Emr, S D; Winther, Jakob R.

1999-01-01

Vp10p is a receptor that sorts several different vacuolar proteins by cycling between a late Golgi compartment and the endosome. The cytoplasmic tail of Vps10p is necessary for the recycling, whereas the lumenal domain is predicted to interact with the soluble ligands. We have studied ligand bind...

Physics of Automatic Target Recognition

CERN Document Server

Sadjadi, Firooz

2007-01-01

Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

Conformational changes and allosteric communications in human serum albumin due to ligand binding.

Science.gov (United States)

Ahalawat, Navjeet; Murarka, Rajesh K

2015-01-01

It is well recognized that knowledge of structure alone is not sufficient to understand the fundamental mechanism of biomolecular recognition. Information of dynamics is necessary to describe motions involving relevant conformational states of functional importance. We carried out principal component analysis (PCA) of structural ensemble, derived from 84 crystal structures of human serum albumin (HSA) with different ligands and/or different conditions, to identify the functionally important collective motions, and compared with the motions along the low-frequency modes obtained from normal mode analysis of the elastic network model (ENM) of unliganded HSA. Significant overlap is observed in the collective motions derived from PCA and ENM. PCA and ENM analysis revealed that ligand selects the most favored conformation from accessible equilibrium structures of unliganded HSA. Further, we analyzed dynamic network obtained from molecular dynamics simulations of unliganded HSA and fatty acids- bound HSA. Our results show that fatty acids-bound HSA has more robust community network with several routes to communicate among different parts of the protein. Critical nodes (residues) identified from dynamic network analysis are in good agreement with allosteric residues obtained from sequence-based statistical coupling analysis method. This work underscores the importance of intrinsic structural dynamics of proteins in ligand recognition and can be utilized for the development of novel drugs with optimum activity.

Vesicular Stomatitis Virus Infection Promotes Immune Evasion by Preventing NKG2D-Ligand Surface Expression

DEFF Research Database (Denmark)

Jensen, Helle; Andresen, Lars; Nielsen, Jens

2011-01-01

Vesicular stomatitis virus (VSV) has recently gained attention for its oncolytic ability in cancer treatment. Initially, we hypothesized that VSV infection could increase immune recognition of cancer cells through induction of the immune stimulatory NKG2D-ligands. Here we show that VSV infection ...

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

Science.gov (United States)

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the

Protein flexibility and ligand rigidity : a thermodynamic and kinetic study of ITAM-based ligand binding to Syk tandem SH2

NARCIS (Netherlands)

de Mol, Nico J; Catalina, M Isabel; Dekker, Frank J; Fischer, Marcel J E; Heck, Albert J R; Liskamp, Rob M J; Dekker, Frank

2005-01-01

The Syk tandem Src homology 2 domain (Syk tSH2) constitutes a flexible protein module involved in the regulation of Syk kinase activity. The Syk tSH2 domain is assumed to function by adapting the distance between its two SH2 domains upon bivalent binding to diphosphotyrosine ligands. A thermodynamic

Computational Approaches to the Chemical Equilibrium Constant in Protein-ligand Binding.

Science.gov (United States)

Montalvo-Acosta, Joel José; Cecchini, Marco

2016-12-01

The physiological role played by protein-ligand recognition has motivated the development of several computational approaches to the ligand binding affinity. Some of them, termed rigorous, have a strong theoretical foundation but involve too much computation to be generally useful. Some others alleviate the computational burden by introducing strong approximations and/or empirical calibrations, which also limit their general use. Most importantly, there is no straightforward correlation between the predictive power and the level of approximation introduced. Here, we present a general framework for the quantitative interpretation of protein-ligand binding based on statistical mechanics. Within this framework, we re-derive self-consistently the fundamental equations of some popular approaches to the binding constant and pinpoint the inherent approximations. Our analysis represents a first step towards the development of variants with optimum accuracy/efficiency ratio for each stage of the drug discovery pipeline. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Essential role of conformational selection in ligand binding.

Science.gov (United States)

Vogt, Austin D; Pozzi, Nicola; Chen, Zhiwei; Di Cera, Enrico

2014-02-01

Two competing and mutually exclusive mechanisms of ligand recognition - conformational selection and induced fit - have dominated our interpretation of ligand binding in biological macromolecules for almost six decades. Conformational selection posits the pre-existence of multiple conformations of the macromolecule from which the ligand selects the optimal one. Induced fit, on the other hand, postulates the existence of conformational rearrangements of the original conformation into an optimal one that are induced by binding of the ligand. In the former case, conformational transitions precede the binding event; in the latter, conformational changes follow the binding step. Kineticists have used a facile criterion to distinguish between the two mechanisms based on the dependence of the rate of relaxation to equilibrium, kobs, on the ligand concentration, [L]. A value of kobs decreasing hyperbolically with [L] has been seen as diagnostic of conformational selection, while a value of kobs increasing hyperbolically with [L] has been considered diagnostic of induced fit. However, this simple conclusion is only valid under the rather unrealistic assumption of conformational transitions being much slower than binding and dissociation events. In general, induced fit only produces values of kobs that increase with [L] but conformational selection is more versatile and is associated with values of kobs that increase with, decrease with or are independent of [L]. The richer repertoire of kinetic properties of conformational selection applies to kinetic mechanisms with single or multiple saturable relaxations and explains the behavior of nearly all experimental systems reported in the literature thus far. Conformational selection is always sufficient and often necessary to account for the relaxation kinetics of ligand binding to a biological macromolecule and is therefore an essential component of any binding mechanism. On the other hand, induced fit is never necessary and

Contrasting roles for TLR ligands in HIV-1 pathogenesis.

Directory of Open Access Journals (Sweden)

Beda Brichacek

2010-09-01

Full Text Available The first line of a host's response to various pathogens is triggered by their engagement of cellular pattern recognition receptors (PRRs. Binding of microbial ligands to these receptors leads to the induction of a variety of cellular factors that alter intracellular and extracellular environment and interfere directly or indirectly with the life cycle of the triggering pathogen. Such changes may also affect any coinfecting microbe. Using ligands to Toll-like receptors (TLRs 5 and 9, we examined their effect on human immunodeficiency virus (HIV-1 replication in lymphoid tissue ex vivo. We found marked differences in the outcomes of such treatment. While flagellin (TLR5 agonist treatment enhanced replication of CC chemokine receptor 5 (CCR 5-tropic and CXC chemokine receptor 4 (CXCR4-tropic HIV-1, treatment with oligodeoxynucleotide (ODN M362 (TLR9 agonist suppressed both viral variants. The differential effects of these TLR ligands on HIV-1 replication correlated with changes in production of CC chemokines CCL3, CCL4, CCL5, and of CXC chemokines CXCL10, and CXCL12 in the ligand-treated HIV-1-infected tissues. The nature and/or magnitude of these changes were dependent on the ligand as well as on the HIV-1 viral strain. Moreover, the tested ligands differed in their ability to induce cellular activation as evaluated by the expression of the cluster of differentiation markers (CD 25, CD38, CD39, CD69, CD154, and human leukocyte antigen D related (HLA-DR as well as of a cell proliferation marker, Ki67, and of CCR5. No significant effect of the ligand treatment was observed on apoptosis and cell death/loss in the treated lymphoid tissue ex vivo. Our results suggest that binding of microbial ligands to TLRs is one of the mechanisms that mediate interactions between coinfected microbes and HIV-1 in human tissues. Thus, the engagement of appropriate TLRs by microbial molecules or their mimetic might become a new strategy for HIV therapy or prevention.

Extended Target Recognition in Cognitive Radar Networks

Directory of Open Access Journals (Sweden)

Xiqin Wang

2010-11-01

Full Text Available 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.

Soaking suggests "alternative facts": Only co-crystallization discloses major ligand-induced interface rearrangements of a homodimeric tRNA-binding protein indicating a novel mode-of-inhibition.

Directory of Open Access Journals (Sweden)

Frederik Rainer Ehrmann

Full Text Available For the efficient pathogenesis of Shigella, the causative agent of bacillary dysentery, full functionality of tRNA-guanine transglycosylase (TGT is mandatory. TGT performs post-transcriptional modifications of tRNAs in the anticodon loop taking impact on virulence development. This suggests TGT as a putative target for selective anti-shigellosis drug therapy. Since bacterial TGT is only functional as homodimer, its activity can be inhibited either by blocking its active site or by preventing dimerization. Recently, we discovered that in some crystal structures obtained by soaking the full conformational adaptation most likely induced in solution upon ligand binding is not displayed. Thus, soaked structures may be misleading and suggest irrelevant binding modes. Accordingly, we re-investigated these complexes by co-crystallization. The obtained structures revealed large conformational rearrangements not visible in the soaked complexes. They result from spatial perturbations in the ribose-34/phosphate-35 recognition pocket and, consequently, an extended loop-helix motif required to prevent access of water molecules into the dimer interface loses its geometric integrity. Thermodynamic profiles of ligand binding in solution indicate favorable entropic contributions to complex formation when large conformational adaptations in the dimer interface are involved. Native MS titration experiments reveal the extent to which the homodimer is destabilized in the presence of each inhibitor. Unexpectedly, one ligand causes a complete rearrangement of subunit packing within the homodimer, never observed in any other TGT crystal structure before. Likely, this novel twisted dimer is catalytically inactive and, therefore, suggests that stabilizing this non-productive subunit arrangement may be used as a further strategy for TGT inhibition.

π-Cation Interactions in Molecular Recognition: Perspectives on Pharmaceuticals and Pesticides.

Science.gov (United States)

Liang, Zhibin; Li, Qing X

2018-04-04

The π-cation interaction that differs from the cation-π interaction is a valuable concept in molecular design of pharmaceuticals and pesticides. In this Perspective we present an up-to-date review (from 1995 to 2017) on bioactive molecules involving π-cation interactions with the recognition site, and categorize into systems of inhibitor-enzyme, ligand-receptor, ligand-transporter, and hapten-antibody. The concept of π-cation interactions offers use of π systems in a small molecule to enhance the binding affinity, specificity, selectivity, lipophilicity, bioavailability, and metabolic stability, which are physiochemical features desired for drugs and pesticides.

Reversible Size Control of Silver Nanoclusters via Ligand-exchange

KAUST Repository

Bootharaju, Megalamane Siddaramappa

2015-05-21

The properties of atomically monodisperse noble metal nanoclusters (NCs) are intricately intertwined with their precise molecular formula. The vast majority of size-specific NC syntheses start from the reduction of the metal salt and thiol ligand mixture. Only in gold was it recently shown that ligand-exchange could induce the growth of NCs from one atomically precise species to another; a process of yet unknown reversibility. Here, we present a process for the ligand-exchange-induced growth of atomically precise silver NCs, in a biphasic liquid-liquid system, which is particularly of interest because of its complete reversibility and ability to occur at room temperature. We explore this phenomenon in-depth using Ag35(SG)18 [SG= glutathionate] and Ag44(4-FTP)30 [4-FTP= 4-fluorothiophenol] as model systems. We show that the ligand-exchange conversion of Ag35(SG)18 into Ag44(4-FTP)30 is rapid (< 5 min) and direct, while the reverse process proceeds slowly through intermediate cluster sizes. We adapt a recently developed theory of reverse Ostwald ripening to model the NCs’ interconvertibility. The model’s predictions are in good agreement with the experimental observations, and they highlight the importance of small changes in the ligand-metal binding energy in determining the final equilibrium NC size. Based on the insight provided by this model, we demonstrated experimentally that by varying the choice of ligands, ligand-exchange can be used to obtain different sized NCs. The findings in this work establish ligand-exchange as a versatile tool for tuning cluster sizes.

Reversible Size Control of Silver Nanoclusters via Ligand-exchange

KAUST Repository

Bootharaju, Megalamane Siddaramappa; Burlakov, Victor M.; Besong, Tabot M.D.; Joshi, Chakra Prasad; AbdulHalim, L; Black, David; Whetten, Robert; Goriely, Alain; Bakr, Osman

2015-01-01

The properties of atomically monodisperse noble metal nanoclusters (NCs) are intricately intertwined with their precise molecular formula. The vast majority of size-specific NC syntheses start from the reduction of the metal salt and thiol ligand mixture. Only in gold was it recently shown that ligand-exchange could induce the growth of NCs from one atomically precise species to another; a process of yet unknown reversibility. Here, we present a process for the ligand-exchange-induced growth of atomically precise silver NCs, in a biphasic liquid-liquid system, which is particularly of interest because of its complete reversibility and ability to occur at room temperature. We explore this phenomenon in-depth using Ag35(SG)18 [SG= glutathionate] and Ag44(4-FTP)30 [4-FTP= 4-fluorothiophenol] as model systems. We show that the ligand-exchange conversion of Ag35(SG)18 into Ag44(4-FTP)30 is rapid (< 5 min) and direct, while the reverse process proceeds slowly through intermediate cluster sizes. We adapt a recently developed theory of reverse Ostwald ripening to model the NCs’ interconvertibility. The model’s predictions are in good agreement with the experimental observations, and they highlight the importance of small changes in the ligand-metal binding energy in determining the final equilibrium NC size. Based on the insight provided by this model, we demonstrated experimentally that by varying the choice of ligands, ligand-exchange can be used to obtain different sized NCs. The findings in this work establish ligand-exchange as a versatile tool for tuning cluster sizes.

Bio-specific recognition and applications: from molecular to colloidal scales

International Nuclear Information System (INIS)

Baudry, Jean; Bertrand, Emanuel; Lequeux, Nicolas; Bibette, Jerome

2004-01-01

Biomolecules have the well-known ability to build reversible complexes. Indeed, antigens and antibodies or adhesion molecules are able to recognize one another with a strong affinity and a very high specificity. This paper first reviews the various techniques and related results about binding and unbinding, at the scale of a unique ligand/receptor couple. One important biotechnological application arising from these recognition phenomena concerns immuno-diagnosis, which is essentially based on the formation of these specific complexes. We show how the physics of colloids associated with the growing scientific background concerning molecular recognition helps in rationalizing and inventing new diagnostic strategies. Finally the concept of colloidal self-assembling systems as biosensors is presented as directly impacting the most important questions related to molecular recognition and their biotechnological implications. (topical review)

Use of digital speech recognition in diagnostics radiology

International Nuclear Information System (INIS)

Arndt, H.; Stockheim, D.; Mutze, S.; Petersein, J.; Gregor, P.; Hamm, B.

1999-01-01

Purpose: Applicability and benefits of digital speech recognition in diagnostic radiology were tested using the speech recognition system SP 6000. Methods: The speech recognition system SP 6000 was integrated into the network of the institute and connected to the existing Radiological Information System (RIS). Three subjects used this system for writing 2305 findings from dictation. After the recognition process the date, length of dictation, time required for checking/correction, kind of examination and error rate were recorded for every dictation. With the same subjects, a correlation was performed with 625 conventionally written finding. Results: After an 1-hour initial training the average error rates were 8.4 to 13.3%. The first adaptation of the speech recognition system (after nine days) decreased the average error rates to 2.4 to 10.7% due to the ability of the program to learn. The 2 nd and 3 rd adaptations resulted only in small changes of the error rate. An individual comparison of the error rate developments in the same kind of investigation showed the relative independence of the error rate on the individual user. Conclusion: The results show that the speech recognition system SP 6000 can be evaluated as an advantageous alternative for quickly recording radiological findings. A comparison between manually writing and dictating the findings verifies the individual differences of the writing speeds and shows the advantage of the application of voice recognition when faced with normal keyboard performance. (orig.) [de

Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

Science.gov (United States)

Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

2017-01-01

People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

Destabilization of strigolactone receptor DWARF14 by binding of ligand and E3-ligase signaling effector DWARF3

Science.gov (United States)

Zhao, Li-Hua; Zhou, X Edward; Yi, Wei; Wu, Zhongshan; Liu, Yue; Kang, Yanyong; Hou, Li; de Waal, Parker W; Li, Suling; Jiang, Yi; Scaffidi, Adrian; Flematti, Gavin R; Smith, Steven M; Lam, Vinh Q; Griffin, Patrick R; Wang, Yonghong; Li, Jiayang; Melcher, Karsten; Xu, H Eric

2015-01-01

Strigolactones (SLs) are endogenous hormones and exuded signaling molecules in plant responses to low levels of mineral nutrients. Key mediators of the SL signaling pathway in rice include the α/β-fold hydrolase DWARF 14 (D14) and the F-box component DWARF 3 (D3) of the ubiquitin ligase SCFD3 that mediate ligand-dependent degradation of downstream signaling repressors. One perplexing feature is that D14 not only functions as the SL receptor but is also an active enzyme that slowly hydrolyzes diverse natural and synthetic SLs including GR24, preventing the crystallization of a binary complex of D14 with an intact SL as well as the ternary D14/SL/D3 complex. Here we overcome these barriers to derive a structural model of D14 bound to intact GR24 and identify the interface that is required for GR24-mediated D14-D3 interaction. The mode of GR24-mediated signaling, including ligand recognition, hydrolysis by D14, and ligand-mediated D14-D3 interaction, is conserved in structurally diverse SLs. More importantly, D14 is destabilized upon the binding of ligands and D3, thus revealing an unusual mechanism of SL recognition and signaling, in which the hormone, the receptor, and the downstream effectors are systematically destabilized during the signal transduction process. PMID:26470846

Pseudomonas Evades Immune Recognition of Flagellin in Both Mammals and Plants

Science.gov (United States)

Bardoel, Bart W.; van der Ent, Sjoerd; Pel, Michiel J. C.; Tommassen, Jan; Pieterse, Corné M. J.; van Kessel, Kok P. M.; van Strijp, Jos A. G.

2011-01-01

The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5) in mammals and flagellin-sensitive 2 (FLS2) in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR) antagonists, we screened bacterial supernatants and identified alkaline protease (AprA) of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility) and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition) in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants. PMID:21901099

Exogenous or endogenous Toll-like receptor ligands: which is the MVP in tumorigenesis?

Science.gov (United States)

Yu, Li; Wang, Liantang; Chen, Shangwu

2012-03-01

Toll-like receptors (TLRs) are a class of pattern recognition receptors sensing microbial components and triggering an immune response against pathogens. In addition to their role in anti-infection immunity, increasing evidence indicates that engagement of TLRs can promote cancer cell survival and proliferation, induce tumor immune evasion, and enhance tumor metastasis and chemoresistance. Recent studies have demonstrated that endogenous molecules or damage-associated molecular patterns released from damaged/necrotic tissues are capable of activating TLRs and that the endogenous ligands-mediated TLR signaling is implicated in the tumor development and affects the therapeutic efficacy of tumors. Since both exogenous and endogenous TLR ligands can initiate TLR signaling, which is the most valuable player in tumor development becomes an interesting question. Here, we summarize the effect of TLR signaling on the development and progression of tumors, and discuss the role of exogenous and endogenous TLR ligands in the tumorigenesis.

Protein-Templated Fragment Ligations-From Molecular Recognition to Drug Discovery.

Science.gov (United States)

Jaegle, Mike; Wong, Ee Lin; Tauber, Carolin; Nawrotzky, Eric; Arkona, Christoph; Rademann, Jörg

2017-06-19

Protein-templated fragment ligation is a novel concept to support drug discovery and can help to improve the efficacy of protein ligands. Protein-templated fragment ligations are chemical reactions between small molecules ("fragments") utilizing a protein's surface as a reaction vessel to catalyze the formation of a protein ligand with increased binding affinity. The approach exploits the molecular recognition of reactive small-molecule fragments by proteins both for ligand assembly and for the identification of bioactive fragment combinations. In this way, chemical synthesis and bioassay are integrated in one single step. This Review discusses the biophysical basis of reversible and irreversible fragment ligations and gives an overview of the available methods to detect protein-templated ligation products. The chemical scope and recent applications as well as future potential of the concept in drug discovery are reviewed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Efficient ABC_DE_Based Hybrid Algorithm for Protein–Ligand Docking

Directory of Open Access Journals (Sweden)

Boxin Guan

2018-04-01

Full Text Available Protein–ligand docking is a process of searching for the optimal binding conformation between the receptor and the ligand. Automated docking plays an important role in drug design, and an efficient search algorithm is needed to tackle the docking problem. To tackle the protein–ligand docking problem more efficiently, An ABC_DE_based hybrid algorithm (ADHDOCK, integrating artificial bee colony (ABC algorithm and differential evolution (DE algorithm, is proposed in the article. ADHDOCK applies an adaptive population partition (APP mechanism to reasonably allocate the computational resources of the population in each iteration process, which helps the novel method make better use of the advantages of ABC and DE. The experiment tested fifty protein–ligand docking problems to compare the performance of ADHDOCK, ABC, DE, Lamarckian genetic algorithm (LGA, running history information guided genetic algorithm (HIGA, and swarm optimization for highly flexible protein–ligand docking (SODOCK. The results clearly exhibit the capability of ADHDOCK toward finding the lowest energy and the smallest root-mean-square deviation (RMSD on most of the protein–ligand docking problems with respect to the other five algorithms.

Synthesis and binding properties of new selective ligands for the nucleobase opposite the AP site.

Science.gov (United States)

Abe, Yukiko; Nakagawa, Osamu; Yamaguchi, Rie; Sasaki, Shigeki

2012-06-01

DNA is continuously damaged by endogenous and exogenous factors such as oxidative stress or DNA alkylating agents. These damaged nucleobases are removed by DNA N-glycosylase and form apurinic/apyrimidinic sites (AP sites) as intermediates in the base excision repair (BER) pathway. AP sites are also representative DNA damages formed by spontaneous hydrolysis. The AP sites block DNA polymerase and a mismatch nucleobase is inserted opposite the AP sites by polymerization to cause acute toxicities and mutations. Thus, AP site specific compounds have attracted much attention for therapeutic and diagnostic purposes. In this study, we have developed nucleobase-polyamine conjugates as the AP site binding ligand by expecting that the nucleobase part would play a role in the specific recognition of the nucleobase opposite the AP site by the Watson-Crick base pair formation and that the polyamine part should contribute to the access of the ligand to the AP site by a non-specific interaction to the DNA phosphate backbone. The nucleobase conjugated with 3,3'-diaminodipropylamine (A-ligand, G-ligand, C-ligand, T-ligand and U-ligand) showed a specific stabilization of the duplex containing the AP site depending on the complementary combination with the nucleobase opposite the AP site; that is A-ligand to T, G-ligand to C, C-ligand to G, T- and U-ligand to A. The thermodynamic binding parameters clearly indicated that the specific stabilization is due to specific binding of the ligands to the complementary AP site. These results have suggested that the complementary base pairs of the Watson-Crick type are formed at the AP site. Copyright © 2012 Elsevier Ltd. All rights reserved.

An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition

Directory of Open Access Journals (Sweden)

Ing-Jr Ding

2014-01-01

Full Text Available In the past, the kernel of automatic speech recognition (ASR is dynamic time warping (DTW, which is feature-based template matching and belongs to the category technique of dynamic programming (DP. Although DTW is an early developed ASR technique, DTW has been popular in lots of applications. DTW is playing an important role for the known Kinect-based gesture recognition application now. This paper proposed an intelligent speech recognition system using an improved DTW approach for multimedia and home automation services. The improved DTW presented in this work, called HMM-like DTW, is essentially a hidden Markov model- (HMM- like method where the concept of the typical HMM statistical model is brought into the design of DTW. The developed HMM-like DTW method, transforming feature-based DTW recognition into model-based DTW recognition, will be able to behave as the HMM recognition technique and therefore proposed HMM-like DTW with the HMM-like recognition model will have the capability to further perform model adaptation (also known as speaker adaptation. A series of experimental results in home automation-based multimedia access service environments demonstrated the superiority and effectiveness of the developed smart speech recognition system by HMM-like DTW.

Investigating the binding behaviour of two avidin-based testosterone binders using molecular recognition force spectroscopy.

Science.gov (United States)

Rangl, Martina; Leitner, Michael; Riihimäki, Tiina; Lehtonen, Soili; Hytönen, Vesa P; Gruber, Hermann J; Kulomaa, Markku; Hinterdorfer, Peter; Ebner, Andreas

2014-02-01

Molecular recognition force spectroscopy, a biosensing atomic force microscopy technique allows to characterise the dissociation of ligand-receptor complexes at the molecular level. Here, we used molecular recognition force spectroscopy to study the binding capability of recently developed testosterone binders. The two avidin-based proteins called sbAvd-1 and sbAvd-2 are expected to bind both testosterone and biotin but differ in their binding behaviour towards these ligands. To explore the ligand binding and dissociation energy landscape of these proteins, we tethered biotin or testosterone to the atomic force microscopy probe while the testosterone-binding protein was immobilized on the surface. Repeated formation and rupture of the ligand-receptor complex at different pulling velocities allowed determination of the loading rate dependence of the complex-rupturing force. In this way, we obtained the molecular dissociation rate (k(off)) and energy landscape distances (x(β)) of the four possible complexes: sbAvd-1-biotin, sbAvd-1-testosterone, sbAvd-2-biotin and sbAvd-2-testosterone. It was found that the kinetic off-rates for both proteins and both ligands are similar. In contrast, the x(β) values, as well as the probability of complex formations, varied considerably. In addition, competitive binding experiments with biotin and testosterone in solution differ significantly for the two testosterone-binding proteins, implying a decreased cross-reactivity of sbAvd-2. Unravelling the binding behaviour of the investigated testosterone-binding proteins is expected to improve their usability for possible sensing applications. Copyright © 2014 John Wiley & Sons, Ltd.

Toxoplasma gondii peptide ligands open the gate of the HLA class I binding groove

DEFF Research Database (Denmark)

McMurtrey, Curtis; Trolle, Thomas; Sansom, Tiffany

2016-01-01

HLA class I presentation of pathogen-derived peptide ligands is essential for CD8+ T cell recognition of Toxoplasma gondii infected cells. Currently, little data exist pertaining to peptides that are presented after T. gondii infection. Herein we purify HLA-A*02:01 complexes from T. gondii infect...

Endocytosis via galactose receptors in vivo. Ligand size directs uptake by hepatocytes and/or liver macrophages

International Nuclear Information System (INIS)

Schlepper-Schaefer, J.; Huelsmann, D.; Djovkar, A.; Meyer, H.E.; Herbertz, L.; Kolb, H.; Kolb-Bachofen, V.

1986-01-01

The intrahepatic binding and uptake of variously sized ligands with terminal galactosyl residues is rat liver was followed. The ligands were administered to prefixed livers in binding studies and in vivo and in situ (serum-free perfused livers) in uptake studies. Gold sols with different particle diameters were prepared: 5 nm (Au 5 ), 17 nm (Au 17 ), 50 nm (Au 50 ) and coated with galactose exposing glycoproteins (asialofetuin (ASF) or lactosylated BSA (LacBSA)). Electron microscopy of mildly prefixed livers perfused with LacBSA-Au 5 in serum-free medium showed ligand binding to liver macrophages, hepatocytes and endothelial cells. Ligands bound to prefixed cell surfaces reflect the initial distribution of receptor activity: pre-aggregated clusters of ligands are found on liver macrophages, single particles statistically distributed on hepatocytes and pre-aggregated clusters of particles restricted to coated pits on endothelial cells. Ligand binding is prevented in the presence of 80 mM N-acetylgalactosamine (GalNAc), while N-acetylglucosamine (GlcNAc) is without effect. Electron microscopy of livers after ligand injection into the tail vein shows that in vivo uptake of electron-dense galactose particles by liver cells is size-dependent. In vivo uptake by liver macrophages is mediated by galactose-specific recognition as shown by inhibition with GalNAc

Adaptive metric learning with deep neural networks for video-based facial expression recognition

Science.gov (United States)

Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

2018-01-01

Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

Molecular modeling of ligand-receptor interactions in the OR5 olfactory receptor.

Science.gov (United States)

Singer, M S; Shepherd, G M

1994-06-02

Olfactory receptors belong to the superfamily of seven transmembrane domain, G protein-coupled receptors. In order to begin analysis of mechanisms of receptor activation, a computer model of the OR5 olfactory receptor has been constructed and compared with other members of this superfamily. We have tested docking of the odor molecule lyral, which is known to activate the OR5 receptor. The results point to specific ligand-binding residues on helices III through VII that form a binding pocket in the receptor. Some of these residues occupy sequence positions identical to ligand-binding residues conserved among other superfamily members. The results provide new insights into possible molecular mechanisms of odor recognition and suggest hypotheses to guide future experimental studies using site-directed mutagenesis.

Thermodynamic fingerprints of ligand binding to human telomeric G-quadruplexes.

Science.gov (United States)

Bončina, Matjaž; Podlipnik, Črtomir; Piantanida, Ivo; Eilmes, Julita; Teulade-Fichou, Marie-Paule; Vesnaver, Gorazd; Lah, Jurij

2015-12-02

Thermodynamic studies of ligand binding to human telomere (ht) DNA quadruplexes, as a rule, neglect the involvement of various ht-DNA conformations in the binding process. Therefore, the thermodynamic driving forces and the mechanisms of ht-DNA G-quadruplex-ligand recognition remain poorly understood. In this work we characterize thermodynamically and structurally binding of netropsin (Net), dibenzotetraaza[14]annulene derivatives (DP77, DP78), cationic porphyrin (TMPyP4) and two bisquinolinium ligands (Phen-DC3, 360A-Br) to the ht-DNA fragment (Tel22) AGGG(TTAGGG)3 using isothermal titration calorimetry, CD and fluorescence spectroscopy, gel electrophoresis and molecular modeling. By global thermodynamic analysis of experimental data we show that the driving forces characterized by contributions of specific interactions, changes in solvation and conformation differ significantly for binding of ligands with low quadruplex selectivity over duplexes (Net, DP77, DP78, TMPyP4; KTel22 ≈ KdsDNA). These contributions are in accordance with the observed structural features (changes) and suggest that upon binding Net, DP77, DP78 and TMPyP4 select hybrid-1 and/or hybrid-2 conformation while Phen-DC3 and 360A-Br induce the transition of hybrid-1 and hybrid-2 to the structure with characteristics of antiparallel or hybrid-3 type conformation. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Toward fast feature adaptation and localization for real-time face recognition systems

NARCIS (Netherlands)

Zuo, F.; With, de P.H.N.; Ebrahimi, T.; Sikora, T.

2003-01-01

In a home environment, video surveillance employing face detection and recognition is attractive for new applications. Facial feature (e.g. eyes and mouth) localization in the face is an essential task for face recognition because it constitutes an indispensable step for face geometry normalization.

Action recognition is sensitive to the identity of the actor.

Science.gov (United States)

Ferstl, Ylva; Bülthoff, Heinrich; de la Rosa, Stephan

2017-09-01

Recognizing who is carrying out an action is essential for successful human interaction. The cognitive mechanisms underlying this ability are little understood and have been subject of discussions in embodied approaches to action recognition. Here we examine one solution, that visual action recognition processes are at least partly sensitive to the actor's identity. We investigated the dependency between identity information and action related processes by testing the sensitivity of neural action recognition processes to clothing and facial identity information with a behavioral adaptation paradigm. Our results show that action adaptation effects are in fact modulated by both clothing information and the actor's facial identity. The finding demonstrates that neural processes underlying action recognition are sensitive to identity information (including facial identity) and thereby not exclusively tuned to actions. We suggest that such response properties are useful to help humans in knowing who carried out an action. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Structural basis for AMPA receptor activation and ligand selectivity

DEFF Research Database (Denmark)

Hogner, A; Kastrup, Jette Sandholm Jensen; Jin, R

2002-01-01

Glutamate is the principal excitatory neurotransmitter within the mammalian CNS, playing an important role in many different functions in the brain such as learning and memory. In this study, a combination of molecular biology, X-ray structure determinations, as well as electrophysiology...... with Br-HIBO and ACPA have allowed us to explain the molecular mechanism behind this selectivity and to identify key residues for ligand recognition. The agonists induce the same degree of domain closure as AMPA, except for Br-HIBO, which shows a slightly lower degree of domain closure. An excellent...

Face recognition in securing optical telecom network equipment

International Nuclear Information System (INIS)

Ali, N.M.

2015-01-01

In this paper, face recognition is used with a microcontroller based hardware module to secure the telecommunication equipments like ONU (optical network units) or any other telecommunication equipment. The face recognition classifier value optimization adaption is deployed and in this scheme by increasing or decreasing the number of images in the database will automatically generate and adopt the classifier value for recognition of known and unknown persons. On recognizing and unknown persons. On recognizing an unknown person, the hardware module will send an SMS to the concerned security personnel for security preventive measures. (author)

Regulation mechanisms of the FLT3-ligand after irradiation

International Nuclear Information System (INIS)

Prat-Lepesant, M.

2005-06-01

The hematopoietic compartment is one of the most severely damaged after chemotherapy, radiotherapy or accidental irradiations. Whatever its origin, the resulting damage to the bone marrow remains difficult to evaluate. Thus, it would be of great interest to get a biological indicator of residual hematopoiesis in order to adapt the treatment to each clinical situation. Recent results indicated that the plasma Flt3 ligand concentration was increased in patients suffering from either acquired or induced aplasia, suggesting that Flt3 ligand might be useful as a biological indicator of bone marrow status. We thus followed in a mouse model as well as in several clinical situations the variations in plasma Flt3 ligand concentration, after either homogeneous or heterogeneous irradiations. These variations were correlated to the number of hematopoietic progenitors and to other parameters such as duration and depth of pancytopenia. The results indicated that the concentration of Flt3 ligand in the blood reflects the bone marrow status, and that the follow-up of plasma Flt3 ligand concentration could give predictive information about the bone marrow function and the duration and severity of pancytopenia and thrombocytopenia. Nevertheless, the clinical use of Flt3 ligand as a biological indicator of bone marrow damage require the knowledge of the mechanisms regulating the variations in plasma Flt3 ligand concentration. We thus developed a study in the mouse model. The results indicated that the variations in plasma Flt3 ligand variations were not solely due to a balance between its production by lymphoid cells and its consumption by hematopoietic cells. Moreover, we showed that T lymphocytes are not the main regulator of plasma Flt3 ligand concentration as previously suggested, and that other cell types, possibly including bone marrow stromal cells, might be strongly implicated. These results also suggest that the Flt3 ligand is a main systemic regulator of hematopoiesis

Developmental reversals in recognition memory in children and adults.

Science.gov (United States)

Gross, Julien; Gardiner, Beatrix; Hayne, Harlene

2016-01-01

Older members of a given species typically exhibit superior learning and memory abilities relative to younger members, however, the developmental difference does not always occur in this younger-to-older direction. Developmental reversals are thought to reflect adaptive responses to the unique challenges imposed by the infant's niche. In humans, identification of developmental reversals has largely been precluded because infants, children, and adults are rarely tested using the same experimental procedures. Here, we adapted the visual recognition memory task and tested 3-year-olds and adults using one set of child-oriented stimuli and one set of adult-orientated stimuli. When tested immediately, children and adults exhibited recognition memory for both stimuli. When tested after a 1-week delay, children exhibited recognition memory for the child-oriented stimuli, but not for the adult-oriented stimuli and adults exhibited recognition memory for the adult-oriented stimuli, but not for the child-oriented stimuli. These data have important implications for current theories of memory development. © 2015 Wiley Periodicals, Inc.

Hypergraph-Based Recognition Memory Model for Lifelong Experience

Science.gov (United States)

2014-01-01

Cognitive agents are expected to interact with and adapt to a nonstationary dynamic environment. As an initial process of decision making in a real-world agent interaction, familiarity judgment leads the following processes for intelligence. Familiarity judgment includes knowing previously encoded data as well as completing original patterns from partial information, which are fundamental functions of recognition memory. Although previous computational memory models have attempted to reflect human behavioral properties on the recognition memory, they have been focused on static conditions without considering temporal changes in terms of lifelong learning. To provide temporal adaptability to an agent, in this paper, we suggest a computational model for recognition memory that enables lifelong learning. The proposed model is based on a hypergraph structure, and thus it allows a high-order relationship between contextual nodes and enables incremental learning. Through a simulated experiment, we investigate the optimal conditions of the memory model and validate the consistency of memory performance for lifelong learning. PMID:25371665

Pseudomonas evades immune recognition of flagellin in both mammals and plants.

Directory of Open Access Journals (Sweden)

Bart W Bardoel

2011-08-01

Full Text Available The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5 in mammals and flagellin-sensitive 2 (FLS2 in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR antagonists, we screened bacterial supernatants and identified alkaline protease (AprA of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants.

Sampling protein motion and solvent effect during ligand binding

Science.gov (United States)

Limongelli, Vittorio; Marinelli, Luciana; Cosconati, Sandro; La Motta, Concettina; Sartini, Stefania; Mugnaini, Laura; Da Settimo, Federico; Novellino, Ettore; Parrinello, Michele

2012-01-01

An exhaustive description of the molecular recognition mechanism between a ligand and its biological target is of great value because it provides the opportunity for an exogenous control of the related process. Very often this aim can be pursued using high resolution structures of the complex in combination with inexpensive computational protocols such as docking algorithms. Unfortunately, in many other cases a number of factors, like protein flexibility or solvent effects, increase the degree of complexity of ligand/protein interaction and these standard techniques are no longer sufficient to describe the binding event. We have experienced and tested these limits in the present study in which we have developed and revealed the mechanism of binding of a new series of potent inhibitors of Adenosine Deaminase. We have first performed a large number of docking calculations, which unfortunately failed to yield reliable results due to the dynamical character of the enzyme and the complex role of the solvent. Thus, we have stepped up the computational strategy using a protocol based on metadynamics. Our approach has allowed dealing with protein motion and solvation during ligand binding and finally identifying the lowest energy binding modes of the most potent compound of the series, 4-decyl-pyrazolo[1,5-a]pyrimidin-7-one. PMID:22238423

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Heracleous Panikos

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

The recognition heuristic: A decade of research

Directory of Open Access Journals (Sweden)

Gerd Gigerenzer

2011-02-01

Full Text Available The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein and Gigerenzer, 1999, 2002, including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.

Synthesis, Crystal Structure and Luminescent Property of A Novel Cd(II) Coordination Polymer with Bis-imidazole Ligand

International Nuclear Information System (INIS)

Zhou, Yong Hong

2013-01-01

The key to the successful design of metal-organic coordination polymers is the judicious selection of organic ligand. Recently, polydentate aromatic nitrogen heterocyclic ligands with five-membered rings have been well-studied in the construction of supramolecular structure for their N-coordinated sites apt to coordinating to transition metals. Similar to six-membered N-heterocyclic ligands, the azole-based five-membered N-heterocyclic ligands, such as imidazoles, triazoles and tetrazoles have been extensively employed in the construction of various coordination polymers with diverse topologies and interesting properties. The bis(azole) ligands in which N-donor azole rings (imidazole, triazole, or tetrazole) are separated by alkyl, (CH 2 ) n , spacers are good choices for flexible bridging ligands. The conformational flexibility of the spacers makes the ligands adaptable to various coordination networks with one-, two-, and three dimensional structures

The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.

Directory of Open Access Journals (Sweden)

Xiliang Zheng

2015-04-01

Full Text Available We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity, the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics.

The Role of Higher Level Adaptive Coding Mechanisms in the Development of Face Recognition

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Pimperton, Hannah; Pellicano, Elizabeth; Jeffery, Linda; Rhodes, Gillian

2009-01-01

DevDevelopmental improvements in face identity recognition ability are widely documented, but the source of children's immaturity in face recognition remains unclear. Differences in the way in which children and adults visually represent faces might underlie immaturities in face recognition. Recent evidence of a face identity aftereffect (FIAE),…

A real-time control system of gene expression using ligand-bound nucleic acid aptamer for metabolic engineering.

Science.gov (United States)

Wang, Jing; Cui, Xun; Yang, Le; Zhang, Zhe; Lv, Liping; Wang, Haoyuan; Zhao, Zhenmin; Guan, Ningzi; Dong, Lichun; Chen, Rachel

2017-07-01

Artificial control of bio-functions through regulating gene expression is one of the most important and attractive technologies to build novel living systems that are useful in the areas of chemical synthesis, nanotechnology, pharmacology, cell biology. Here, we present a novel real-time control system of gene regulation that includes an enhancement element by introducing duplex DNA aptamers upstream promoter and a repression element by introducing a RNA aptamer upstream ribosome binding site. With the presence of ligands corresponding to the DNA aptamers, the expression of the target gene can be potentially enhanced at the transcriptional level by strengthening the recognition capability of RNAP to the recognition region and speeding up the separation efficiency of the unwinding region due to the induced DNA bubble around the thrombin-bound aptamers; while with the presence of RNA aptamer ligand, the gene expression can be repressed at the translational level by weakening the recognition capability of ribosome to RBS due to the shielding of RBS by the formed aptamer-ligand complex upstream RBS. The effectiveness and potential utility of the developed gene regulation system were demonstrated by regulating the expression of ecaA gene in the cell-free systems. The realistic metabolic engineering application of the system has also tested by regulating the expression of mgtC gene and thrombin cDNA in Escherichia coli JD1021 for controlling metabolic flux and improving thrombin production, verifying that the real-time control system of gene regulation is able to realize the dynamic regulation of gene expression with potential applications in bacterial physiology studies and metabolic engineering. Copyright © 2017. Published by Elsevier Inc.

@TOME-2: a new pipeline for comparative modeling of protein–ligand complexes

Science.gov (United States)

Pons, Jean-Luc; Labesse, Gilles

2009-01-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein–protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein–ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/ PMID:19443448

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

Science.gov (United States)

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

Goal-seeking neural net for recall and recognition

Science.gov (United States)

Omidvar, Omid M.

1990-07-01

Neural networks have been used to mimic cognitive processes which take place in animal brains. The learning capability inherent in neural networks makes them suitable candidates for adaptive tasks such as recall and recognition. The synaptic reinforcements create a proper condition for adaptation, which results in memorization, formation of perception, and higher order information processing activities. In this research a model of a goal seeking neural network is studied and the operation of the network with regard to recall and recognition is analyzed. In these analyses recall is defined as retrieval of stored information where little or no matching is involved. On the other hand recognition is recall with matching; therefore it involves memorizing a piece of information with complete presentation. This research takes the generalized view of reinforcement in which all the signals are potential reinforcers. The neuronal response is considered to be the source of the reinforcement. This local approach to adaptation leads to the goal seeking nature of the neurons as network components. In the proposed model all the synaptic strengths are reinforced in parallel while the reinforcement among the layers is done in a distributed fashion and pipeline mode from the last layer inward. A model of complex neuron with varying threshold is developed to account for inhibitory and excitatory behavior of real neuron. A goal seeking model of a neural network is presented. This network is utilized to perform recall and recognition tasks. The performance of the model with regard to the assigned tasks is presented.

Embedded face recognition using cascaded structures

NARCIS (Netherlands)

Zuo, F.

2006-01-01

During the past few years, there is an increasing demand for smart devices in consumer electronics. These smart devices should be capable of consciously sensing their surroundings and adapting their services according to their environments. Face recognition provides a natural visual interface for

Starch Catabolism by a Prominent Human Gut Symbiont Is Directed by the Recognition of Amylose Helices

Energy Technology Data Exchange (ETDEWEB)

Koropatkin, Nicole M.; Martens, Eric C.; Gordon, Jeffrey I.; Smith, Thomas J. (WU); (Danforth)

2009-01-12

The human gut microbiota performs functions that are not encoded in our Homo sapiens genome, including the processing of otherwise undigestible dietary polysaccharides. Defining the structures of proteins involved in the import and degradation of specific glycans by saccharolytic bacteria complements genomic analysis of the nutrient-processing capabilities of gut communities. Here, we describe the atomic structure of one such protein, SusD, required for starch binding and utilization by Bacteroides thetaiotaomicron, a prominent adaptive forager of glycans in the distal human gut microbiota. The binding pocket of this unique {alpha}-helical protein contains an arc of aromatic residues that complements the natural helical structure of starch and imposes this conformation on bound maltoheptaose. Furthermore, SusD binds cyclic oligosaccharides with higher affinity than linear forms. The structures of several SusD/oligosaccharide complexes reveal an inherent ligand recognition plasticity dominated by the three-dimensional conformation of the oligosaccharides rather than specific interactions with the composite sugars.

Heterobifunctional crosslinkers for tethering single ligand molecules to scanning probes

International Nuclear Information System (INIS)

Riener, Christian K.; Kienberger, Ferry; Hahn, Christoph D.; Buchinger, Gerhard M.; Egwim, Innocent O.C.; Haselgruebler, Thomas; Ebner, Andreas; Romanin, Christoph; Klampfl, Christian; Lackner, Bernd; Prinz, Heino; Blaas, Dieter; Hinterdorfer, Peter; Gruber, Hermann J.

2003-01-01

Single molecule recognition force microscopy (SMRFM) is a versatile atomic force microscopy (AFM) method to probe specific interactions of cognitive molecules on the single molecule level. It allows insights to be gained into interaction potentials and kinetic barriers and is capable of mapping interaction sites with nm positional accuracy. These applications require a ligand to be attached to the AFM tip, preferably by a distensible poly(ethylene glycol) (PEG) chain between the measuring tip and the ligand molecule. The PEG chain greatly facilitates specific binding of the ligand to immobile receptor sites on the sample surface. The present study contributes to tip-PEG-ligand tethering in three ways: (i) a convenient synthetic route was found to prepare NH 2 -PEG-COOH which is the key intermediate for long heterobifunctional crosslinkers; (ii) a variety of heterobifunctional PEG derivatives for tip-PEG-ligand linking were prepared from NH 2 -PEG-COOH; (iii) in particular, a new PEG crosslinker with one thiol-reactive end and one terminal nitrilotriacetic acid (NTA) group was synthesized and successfully used to tether His 6 -tagged protein molecules to AFM tips via noncovalent NTA-Ni 2+ -His 6 bridges. The new crosslinker was applied to link a recombinant His 6 -tagged fragment of the very-low density lipoprotein receptor to the AFM tip whereupon specific docking to the capsid of human rhinovirus particles was observed by force microscopy. In a parallel study, the specific interaction of the small GTPase Ran with the nuclear import receptor importin β1 was studied in detail by SMRFM, using the new crosslinker to link His 6 -tagged Ran to the measuring tip [Nat. Struct. Biol. (2003), 10, 553-557

A fast, open source implementation of adaptive biasing potentials uncovers a ligand design strategy for the chromatin regulator BRD4

Science.gov (United States)

Dickson, Bradley M.; de Waal, Parker W.; Ramjan, Zachary H.; Xu, H. Eric; Rothbart, Scott B.

2016-10-01

In this communication we introduce an efficient implementation of adaptive biasing that greatly improves the speed of free energy computation in molecular dynamics simulations. We investigated the use of accelerated simulations to inform on compound design using a recently reported and clinically relevant inhibitor of the chromatin regulator BRD4 (bromodomain-containing protein 4). Benchmarking on our local compute cluster, our implementation achieves up to 2.5 times more force calls per day than plumed2. Results of five 1 μs-long simulations are presented, which reveal a conformational switch in the BRD4 inhibitor between a binding competent and incompetent state. Stabilization of the switch led to a -3 kcal/mol improvement of absolute binding free energy. These studies suggest an unexplored ligand design principle and offer new actionable hypotheses for medicinal chemistry efforts against this druggable epigenetic target class.

Functions of galectins as 'self/non-self'-recognition and effector factors.

Science.gov (United States)

Vasta, Gerardo R; Feng, Chiguang; González-Montalbán, Nuria; Mancini, Justin; Yang, Lishi; Abernathy, Kelsey; Frost, Graeme; Palm, Cheyenne

2017-07-31

Carbohydrate structures on the cell surface encode complex information that through specific recognition by carbohydrate-binding proteins (lectins) modulates interactions between cells, cells and the extracellular matrix, or mediates recognition of potential microbial pathogens. Galectins are a family of ß-galactoside-binding lectins, which are evolutionary conserved and have been identified in most organisms, from fungi to invertebrates and vertebrates, including mammals. Since their discovery in the 1970s, their biological roles, initially understood as limited to recognition of endogenous carbohydrate ligands in embryogenesis and development, have expanded in recent years by the discovery of their roles in tissue repair and regulation of immune homeostasis. More recently, evidence has accumulated to support the notion that galectins can also bind glycans on the surface of potentially pathogenic microbes, and function as recognition and effector factors in innate immunity, thus establishing a new paradigm. Furthermore, some parasites 'subvert' the recognition roles of the vector/host galectins for successful attachment or invasion. These recent findings have revealed a striking functional diversification in this structurally conserved lectin family. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Recognition of extracellular bacteria by NLRs and its role in the development of adaptive immunity

Directory of Open Access Journals (Sweden)

Jonathan eFerrand

2013-10-01

Full Text Available Innate immune recognition of bacteria is the first requirement for mounting an effective immune response able to control infection. Over the previous decade, the general paradigm was that extracellular bacteria were only sensed by cell surface-expressed Toll-like receptors (TLRs, whereas cytoplasmic sensors, including members of the Nod-like receptor (NLR family, were specific to pathogens capable of breaching the host cell membrane. It has become apparent, however, that intracellular innate immune molecules, such as the NLRs, play key roles in the sensing of not only intracellular, but also extracellular bacterial pathogens or their components. In this review, we will discuss the various mechanisms used by bacteria to activate NLR signaling in host cells. These mechanisms include bacterial secretion systems, pore-forming toxins and outer membrane vesicles. We will then focus on the influence of NLR activation on the development of adaptive immune responses in different cell types.

Spatio-temporal regulation of Hsp90-ligand complex leads to immune activation.

Directory of Open Access Journals (Sweden)

Yasuaki eTamura

2016-05-01

Full Text Available Hsp90 is the most abundant cytosolic HSP and is known to act as a molecular chaperone. We found that an Hsp90-cancer antigen peptide complex was efficiently cross-presented by human monocyte-derived dendritic cells and induced peptide-specific cytotoxic T lymphocytes. Furthermore, we observed that the internalized Hsp90-peptide complex was strictly sorted to the Rab5+, EEA1+ static early endosome and the Hsp90-chaperoned peptide was processed and bound to MHC class I molecules through a endosome-recycling pathway. We also found that extracellular Hsp90 complexed with CpG-A or self-DNA stimulates production of a large amount of IFN-α from pDCs via static early endosome targeting. Thus, extracellular Hsp90 can target the antigen or nucleic acid to a static early endosome by spatio-temporal regulation. Moreover, we showed that Hsp90 associates with and delivers TLR7/9 from the ER to early endosomes for ligand recognition. Hsp90 inhibitor, geldanamycin derivative inhibited the Hsp90 association with TLR7/9, resulting in inhibition IFN-α production, leading to improvement of SLE symptoms. Interstingly, we observed that serum Hsp90 is clearly increased in patients with active SLE compared with that in patients with inactive disease. Serum Hsp90 detected in SLE patients binds to self-DNA and/or anti-DNA Ab, thus leading to stimulation of pDCs to produce IFN-α. Thus, Hsp90 plays a crucial role in the pathogenesis of SLE and that an Hsp90 inhibitor will therefore provide a new therapeutic approach to SLE and other nucleic acid-related autoimmune diseases. We will discuss how spatio-temporal regulation of Hsp90-ligand complexes within antigen-presenting cells affects the innate immunity and adaptive immunity.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Hiroshi Saruwatari

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a 93.9% word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Ligand Access Channels in Cytochrome P450 Enzymes: A Review

Directory of Open Access Journals (Sweden)

Philippe Urban

2018-05-01

Full Text Available Quantitative structure-activity relationships may bring invaluable information on structural elements of both enzymes and substrates that, together, govern substrate specificity. Buried active sites in cytochrome P450 enzymes are connected to the solvent by a network of channels exiting at the distal surface of the protein. This review presents different in silico tools that were developed to uncover such channels in P450 crystal structures. It also lists some of the experimental evidence that actually suggest that these predicted channels might indeed play a critical role in modulating P450 functions. Amino acid residues at the entrance of the channels may participate to a first global ligand recognition of ligands by P450 enzymes before they reach the buried active site. Moreover, different P450 enzymes show different networks of predicted channels. The plasticity of P450 structures is also important to take into account when looking at how channels might play their role.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

Science.gov (United States)

Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites.

Science.gov (United States)

Vukovic, Sinisa; Brennan, Paul E; Huggins, David J

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Importance of the extracellular loops in G protein-coupled receptors for ligand recognition and receptor activation.

Science.gov (United States)

Peeters, M C; van Westen, G J P; Li, Q; IJzerman, A P

2011-01-01

G protein-coupled receptors (GPCRs) are the major drug target of medicines on the market today. Therefore, much research is and has been devoted to the elucidation of the function and three-dimensional structure of this large family of membrane proteins, which includes multiple conserved transmembrane domains connected by intra- and extracellular loops. In the last few years, the less conserved extracellular loops have garnered increasing interest, particularly after the publication of several GPCR crystal structures that clearly show the extracellular loops to be involved in ligand binding. This review will summarize the recent progress made in the clarification of the ligand binding and activation mechanism of class-A GPCRs and the role of extracellular loops in this process. Copyright © 2010 Elsevier Ltd. All rights reserved.

Recent progress in invariant pattern recognition

Science.gov (United States)

Arsenault, Henri H.; Chang, S.; Gagne, Philippe; Gualdron Gonzalez, Oscar

1996-12-01

We present some recent results in invariant pattern recognition, including methods that are invariant under two or more distortions of position, orientation and scale. There are now a few methods that yield good results under changes of both rotation and scale. Some new methods are introduced. These include locally adaptive nonlinear matched filters, scale-adapted wavelet transforms and invariant filters for disjoint noise. Methods using neural networks will also be discussed, including an optical method that allows simultaneous classification of multiple targets.

Cross-sensor iris recognition through kernel learning.

Science.gov (United States)

Pillai, Jaishanker K; Puertas, Maria; Chellappa, Rama

2014-01-01

Due to the increasing popularity of iris biometrics, new sensors are being developed for acquiring iris images and existing ones are being continuously upgraded. Re-enrolling users every time a new sensor is deployed is expensive and time-consuming, especially in applications with a large number of enrolled users. However, recent studies show that cross-sensor matching, where the test samples are verified using data enrolled with a different sensor, often lead to reduced performance. In this paper, we propose a machine learning technique to mitigate the cross-sensor performance degradation by adapting the iris samples from one sensor to another. We first present a novel optimization framework for learning transformations on iris biometrics. We then utilize this framework for sensor adaptation, by reducing the distance between samples of the same class, and increasing it between samples of different classes, irrespective of the sensors acquiring them. Extensive evaluations on iris data from multiple sensors demonstrate that the proposed method leads to improvement in cross-sensor recognition accuracy. Furthermore, since the proposed technique requires minimal changes to the iris recognition pipeline, it can easily be incorporated into existing iris recognition systems.

Research on operation and maintenance support system adaptive to human recognition and understanding in human-centered plant

International Nuclear Information System (INIS)

Numano, Masayoshi; Matsuoka, Takeshi; Mitomo, N.

2004-01-01

As a human-centered plant, advanced nuclear power plant needs appropriate role sharing between human and mobile intelligent agents. Human-machine cooperation for plant operation and maintenance activities is also required with an advanced interface. Plant's maintenance is programmed using mobile robots working under the radiation environments instead of human beings. Operation and maintenance support system adaptive to human recognition and understanding should be developed to establish adequate human and machine interface so as to induce human capabilities to the full and enable human to take responsibility for plan's operation. Plant's operation and maintenance can be cooperative activities between human and intelligent automonous agents having surveillance and control functions. Infrastructure of multi-agent simulation system for the support system has been investigated and developed based on work plans derived from the scheduler. (T. Tanaka)

Equilibrium dialysis-ligand exchange: adaptation of the method for determination of conditional stability constants of radionuclide-fulvic acid complexes

International Nuclear Information System (INIS)

Glaus, M.A.; Hummel, W.; Van Loon, L.R.

1995-01-01

The equilibrium dialysis-ligand exchange technique (EDLE) is used to determine conditional stability constants for the complexation of metal ions with humic acid, particularly in high pH solutions. Here, this technique has been adapted to measure conditional stability constants with fulvic acid. Fulvic acid permeates across all membranes during the experiment. The quantities involved therefore have to be determined analytically and taken into account when calculating the conditional stability constants. Co(II) and Laurentian Soil fulvic (LFA) acid were selected as a test system in order to investigate the time scale required to establish chemical and diffusion equilibria. After an incubation time of approximately two days, the conditional stability constants measured for the formation of Co-LFA-complexes are not time dependent, although across the whole time period investigated, LFA was still diffusing in increasing amounts across the dialysis membrane. This work demonstrates that the modified EDLE technique can be used in the determination of conditional metal stability constants of fulvic acid. (authors)

Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free Energy.

Science.gov (United States)

Duan, Lili; Liu, Xiao; Zhang, John Z H

2016-05-04

Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.

Cough Recognition Based on Mel Frequency Cepstral Coefficients and Dynamic Time Warping

Science.gov (United States)

Zhu, Chunmei; Liu, Baojun; Li, Ping

Cough recognition provides important clinical information for the treatment of many respiratory diseases, but the assessment of cough frequency over a long period of time remains unsatisfied for either clinical or research purpose. In this paper, according to the advantage of dynamic time warping (DTW) and the characteristic of cough recognition, an attempt is made to adapt DTW as the recognition algorithm for cough recognition. The process of cough recognition based on mel frequency cepstral coefficients (MFCC) and DTW is introduced. Experiment results of testing samples from 3 subjects show that acceptable performances of cough recognition are obtained by DTW with a small training set.

Two novel mixed-ligand complexes containing organosulfonate ligands.

Science.gov (United States)

Li, Mingtian; Huang, Jun; Zhou, Xuan; Fang, Hua; Ding, Liyun

2008-07-01

The structures reported herein, viz. bis(4-aminonaphthalene-1-sulfonato-kappaO)bis(4,5-diazafluoren-9-one-kappa(2)N,N')copper(II), [Cu(C(10)H(8)NO(3)S)(2)(C(11)H(6)N(2)O)(2)], (I), and poly[[[diaquacadmium(II)]-bis(mu-4-aminonaphthalene-1-sulfonato)-kappa(2)O:N;kappa(2)N:O] dihydrate], {[Cd(C(10)H(8)NO(3)S)(2)(H(2)O)(2)].2H(2)O}(n), (II), are rare examples of sulfonate-containing complexes where the anion does not fulfill a passive charge-balancing role, but takes an active part in coordination as a monodentate and/or bridging ligand. Monomeric complex (I) possesses a crystallographic inversion center at the Cu(II) atom, and the asymmetric unit contains one-half of a Cu atom, one complete 4-aminonaphthalene-1-sulfonate (ans) ligand and one 4,5-diazafluoren-9-one (DAFO) ligand. The Cu(II) atom has an elongated distorted octahedral coordination geometry formed by two O atoms from two monodentate ans ligands and by four N atoms from two DAFO molecules. Complex (II) is polymeric and its crystal structure is built up by one-dimensional chains and solvent water molecules. Here also the cation (a Cd(II) atom) lies on a crystallographic inversion center and adopts a slightly distorted octahedral geometry. Each ans anion serves as a bridging ligand linking two Cd(II) atoms into one-dimensional infinite chains along the [010] direction, with each Cd(II) center coordinated by four ans ligands via O and N atoms and by two aqua ligands. In both structures, there are significant pi-pi stacking interactions between adjacent ligands and hydrogen bonds contribute to the formation of two- and three-dimensional networks.

The recognition heuristic: a review of theory and tests.

Science.gov (United States)

Pachur, Thorsten; Todd, Peter M; Gigerenzer, Gerd; Schooler, Lael J; Goldstein, Daniel G

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect - the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference).

The Recognition Heuristic: A Review of Theory and Tests

Directory of Open Access Journals (Sweden)

Thorsten ePachur

2011-07-01

Full Text Available The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a that recognition is often an ecologically valid cue; (b that people often follow recognition when making inferences; (c that recognition supersedes further cue knowledge; (d that its use can produce the less-is-more effect—the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference.

The Recognition Heuristic: A Review of Theory and Tests

Science.gov (United States)

Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

Recognition of GPCRs by peptide ligands and membrane compartments theory: structural studies of endogenous peptide hormones in membrane environment.

Science.gov (United States)

Sankararamakrishnan, Ramasubbu

2006-04-01

One of the largest family of cell surface proteins, G-protein coupled receptors (GPCRs) regulate virtually all known physiological processes in mammals. With seven transmembrane segments, they respond to diverse range of extracellular stimuli and represent a major class of drug targets. Peptidergic GPCRs use endogenous peptides as ligands. To understand the mechanism of GPCR activation and rational drug design, knowledge of three-dimensional structure of receptor-ligand complex is important. The endogenous peptide hormones are often short, flexible and completely disordered in aqueous solution. According to "Membrane Compartments Theory", the flexible peptide binds to the membrane in the first step before it recognizes its receptor and the membrane-induced conformation is postulated to bind to the receptor in the second step. Structures of several peptide hormones have been determined in membrane-mimetic medium. In these studies, micelles, reverse micelles and bicelles have been used to mimic the cell membrane environment. Recently, conformations of two peptide hormones have also been studied in receptor-bound form. Membrane environment induces stable secondary structures in flexible peptide ligands and membrane-induced peptide structures have been correlated with their bioactivity. Results of site-directed mutagenesis, spectroscopy and other experimental studies along with the conformations determined in membrane medium have been used to interpret the role of individual residues in the peptide ligand. Structural differences of membrane-bound peptides that belong to the same family but differ in selectivity are likely to explain the mechanism of receptor selectivity and specificity of the ligands. Knowledge of peptide 3D structures in membrane environment has potential applications in rational drug design.

(125I)LSD labels 5-TCsub(IC) recognition sites in pig choriod plexus membranes. Comparison with (3H)mesulergine and (3H)5-HT binding

International Nuclear Information System (INIS)

Hoyer, D.; Srivatsa, S.; Pazos, A.; Engel, G.; Palacios, J.M.

1986-01-01

The mammalian choroid plexus is enriched in a newly described serotonin recognition site, the binding characteristics of ( 125 I)LSD, ( 3 H)mesulergine and ( 3 H)serotonin to pig choroid plexus membranes were compared. These ligands labelled with high affinity a similar number of sites. The binding profiles of the sites labelled with these radioligands are indistinguishable as illustrated by highly significant correlation parameters. These sites are very similar to those labelled by Nsub(I)-methyl-2-( 125 I)LSD in pig and rat choroid plexus membranes. The data demonstrate that these ligands label 5-HTsub(IC) recognition sites in the pig and rat choroid plexus membranes. (author)

Unsupervised domain adaptation techniques based on auto-encoder for non-stationary EEG-based emotion recognition.

Science.gov (United States)

Chai, Xin; Wang, Qisong; Zhao, Yongping; Liu, Xin; Bai, Ou; Li, Yongqiang

2016-12-01

In electroencephalography (EEG)-based emotion recognition systems, the distribution between the training samples and the testing samples may be mismatched if they are sampled from different experimental sessions or subjects because of user fatigue, different electrode placements, varying impedances, etc. Therefore, it is difficult to directly classify the EEG patterns with a conventional classifier. The domain adaptation method, which is aimed at obtaining a common representation across training and test domains, is an effective method for reducing the distribution discrepancy. However, the existing domain adaptation strategies either employ a linear transformation or learn the nonlinearity mapping without a consistency constraint; they are not sufficiently powerful to obtain a similar distribution from highly non-stationary EEG signals. To address this problem, in this paper, a novel component, called the subspace alignment auto-encoder (SAAE), is proposed. Taking advantage of both nonlinear transformation and a consistency constraint, we combine an auto-encoder network and a subspace alignment solution in a unified framework. As a result, the source domain can be aligned with the target domain together with its class label, and any supervised method can be applied to the new source domain to train a classifier for classification in the target domain, as the aligned source domain follows a distribution similar to that of the target domain. We compared our SAAE method with six typical approaches using a public EEG dataset containing three affective states: positive, neutral, and negative. Subject-to-subject and session-to-session evaluations were performed. The subject-to-subject experimental results demonstrate that our component achieves a mean accuracy of 77.88% in comparison with a state-of-the-art method, TCA, which achieves 73.82% on average. In addition, the average classification accuracy of SAAE in the session-to-session evaluation for all the 15 subjects

Monoclonal antibody-assisted structure-function analysis of the carbohydrate recognition domain of surfactant protein D

DEFF Research Database (Denmark)

Hartshorn, Kevan L; White, Mitchell R; Rynkiewicz, Michael

2010-01-01

Surfactant protein D (SP-D) plays important roles in host defense against a variety of pathogens including influenza A virus (IAV). Ligand binding by SP-D is mediated by the trimeric neck and carbohydrate recognition domain (NCRD). We used monoclonal antibodies (mAbs) against human SP-D and a panel...

Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including protein markers, pathogens and cellular debris

Science.gov (United States)

Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM

2009-06-02

An assay element is described including recognition ligands bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

AutoSite: an automated approach for pseudo-ligands prediction—from ligand-binding sites identification to predicting key ligand atoms

Science.gov (United States)

Ravindranath, Pradeep Anand; Sanner, Michel F.

2016-01-01

Motivation: The identification of ligand-binding sites from a protein structure facilitates computational drug design and optimization, and protein function assignment. We introduce AutoSite: an efficient software tool for identifying ligand-binding sites and predicting pseudo ligand corresponding to each binding site identified. Binding sites are reported as clusters of 3D points called fills in which every point is labelled as hydrophobic or as hydrogen bond donor or acceptor. From these fills AutoSite derives feature points: a set of putative positions of hydrophobic-, and hydrogen-bond forming ligand atoms. Results: We show that AutoSite identifies ligand-binding sites with higher accuracy than other leading methods, and produces fills that better matches the ligand shape and properties, than the fills obtained with a software program with similar capabilities, AutoLigand. In addition, we demonstrate that for the Astex Diverse Set, the feature points identify 79% of hydrophobic ligand atoms, and 81% and 62% of the hydrogen acceptor and donor hydrogen ligand atoms interacting with the receptor, and predict 81.2% of water molecules mediating interactions between ligand and receptor. Finally, we illustrate potential uses of the predicted feature points in the context of lead optimization in drug discovery projects. Availability and Implementation: http://adfr.scripps.edu/AutoDockFR/autosite.html Contact: sanner@scripps.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27354702

Siderocalin-mediated recognition, sensitization, and cellular uptake of actinides.

Science.gov (United States)

Allred, Benjamin E; Rupert, Peter B; Gauny, Stacey S; An, Dahlia D; Ralston, Corie Y; Sturzbecher-Hoehne, Manuel; Strong, Roland K; Abergel, Rebecca J

2015-08-18

Synthetic radionuclides, such as the transuranic actinides plutonium, americium, and curium, present severe health threats as contaminants, and understanding the scope of the biochemical interactions involved in actinide transport is instrumental in managing human contamination. Here we show that siderocalin, a mammalian siderophore-binding protein from the lipocalin family, specifically binds lanthanide and actinide complexes through molecular recognition of the ligands chelating the metal ions. Using crystallography, we structurally characterized the resulting siderocalin-transuranic actinide complexes, providing unprecedented insights into the biological coordination of heavy radioelements. In controlled in vitro assays, we found that intracellular plutonium uptake can occur through siderocalin-mediated endocytosis. We also demonstrated that siderocalin can act as a synergistic antenna to sensitize the luminescence of trivalent lanthanide and actinide ions in ternary protein-ligand complexes, dramatically increasing the brightness and efficiency of intramolecular energy transfer processes that give rise to metal luminescence. Our results identify siderocalin as a potential player in the biological trafficking of f elements, but through a secondary ligand-based metal sequestration mechanism. Beyond elucidating contamination pathways, this work is a starting point for the design of two-stage biomimetic platforms for photoluminescence, separation, and transport applications.

Diversity in peptide recognition by the SH2 domain of SH2B1.

Science.gov (United States)

McKercher, Marissa A; Guan, Xiaoyang; Tan, Zhongping; Wuttke, Deborah S

2018-02-01

SH2B1 is a multidomain protein that serves as a key adaptor to regulate numerous cellular events, such as insulin, leptin, and growth hormone signaling pathways. Many of these protein-protein interactions are mediated by the SH2 domain of SH2B1, which recognizes ligands containing a phosphorylated tyrosine (pY), including peptides derived from janus kinase 2, insulin receptor, and insulin receptor substrate-1 and -2. Specificity for the SH2 domain of SH2B1 is conferred in these ligands either by a hydrophobic or an acidic side chain at the +3 position C-terminal to the pY. This specificity for chemically disparate species suggests that SH2B1 relies on distinct thermodynamic or structural mechanisms to bind to peptides. Using binding and structural strategies, we have identified unique thermodynamic signatures for each peptide binding mode, and several SH2B1 residues, including K575 and R578, that play distinct roles in peptide binding. The high-resolution structure of the SH2 domain of SH2B1 further reveals conformationally plastic protein loops that may contribute to the ability of the protein to recognize dissimilar ligands. Together, numerous hydrophobic and electrostatic interactions, in addition to backbone conformational flexibility, permit the recognition of diverse peptides by SH2B1. An understanding of this expanded peptide recognition will allow for the identification of novel physiologically relevant SH2B1/peptide interactions, which can contribute to the design of obesity and diabetes pharmaceuticals to target the ligand-binding interface of SH2B1 with high specificity. © 2017 Wiley Periodicals, Inc.

Applications of pattern recognition theory in diagnostics of nuclear power plants

International Nuclear Information System (INIS)

Cech, J.

1982-01-01

The questions are discussed of the application of the theory of pattern recognition in the diagnostics of nuclear power plants. For the future use of recognition systems in the diagnostics of nuclear power plants it is obvious that like with other complex systems, optimal models will have to be used which will organize the optimal recognition algorithm. The conclusion is presented that for the needs of nuclear power plants special systems will be more suitable for pattern recognition than digital computers which are flexible and adaptible but have a lower decision rate, an insufficient working memory, complicated programs, etc. (Z.M.)

Liquid lens: advances in adaptive optics

Science.gov (United States)

Casey, Shawn Patrick

2010-12-01

'Liquid lens' technologies promise significant advancements in machine vision and optical communications systems. Adaptations for machine vision, human vision correction, and optical communications are used to exemplify the versatile nature of this technology. Utilization of liquid lens elements allows the cost effective implementation of optical velocity measurement. The project consists of a custom image processor, camera, and interface. The images are passed into customized pattern recognition and optical character recognition algorithms. A single camera would be used for both speed detection and object recognition.

Contributions of feature shapes and surface cues to the recognition and neural representation of facial identity.

Science.gov (United States)

Andrews, Timothy J; Baseler, Heidi; Jenkins, Rob; Burton, A Mike; Young, Andrew W

2016-10-01

A full understanding of face recognition will involve identifying the visual information that is used to discriminate different identities and how this is represented in the brain. The aim of this study was to explore the importance of shape and surface properties in the recognition and neural representation of familiar faces. We used image morphing techniques to generate hybrid faces that mixed shape properties (more specifically, second order spatial configural information as defined by feature positions in the 2D-image) from one identity and surface properties from a different identity. Behavioural responses showed that recognition and matching of these hybrid faces was primarily based on their surface properties. These behavioural findings contrasted with neural responses recorded using a block design fMRI adaptation paradigm to test the sensitivity of Haxby et al.'s (2000) core face-selective regions in the human brain to the shape or surface properties of the face. The fusiform face area (FFA) and occipital face area (OFA) showed a lower response (adaptation) to repeated images of the same face (same shape, same surface) compared to different faces (different shapes, different surfaces). From the behavioural data indicating the critical contribution of surface properties to the recognition of identity, we predicted that brain regions responsible for familiar face recognition should continue to adapt to faces that vary in shape but not surface properties, but show a release from adaptation to faces that vary in surface properties but not shape. However, we found that the FFA and OFA showed an equivalent release from adaptation to changes in both shape and surface properties. The dissociation between the neural and perceptual responses suggests that, although they may play a role in the process, these core face regions are not solely responsible for the recognition of facial identity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neurotrophins play differential roles in short and long-term recognition memory.

Science.gov (United States)

Callaghan, Charlotte K; Kelly, Aine M

2013-09-01

The neurotrophin family of proteins are believed to mediate various forms of synaptic plasticity in the adult brain. Here we have assessed the roles of these proteins in object recognition memory in the rat, using icv infusions of function-blocking antibodies or the tyrosine kinase antagonist, tyrphostin AG879, to block Trk receptors. We report that tyrphostin AG879 impairs both short-term and long-term recognition memory, indicating a requirement for Trk receptor activation in both processes. The effect of inhibition of each of the neurotrophins with activity-blocking neutralising antibodies was also tested. Treatment with anti-BDNF, anti-NGF or anti-NT4 had no effect on short-term memory, but blocked long-term recognition memory. Treatment with anti-NT3 had no effect on either process. We also assessed changes in expression of neurotrophins and their respective receptors in the hippocampus, dentate gyrus and perirhinal cortex over a 24 h period following training in the object recognition task. We observed time-dependent changes in expression of the Trk receptors and their ligands in the dentate gyrus and perirhinal cortex. The data are consistent with a pivotal role for neurotrophic factors in the expression of recognition memory. Copyright © 2013 Elsevier Inc. All rights reserved.

Potential New Ligand Systems for Binding Uranyl Ions in Seawater Environments

Energy Technology Data Exchange (ETDEWEB)

Arnold, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2014-12-13

Work began this quarter on a new project involving a combined computational and biosynthetic approach to selective recognition of uranyl ion in aqueous solution. This project exploits the results of computational studies to discover new ligand classes. Synthetic studies will follow to generate target systems for uranyl binding and determination of binding constants. The process will be iterative, with results from computation informing synthesis, and vice versa. The theme of the ligand classes to be examined initially will be biologically based. New phosphonate-containing α-amino acid N-carboxyanhydride (NCA) monomers were used recently to prepare well-defined phosphonate-containing poly-peptides and block copolypeptides. Our first approach is to utilize these phosphate- and phosphonate-containing NCAs for the coordination of uranyl. The work includes the laboratory-scale preparation of a series of NCAs and the full thermodynamic and spectroscopic characterization of the resulting uranyl complexes. We are also evaluating the sequestering activity in different physiological and environmental conditions of these copolymers as well as their biodegradability.

Misattribution, false recognition and the sins of memory.

Science.gov (United States)

Schacter, D L; Dodson, C S

2001-09-29

Memory is sometimes a troublemaker. Schacter has classified memory's transgressions into seven fundamental 'sins': transience, absent-mindedness, blocking, misattribution, suggestibility, bias and persistence. This paper focuses on one memory sin, misattribution, that is implicated in false or illusory recognition of episodes that never occurred. We present data from cognitive, neuropsychological and neuroimaging studies that illuminate aspects of misattribution and false recognition. We first discuss cognitive research examining possible mechanisms of misattribution associated with false recognition. We also consider ways in which false recognition can be reduced or avoided, focusing in particular on the role of distinctive information. We next turn to neuropsychological research concerning patients with amnesia and Alzheimer's disease that reveals conditions under which such patients are less susceptible to false recognition than are healthy controls, thus providing clues about the brain mechanisms that drive false recognition. We then consider neuroimaging studies concerned with the neural correlates of true and false recognition, examining when the two forms of recognition can and cannot be distinguished on the basis of brain activity. Finally, we argue that even though misattribution and other memory sins are annoying and even dangerous, they can also be viewed as by-products of adaptive features of memory.

Ligand Depot: a data warehouse for ligands bound to macromolecules.

Science.gov (United States)

Feng, Zukang; Chen, Li; Maddula, Himabindu; Akcan, Ozgur; Oughtred, Rose; Berman, Helen M; Westbrook, John

2004-09-01

Ligand Depot is an integrated data resource for finding information about small molecules bound to proteins and nucleic acids. The initial release (version 1.0, November, 2003) focuses on providing chemical and structural information for small molecules found as part of the structures deposited in the Protein Data Bank. Ligand Depot accepts keyword-based queries and also provides a graphical interface for performing chemical substructure searches. A wide variety of web resources that contain information on small molecules may also be accessed through Ligand Depot. Ligand Depot is available at http://ligand-depot.rutgers.edu/. Version 1.0 supports multiple operating systems including Windows, Unix, Linux and the Macintosh operating system. The current drawing tool works in Internet Explorer, Netscape and Mozilla on Windows, Unix and Linux.

Novel Techniques for Dialectal Arabic Speech Recognition

CERN Document Server

Elmahdy, Mohamed; Minker, Wolfgang

2012-01-01

Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and M...

Crystal Structures of Mouse CD1d-IGb3 Complex And Its Cognate Valpha14 T Cell Receptor Suggest a Model for Dual Recognition of Foreign And Self Glycolipids

Energy Technology Data Exchange (ETDEWEB)

Zajonc, D.M.; Saveage, P.B.; Bendelac, A.; Wilson, I.A.; Teyton, L.

2009-05-28

The semi-invariant Valpha14Jalpha18 T cell receptor (TCR) is expressed by regulatory NKT cells and has the unique ability to recognize chemically diverse ligands presented by CD1d. The crystal structure of CD1d complexed to a natural, endogenous ligand, isoglobotrihexosylceramide (iGb3), illustrates the extent of this diversity when compared to the binding of potent, exogenous ligands, such as alpha-galactosylceramide (alpha-GalCer). A single mode of recognition for these two classes of ligands would then appear problematic for a single T cell receptor. However, the Valpha14 TCR adopts two different conformations in the crystal where, in one configuration, the presence of a larger cavity between the two CDR3 regions could accommodate iGb3 and, in the other, a smaller cavity fits alpha-GalCer more snugly. Alternatively, the extended iGb3 headgroup could be 'squashed' upon docking of the TCR and accommodated between the CD1 and TCR surfaces. Thus, the same TCR may adopt alternative modes of recognition for these foreign and self-ligands for NKT cell activation.

Beyond the Matrix: The Many Non-ECM Ligands for Integrins

Directory of Open Access Journals (Sweden)

Bryce LaFoya

2018-02-01

Full Text Available The traditional view of integrins portrays these highly conserved cell surface receptors as mediators of cellular attachment to the extracellular matrix (ECM, and to a lesser degree, as coordinators of leukocyte adhesion to the endothelium. These canonical activities are indispensable; however, there is also a wide variety of integrin functions mediated by non-ECM ligands that transcend the traditional roles of integrins. Some of these unorthodox roles involve cell-cell interactions and are engaged to support immune functions such as leukocyte transmigration, recognition of opsonization factors, and stimulation of neutrophil extracellular traps. Other cell-cell interactions mediated by integrins include hematopoietic stem cell and tumor cell homing to target tissues. Integrins also serve as cell-surface receptors for various growth factors, hormones, and small molecules. Interestingly, integrins have also been exploited by a wide variety of organisms including viruses and bacteria to support infectious activities such as cellular adhesion and/or cellular internalization. Additionally, the disruption of integrin function through the use of soluble integrin ligands is a common strategy adopted by several parasites in order to inhibit blood clotting during hematophagy, or by venomous snakes to kill prey. In this review, we strive to go beyond the matrix and summarize non-ECM ligands that interact with integrins in order to highlight these non-traditional functions of integrins.

LiCABEDS II. Modeling of ligand selectivity for G-protein-coupled cannabinoid receptors.

Science.gov (United States)

Ma, Chao; Wang, Lirong; Yang, Peng; Myint, Kyaw Z; Xie, Xiang-Qun

2013-01-28

The cannabinoid receptor subtype 2 (CB2) is a promising therapeutic target for blood cancer, pain relief, osteoporosis, and immune system disease. The recent withdrawal of Rimonabant, which targets another closely related cannabinoid receptor (CB1), accentuates the importance of selectivity for the development of CB2 ligands in order to minimize their effects on the CB1 receptor. In our previous study, LiCABEDS (Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps) was reported as a generic ligand classification algorithm for the prediction of categorical molecular properties. Here, we report extension of the application of LiCABEDS to the modeling of cannabinoid ligand selectivity with molecular fingerprints as descriptors. The performance of LiCABEDS was systematically compared with another popular classification algorithm, support vector machine (SVM), according to prediction precision and recall rate. In addition, the examination of LiCABEDS models revealed the difference in structure diversity of CB1 and CB2 selective ligands. The structure determination from data mining could be useful for the design of novel cannabinoid lead compounds. More importantly, the potential of LiCABEDS was demonstrated through successful identification of newly synthesized CB2 selective compounds.

Impact of protein and ligand impurities on ITC-derived protein-ligand thermodynamics.

Science.gov (United States)

Grüner, Stefan; Neeb, Manuel; Barandun, Luzi Jakob; Sielaff, Frank; Hohn, Christoph; Kojima, Shun; Steinmetzer, Torsten; Diederich, François; Klebe, Gerhard

2014-09-01

The thermodynamic characterization of protein-ligand interactions by isothermal titration calorimetry (ITC) is a powerful tool in drug design, giving valuable insight into the interaction driving forces. ITC is thought to require protein and ligand solutions of high quality, meaning both the absence of contaminants as well as accurately determined concentrations. Ligands synthesized to deviating purity and protein of different pureness were titrated by ITC. Data curation was attempted also considering information from analytical techniques to correct stoichiometry. We used trypsin and tRNA-guanine transglycosylase (TGT), together with high affinity ligands to investigate the effect of errors in protein concentration as well as the impact of ligand impurities on the apparent thermodynamics. We found that errors in protein concentration did not change the thermodynamic properties obtained significantly. However, most ligand impurities led to pronounced changes in binding enthalpy. If protein binding of the respective impurity is not expected, the actual ligand concentration was corrected for and the thus revised data compared to thermodynamic properties obtained with the respective pure ligand. Even in these cases, we observed differences in binding enthalpy of about 4kJ⋅mol(-1), which is considered significant. Our results indicate that ligand purity is the critical parameter to monitor if accurate thermodynamic data of a protein-ligand complex are to be recorded. Furthermore, artificially changing fitting parameters to obtain a sound interaction stoichiometry in the presence of uncharacterized ligand impurities may lead to thermodynamic parameters significantly deviating from the accurate thermodynamic signature. Copyright © 2014 Elsevier B.V. All rights reserved.

Accessing Specific Peptide Recognition by Combinatorial Chemistry

DEFF Research Database (Denmark)

Li, Ming

Molecular recognition is at the basis of all processes for life, and plays a central role in many biological processes, such as protein folding, the structural organization of cells and organelles, signal transduction, and the immune response. Hence, my PhD project is entitled “Accessing Specific...... Peptide Recognition by Combinatorial Chemistry”. Molecular recognition is a specific interaction between two or more molecules through noncovalent bonding, such as hydrogen bonding, metal coordination, van der Waals forces, π−π, hydrophobic, or electrostatic interactions. The association involves kinetic....... Combinatorial chemistry was invented in 1980s based on observation of functional aspects of the adaptive immune system. It was employed for drug development and optimization in conjunction with high-throughput synthesis and screening. (chapter 2) Combinatorial chemistry is able to rapidly produce many thousands...

Selectivity in ligand binding to uranyl compounds: A synthetic, structural, thermodynamic and computational study

Energy Technology Data Exchange (ETDEWEB)

Arnold, John [Univ. of California, Berkeley, CA (United States)

2015-01-21

The uranyl cation (UO₂²⁺) is the most abundant form of uranium on the planet. It is estimated that 4.5 billion tons of uranium in this form exist in sea water. The ability to bind and extract the uranyl cation from aqueous solution while separating it from other elements would provide a limitless source of nuclear fuel. A large body of research concerns the selective recognition and extraction of uranyl. A stable molecule, the cation has a linear O=U=O geometry. The short U-O bonds (1.78 Å) arise from the combination of uranium 5f/6d and oxygen 2p orbitals. Due to the oxygen moieties being multiply bonded, these sites were not thought to be basic enough for Lewis acidic coordination to be a viable approach to sequestration. The goal of this research is thus to broaden the coordination chemistry of the uranyl ion by studying new ligand systems via synthetic, structural, thermodynamic and computational methods. It is anticipated that this fundamental science will find use beyond actinide separation technologies in areas such as nuclear waste remediation and nuclear materials. The focus of this study is to synthesize uranyl complexes incorporating amidinate and guanidinate ligands. Both synthetic and computational methods are used to investigate novel equatorial ligand coordination and how this affects the basicity of the oxo ligands. Such an understanding will later apply to designing ligands incorporating functionalities that can bind uranyl both equatorially and axially for highly selective sequestration. Efficient and durable chromatography supports for lanthanide separation will be generated by (1) identifying robust peptoid-based ligands capable of binding different lanthanides with variable affinities, and (2) developing practical synthetic methods for the attachment of these ligands to Dowex ion exchange resins.

Selectivity in ligand binding to uranyl compounds: A synthetic, structural, thermodynamic and computational study

International Nuclear Information System (INIS)

Arnold, John

2015-01-01

The uranyl cation (UO 2 2+ ) is the most abundant form of uranium on the planet. It is estimated that 4.5 billion tons of uranium in this form exist in sea water. The ability to bind and extract the uranyl cation from aqueous solution while separating it from other elements would provide a limitless source of nuclear fuel. A large body of research concerns the selective recognition and extraction of uranyl. A stable molecule, the cation has a linear O=U=O geometry. The short U-O bonds (1.78 Å) arise from the combination of uranium 5f/6d and oxygen 2p orbitals. Due to the oxygen moieties being multiply bonded, these sites were not thought to be basic enough for Lewis acidic coordination to be a viable approach to sequestration. The goal of this research is thus to broaden the coordination chemistry of the uranyl ion by studying new ligand systems via synthetic, structural, thermodynamic and computational methods. It is anticipated that this fundamental science will find use beyond actinide separation technologies in areas such as nuclear waste remediation and nuclear materials. The focus of this study is to synthesize uranyl complexes incorporating amidinate and guanidinate ligands. Both synthetic and computational methods are used to investigate novel equatorial ligand coordination and how this affects the basicity of the oxo ligands. Such an understanding will later apply to designing ligands incorporating functionalities that can bind uranyl both equatorially and axially for highly selective sequestration. Efficient and durable chromatography supports for lanthanide separation will be generated by (1) identifying robust peptoid-based ligands capable of binding different lanthanides with variable affinities, and (2) developing practical synthetic methods for the attachment of these ligands to Dowex ion exchange resins.

A Herpesviral induction of RAE-1 NKG2D ligand expression occurs through release of HDAC mediated repression.

Science.gov (United States)

Greene, Trever T; Tokuyama, Maria; Knudsen, Giselle M; Kunz, Michele; Lin, James; Greninger, Alexander L; DeFilippis, Victor R; DeRisi, Joseph L; Raulet, David H; Coscoy, Laurent

2016-11-22

Natural Killer (NK) cells are essential for control of viral infection and cancer. NK cells express NKG2D, an activating receptor that directly recognizes NKG2D ligands. These are expressed at low level on healthy cells, but are induced by stresses like infection and transformation. The physiological events that drive NKG2D ligand expression during infection are still poorly understood. We observed that the mouse cytomegalovirus encoded protein m18 is necessary and sufficient to drive expression of the RAE-1 family of NKG2D ligands. We demonstrate that RAE-1 is transcriptionally repressed by histone deacetylase inhibitor 3 (HDAC3) in healthy cells, and m18 relieves this repression by directly interacting with Casein Kinase II and preventing it from activating HDAC3. Accordingly, we found that HDAC inhibiting proteins from human herpesviruses induce human NKG2D ligand ULBP-1. Thus our findings indicate that virally mediated HDAC inhibition can act as a signal for the host to activate NK-cell recognition.

[Analysis of the stability and adaptability of near infrared spectra qualitative analysis model].

Science.gov (United States)

Cao, Wu; Li, Wei-jun; Wang, Ping; Zhang, Li-ping

2014-06-01

The stability and adaptability of model of near infrared spectra qualitative analysis were studied. Method of separate modeling can significantly improve the stability and adaptability of model; but its ability of improving adaptability of model is limited. Method of joint modeling can not only improve the adaptability of the model, but also the stability of model, at the same time, compared to separate modeling, the method can shorten the modeling time, reduce the modeling workload; extend the term of validity of model, and improve the modeling efficiency. The experiment of model adaptability shows that, the correct recognition rate of separate modeling method is relatively low, which can not meet the requirements of application, and joint modeling method can reach the correct recognition rate of 90%, and significantly enhances the recognition effect. The experiment of model stability shows that, the identification results of model by joint modeling are better than the model by separate modeling, and has good application value.

CRISPR-Cas: evolution of an RNA-based adaptive immunity system in prokaryotes.

Science.gov (United States)

Koonin, Eugene V; Makarova, Kira S

2013-05-01

The CRISPR-Cas (clustered regularly interspaced short palindromic repeats, CRISPR-associated genes) is an adaptive immunity system in bacteria and archaea that functions via a distinct self-non-self recognition mechanism that is partially analogous to the mechanism of eukaryotic RNA interference (RNAi). The CRISPR-Cas system incorporates fragments of virus or plasmid DNA into the CRISPR repeat cassettes and employs the processed transcripts of these spacers as guide RNAs to cleave the cognate foreign DNA or RNA. The Cas proteins, however, are not homologous to the proteins involved in RNAi and comprise numerous, highly diverged families. The majority of the Cas proteins contain diverse variants of the RNA recognition motif (RRM), a widespread RNA-binding domain. Despite the fast evolution that is typical of the cas genes, the presence of diverse versions of the RRM in most Cas proteins provides for a simple scenario for the evolution of the three distinct types of CRISPR-cas systems. In addition to several proteins that are directly implicated in the immune response, the cas genes encode a variety of proteins that are homologous to prokaryotic toxins that typically possess nuclease activity. The predicted toxins associated with CRISPR-Cas systems include the essential Cas2 protein, proteins of COG1517 that, in addition to a ligand-binding domain and a helix-turn-helix domain, typically contain different nuclease domains and several other predicted nucleases. The tight association of the CRISPR-Cas immunity systems with predicted toxins that, upon activation, would induce dormancy or cell death suggests that adaptive immunity and dormancy/suicide response are functionally coupled. Such coupling could manifest in the persistence state being induced and potentially providing conditions for more effective action of the immune system or in cell death being triggered when immunity fails.

Ligands in PSI structures

International Nuclear Information System (INIS)

Kumar, Abhinav; Chiu, Hsiu-Ju; Axelrod, Herbert L.; Morse, Andrew; Elsliger, Marc-André; Wilson, Ian A.; Deacon, Ashley

2010-01-01

A survey of the types and frequency of ligands that are bound to PSI structures is analyzed as well as their utility in functional annotation of previously uncharacterized proteins. Approximately 65% of PSI structures report some type of ligand(s) that is bound in the crystal structure. Here, a description is given of how such ligands are handled and analyzed at the JCSG and a survey of the types, variety and frequency of ligands that are observed in the PSI structures is also compiled and analyzed, including illustrations of how these bound ligands have provided functional clues for annotation of proteins with little or no previous experimental characterization. Furthermore, a web server was developed as a tool to mine and analyze the PSI structures for bound ligands and other identifying features

Online recognition of Chinese characters: the state-of-the-art.

Science.gov (United States)

Liu, Cheng-Lin; Jaeger, Stefan; Nakagawa, Masaki

2004-02-01

Online handwriting recognition is gaining renewed interest owing to the increase of pen computing applications and new pen input devices. The recognition of Chinese characters is different from western handwriting recognition and poses a special challenge. To provide an overview of the technical status and inspire future research, this paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s. Compared to the research in the 1980s, the research efforts in the 1990s aimed to further relax the constraints of handwriting, namely, the adherence to standard stroke orders and stroke numbers and the restriction of recognition to isolated characters only. The target of recognition has shifted from regular script to fluent script in order to better meet the requirements of practical applications. The research works are reviewed in terms of pattern representation, character classification, learning/adaptation, and contextual processing. We compare important results and discuss possible directions of future research.

A change in strategy: Static emotion recognition in Malaysian Chinese

Directory of Open Access Journals (Sweden)

Chrystalle B.Y. Tan

2015-12-01

Full Text Available Studies have shown that while East Asians focused on the center of the face to recognize identities, participants adapted their strategy by focusing more on the eyes to identify emotions, suggesting that the eyes may contain salient information pertaining to emotional state in Eastern cultures. However, Western Caucasians employ the same strategy by moving between the eyes and mouth to identify both identities and emotions. Malaysian Chinese have been shown to focus on the eyes and nose more than the mouth during face recognition task, which represents an intermediate between Eastern and Western looking strategies. The current study examined whether Malaysian Chinese continue to employ an intermediate strategy or shift towards an Eastern or Western pattern (by fixating more on the eyes or mouth respectively during an emotion recognition task. Participants focused more on the eyes, followed by the nose then mouth. Directing attention towards the eye region resulted in better recognition of certain own- than other-race emotions. Although the fixation patterns appear similar for both tasks, further analyses showed that fixations on the eyes were reduced whereas fixations on the nose and mouth were increased during emotion recognition, indicating that participants adapt looking strategies based on their aims.

Adaptive techniques for diagnostics of vibrating structures

International Nuclear Information System (INIS)

Skormin, V.A.; Sankar, S.

1983-01-01

An adaptive diagnostic procedure for vibrating structures based on correspondence between current estimates of stiffness matrix and structure status is proposed. Procedure employs adaptive mathematical description of the vibrating structure in frequency domain, statistical techniques for detection and location of changes of structure properties, 'recognition' and prediction of defects. (orig.)

Ligand photo-isomerization triggers conformational changes in iGluR2 ligand binding domain.

Directory of Open Access Journals (Sweden)

Tino Wolter

Full Text Available Neurological glutamate receptors bind a variety of artificial ligands, both agonistic and antagonistic, in addition to glutamate. Studying their small molecule binding properties increases our understanding of the central nervous system and a variety of associated pathologies. The large, oligomeric multidomain membrane protein contains a large and flexible ligand binding domains which undergoes large conformational changes upon binding different ligands. A recent application of glutamate receptors is their activation or inhibition via photo-switchable ligands, making them key systems in the emerging field of optochemical genetics. In this work, we present a theoretical study on the binding mode and complex stability of a novel photo-switchable ligand, ATA-3, which reversibly binds to glutamate receptors ligand binding domains (LBDs. We propose two possible binding modes for this ligand based on flexible ligand docking calculations and show one of them to be analogues to the binding mode of a similar ligand, 2-BnTetAMPA. In long MD simulations, it was observed that transitions between both binding poses involve breaking and reforming the T686-E402 protein hydrogen bond. Simulating the ligand photo-isomerization process shows that the two possible configurations of the ligand azo-group have markedly different complex stabilities and equilibrium binding modes. A strong but slow protein response is observed after ligand configuration changes. This provides a microscopic foundation for the observed difference in ligand activity upon light-switching.

Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

Science.gov (United States)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image

Self-recognition in the coordination driven self-assembly of 2-D polygons.

Science.gov (United States)

Addicott, Chris; Das, Neeladri; Stang, Peter J

2004-08-23

Self-recognition in the transition-metal-mediated self-assembly of some 2-D polygons is presented. Prolonged heating of two or three organoplatinum reagents with 4,4'-dipyridyl in aqueous acetone results in the predominant formation of a rectangle, triangle, and/or square. All mixtures are characterized with NMR and electrospray ionization mass spectrometry (ESIMS). Despite the potential for ill-defined oligomeric products, these mixed ligand systems prefer to self-assemble into discrete species.

Fast Pedestrian Recognition Based on Multisensor Fusion

Directory of Open Access Journals (Sweden)

Hongyu Hu

2012-01-01

Full Text Available A fast pedestrian recognition algorithm based on multisensor fusion is presented in this paper. Firstly, potential pedestrian locations are estimated by laser radar scanning in the world coordinates, and then their corresponding candidate regions in the image are located by camera calibration and the perspective mapping model. For avoiding time consuming in the training and recognition process caused by large numbers of feature vector dimensions, region of interest-based integral histograms of oriented gradients (ROI-IHOG feature extraction method is proposed later. A support vector machine (SVM classifier is trained by a novel pedestrian sample dataset which adapt to the urban road environment for online recognition. Finally, we test the validity of the proposed approach with several video sequences from realistic urban road scenarios. Reliable and timewise performances are shown based on our multisensor fusing method.

Conformal prediction for reliable machine learning theory, adaptations and applications

CERN Document Server

Balasubramanian, Vineeth; Vovk, Vladimir

2014-01-01

The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detecti

Dextran as a Generally Applicable Multivalent Scaffold for Improving Immunoglobulin-Binding Affinities of Peptide and Peptidomimetic Ligands

Science.gov (United States)

2015-01-01

Molecules able to bind the antigen-binding sites of antibodies are of interest in medicine and immunology. Since most antibodies are bivalent, higher affinity recognition can be achieved through avidity effects in which a construct containing two or more copies of the ligand engages both arms of the immunoglobulin simultaneously. This can be achieved routinely by immobilizing antibody ligands at high density on solid surfaces, such as ELISA plates, but there is surprisingly little literature on scaffolds that routinely support bivalent binding of antibody ligands in solution, particularly for the important case of human IgG antibodies. Here we show that the simple strategy of linking two antigens with a polyethylene glycol (PEG) spacer long enough to span the two arms of an antibody results in higher affinity binding in some, but not all, cases. However, we found that the creation of multimeric constructs in which several antibody ligands are displayed on a dextran polymer reliably provides much higher affinity binding than is observed with the monomer in all cases tested. Since these dextran conjugates are simple to construct, they provide a general and convenient strategy to transform modest affinity antibody ligands into high affinity probes. An additional advantage is that the antibody ligands occupy only a small number of the reactive sites on the dextran, so that molecular cargo can be attached easily, creating molecules capable of delivering this cargo to cells displaying antigen-specific receptors. PMID:25073654

Role of ligand-ligand vs. core-core interactions in gold nanoclusters.

Science.gov (United States)

Milowska, Karolina Z; Stolarczyk, Jacek K

2016-05-14

The controlled assembly of ligand-coated gold nanoclusters (NCs) into larger structures paves the way for new applications ranging from electronics to nanomedicine. Here, we demonstrate through rigorous density functional theory (DFT) calculations employing novel functionals accounting for van der Waals forces that the ligand-ligand interactions determine whether stable assemblies can be formed. The study of NCs with different core sizes, symmetry forms, ligand lengths, mutual crystal orientations, and in the presence of a solvent suggests that core-to-core van der Waals interactions play a lesser role in the assembly. The dominant interactions originate from combination of steric effects, augmented by ligand bundling on NC facets, and related to them changes in electronic properties induced by neighbouring NCs. We also show that, in contrast to standard colloidal theory approach, DFT correctly reproduces the surprising experimental trends in the strength of the inter-particle interaction observed when varying the length of the ligands. The results underpin the importance of understanding NC interactions in designing gold NCs for a specific function.

High-performance speech recognition using consistency modeling

Science.gov (United States)

Digalakis, Vassilios; Murveit, Hy; Monaco, Peter; Neumeyer, Leo; Sankar, Ananth

1994-12-01

The goal of SRI's consistency modeling project is to improve the raw acoustic modeling component of SRI's DECIPHER speech recognition system and develop consistency modeling technology. Consistency modeling aims to reduce the number of improper independence assumptions used in traditional speech recognition algorithms so that the resulting speech recognition hypotheses are more self-consistent and, therefore, more accurate. At the initial stages of this effort, SRI focused on developing the appropriate base technologies for consistency modeling. We first developed the Progressive Search technology that allowed us to perform large-vocabulary continuous speech recognition (LVCSR) experiments. Since its conception and development at SRI, this technique has been adopted by most laboratories, including other ARPA contracting sites, doing research on LVSR. Another goal of the consistency modeling project is to attack difficult modeling problems, when there is a mismatch between the training and testing phases. Such mismatches may include outlier speakers, different microphones and additive noise. We were able to either develop new, or transfer and evaluate existing, technologies that adapted our baseline genonic HMM recognizer to such difficult conditions.

Action recognition in depth video from RGB perspective: A knowledge transfer manner

Science.gov (United States)

Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

2018-03-01

Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

Facial emotion recognition, socio-occupational functioning and expressed emotions in schizophrenia versus bipolar disorder.

Science.gov (United States)

Thonse, Umesh; Behere, Rishikesh V; Praharaj, Samir Kumar; Sharma, Podila Sathya Venkata Narasimha

2018-06-01

Facial emotion recognition deficits have been consistently demonstrated in patients with severe mental disorders. Expressed emotion is found to be an important predictor of relapse. However, the relationship between facial emotion recognition abilities and expressed emotions and its influence on socio-occupational functioning in schizophrenia versus bipolar disorder has not been studied. In this study we examined 91 patients with schizophrenia and 71 with bipolar disorder for psychopathology, socio occupational functioning and emotion recognition abilities. Primary caregivers of 62 patients with schizophrenia and 49 with bipolar disorder were assessed on Family Attitude Questionnaire to assess their expressed emotions. Patients of schizophrenia and bipolar disorder performed similarly on the emotion recognition task. Patients with schizophrenia group experienced higher critical comments and had a poorer socio-occupational functioning as compared to patients with bipolar disorder. Poorer socio-occupational functioning in patients with schizophrenia was significantly associated with greater dissatisfaction in their caregivers. In patients with bipolar disorder, poorer emotion recognition scores significantly correlated with poorer adaptive living skills and greater hostility and dissatisfaction in their caregivers. The findings of our study suggest that emotion recognition abilities in patients with bipolar disorder are associated with negative expressed emotions leading to problems in adaptive living skills. Copyright © 2018 Elsevier B.V. All rights reserved.

NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions

DEFF Research Database (Denmark)

Nielsen, Morten; Andreatta, Massimo

2017-01-01

Peptides are extensively used to characterize functional or (linear) structural aspects of receptor-ligand interactions in biological systems, e.g. SH2, SH3, PDZ peptide-recognition domains, the MHC membrane receptors and enzymes such as kinases and phosphatases. NNAlign is a method for the ident...... with insertions and deletions, encoding of receptor pseudo-sequences, and custom alphabets for the training sequences. The server is available at http://www.cbs.dtu.dk/services/NNAlign-2.0....

Sensor-Based Activity Recognition with Dynamically Added Context

Directory of Open Access Journals (Sweden)

Jiahui Wen

2015-08-01

Full Text Available An activity recognition system essentially processes raw sensor data and maps them into latent activity classes. Most of the previous systems are built with supervised learning techniques and pre-defined data sources, and result in static models. However, in realistic and dynamic environments, original data sources may fail and new data sources become available, a robust activity recognition system should be able to perform evolution automatically with dynamic sensor availability in dynamic environments. In this paper, we propose methods that automatically incorporate dynamically available data sources to adapt and refine the recognition system at run-time. The system is built upon ensemble classifiers which can automatically choose the features with the most discriminative power. Extensive experimental results with publicly available datasets demonstrate the effectiveness of our methods.

The Neural Correlates of Everyday Recognition Memory

Science.gov (United States)

Milton, F.; Muhlert, N.; Butler, C. R.; Benattayallah, A.; Zeman, A. Z.

2011-01-01

We used a novel automatic camera, SenseCam, to create a recognition memory test for real-life events. Adapting a "Remember/Know" paradigm, we asked healthy undergraduates, who wore SenseCam for 2 days, in their everyday environments, to classify images as strongly or weakly remembered, strongly or weakly familiar or novel, while brain activation…

Characterization of chicken thrombocyte responses to Toll-like receptor ligands.

Directory of Open Access Journals (Sweden)

Michael St Paul

Full Text Available Thrombocytes are the avian equivalent to mammalian platelets. In addition to their hemostatic effects, mammalian platelets rely in part on pattern recognition receptors, such as the Toll-like receptors (TLR, to detect the presence of pathogens and signal the release of certain cytokines. Ligands for TLRs include lipopolysaccharide (LPS, which is bound by TLR4, as well as unmethylated CpG DNA motifs, which are bound by TLR9 in mammals and TLR21 in chickens. Similar to mammalian platelets, avian thrombocytes have been shown to express TLR4 and secrete some pro-inflammatory cytokines in response to LPS treatment. However, the full extent of the contributions made by thrombocytes to host immunity has yet to be elucidated. Importantly, the mechanisms by which TLR stimulation may modulate thrombocyte effector functions have not been well characterized. As such, the objective of the present study was to gain further insight into the immunological role of thrombocytes by analyzing their responses to treatment with ligands for TLR4 and TLR21. To this end, we quantified the relative expression of several immune system genes at 1, 3, 8 and 18 hours post-treatment using real-time RT-PCR. Furthermore, production of nitric oxide and phagocytic activity of thrombocytes was measured after their activation with TLR ligands. We found that thrombocytes constitutively express transcripts for both pro- and anti-inflammatory cytokines, in addition to those associated with anti-viral responses and antigen presentation. Moreover, we found that both LPS and CpG oligodeoxynucleotides (ODN induced robust pro-inflammatory responses in thrombocytes, as characterized by more than 100 fold increase in interleukin (IL-1β, IL-6 and IL-8 transcripts, while only LPS enhanced nitric oxide production and phagocytic capabilities. Future studies may be aimed at examining the responses of thrombocytes to other TLR ligands.

Superpixel-Based Feature for Aerial Image Scene Recognition

Directory of Open Access Journals (Sweden)

Hongguang Li

2018-01-01

Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

The cingulo-opercular network provides word-recognition benefit.

Science.gov (United States)

Vaden, Kenneth I; Kuchinsky, Stefanie E; Cute, Stephanie L; Ahlstrom, Jayne B; Dubno, Judy R; Eckert, Mark A

2013-11-27

Recognizing speech in difficult listening conditions requires considerable focus of attention that is often demonstrated by elevated activity in putative attention systems, including the cingulo-opercular network. We tested the prediction that elevated cingulo-opercular activity provides word-recognition benefit on a subsequent trial. Eighteen healthy, normal-hearing adults (10 females; aged 20-38 years) performed word recognition (120 trials) in multi-talker babble at +3 and +10 dB signal-to-noise ratios during a sparse sampling functional magnetic resonance imaging (fMRI) experiment. Blood oxygen level-dependent (BOLD) contrast was elevated in the anterior cingulate cortex, anterior insula, and frontal operculum in response to poorer speech intelligibility and response errors. These brain regions exhibited significantly greater correlated activity during word recognition compared with rest, supporting the premise that word-recognition demands increased the coherence of cingulo-opercular network activity. Consistent with an adaptive control network explanation, general linear mixed model analyses demonstrated that increased magnitude and extent of cingulo-opercular network activity was significantly associated with correct word recognition on subsequent trials. These results indicate that elevated cingulo-opercular network activity is not simply a reflection of poor performance or error but also supports word recognition in difficult listening conditions.

Stereochemistry of charged nitrogen-aromatic interactions and its involvement in ligand-receptor binding

Science.gov (United States)

Verdonk, Marcel L.; Boks, Gertjan J.; Kooijman, Huub; Kanters, Jan A.; Kroon, Jan

1993-04-01

Recently, new evidence was found for the involvement of charged nitrogen-aromatic interactions in ligand-receptor binding. In this study we report two favourable orientations of a phenyl ring with respect to a R-N+(CH3)3 group, based on crystal structure statistics from the Cambridge Structural Database. In the first orientation, the phenyl ring is situated in between the substituents at about 4.5 Å from the nitrogen atom, and the ring is approximately oriented on the sphere around the nitrogen atom. In the second orientation, the phenyl ring is situated in the same direction as one of the N-C bonds at about 6.0 Å from the nitrogen atom, and the ring is tilted with respect to the sphere around the nitrogen atom. The same two orientations were also found in the crystal structures of three ligand-receptor complexes, which implies that these orientations probably play a major role in molecular recognition mechanisms.

LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone

KAUST Repository

Chen, Peng

2014-12-03

Background Protein-ligand binding is important for some proteins to perform their functions. Protein-ligand binding sites are the residues of proteins that physically bind to ligands. Despite of the recent advances in computational prediction for protein-ligand binding sites, the state-of-the-art methods search for similar, known structures of the query and predict the binding sites based on the solved structures. However, such structural information is not commonly available. Results In this paper, we propose a sequence-based approach to identify protein-ligand binding residues. We propose a combination technique to reduce the effects of different sliding residue windows in the process of encoding input feature vectors. Moreover, due to the highly imbalanced samples between the ligand-binding sites and non ligand-binding sites, we construct several balanced data sets, for each of which a random forest (RF)-based classifier is trained. The ensemble of these RF classifiers forms a sequence-based protein-ligand binding site predictor. Conclusions Experimental results on CASP9 and CASP8 data sets demonstrate that our method compares favorably with the state-of-the-art protein-ligand binding site prediction methods.

Adaptive metric kernel regression

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

2000-01-01

Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

Multitarget-directed tricyclic pyridazinones as G protein-coupled receptor ligands and cholinesterase inhibitors.

Science.gov (United States)

Pau, Amedeo; Catto, Marco; Pinna, Giovanni; Frau, Simona; Murineddu, Gabriele; Asproni, Battistina; Curzu, Maria M; Pisani, Leonardo; Leonetti, Francesco; Loza, Maria Isabel; Brea, José; Pinna, Gérard A; Carotti, Angelo

2015-06-01

By following a multitarget ligand design approach, a library of 47 compounds was prepared, and they were tested as binders of selected G protein-coupled receptors (GPCRs) and inhibitors of acetyl and/or butyryl cholinesterase. The newly designed ligands feature pyridazinone-based tricyclic scaffolds connected through alkyl chains of variable length to proper amine moieties (e.g., substituted piperazines or piperidines) for GPCR and cholinesterase (ChE) molecular recognition. The compounds were tested at three different GPCRs, namely serotoninergic 5-HT1A, adrenergic α1A, and dopaminergic D2 receptors. Our main goal was the discovery of compounds that exhibit, in addition to ChE inhibition, antagonist activity at 5-HT1A because of its involvement in neuronal deficits typical of Alzheimer's and other neurodegenerative diseases. Ligands with nanomolar affinity for the tested GPCRs were discovered, but most of them behaved as dual antagonists of α1A and 5-HT1A receptors. Nevertheless, several compounds displaying this GPCR affinity profile also showed moderate to good inhibition of AChE and BChE, thus deserving further investigations to exploit the therapeutic potential of such unusual biological profiles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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.

Shared or separate mechanisms for self-face and other-face processing? Evidence from adaptation.

Directory of Open Access Journals (Sweden)

Brendan eRooney

2012-03-01

Full Text Available Evidence that self-face recognition is dissociable from general face recognition hasimportant implications both for models of social cognition and for our understanding offace recognition. In two studies, we examine how adaptation affects the perception ofpersonally familiar faces, and we use a visual adaptation paradigm to investigatewhether the neural mechanisms underlying the recognition of one’s own and other facesare shared or separate. In Study 1 we show that the representation of personally familiarfaces is rapidly updated by visual experience with unfamiliar faces, so that theperception of one’s own face and a friend’s face is altered by a brief period ofadaptation to distorted unfamiliar faces. In Study 2, participants adapted to images oftheir own and a friend’s face distorted in opposite directions; the contingent aftereffectswe observe are indicative of separate neural populations, but we suggest that thesereflect coding of facial identity rather than of the categories ‘self’ and ‘other’.

Iris double recognition based on modified evolutionary neural network

Science.gov (United States)

Liu, Shuai; Liu, Yuan-Ning; Zhu, Xiao-Dong; Huo, Guang; Liu, Wen-Tao; Feng, Jia-Kai

2017-11-01

Aiming at multicategory iris recognition under illumination and noise interference, this paper proposes a method of iris double recognition based on a modified evolutionary neural network. An equalization histogram and Laplace of Gaussian operator are used to process the iris to suppress illumination and noise interference and Haar wavelet to convert the iris feature to binary feature encoding. Calculate the Hamming distance for the test iris and template iris , and compare with classification threshold, determine the type of iris. If the iris cannot be identified as a different type, there needs to be a secondary recognition. The connection weights in back-propagation (BP) neural network use modified evolutionary neural network to adaptively train. The modified neural network is composed of particle swarm optimization with mutation operator and BP neural network. According to different iris libraries in different circumstances of experimental results, under illumination and noise interference, the correct recognition rate of this algorithm is higher, the ROC curve is closer to the coordinate axis, the training and recognition time is shorter, and the stability and the robustness are better.

Development of visuo-haptic transfer for object recognition in typical preschool and school-aged children.

Science.gov (United States)

Purpura, Giulia; Cioni, Giovanni; Tinelli, Francesca

2018-07-01

Object recognition is a long and complex adaptive process and its full maturation requires combination of many different sensory experiences as well as cognitive abilities to manipulate previous experiences in order to develop new percepts and subsequently to learn from the environment. It is well recognized that the transfer of visual and haptic information facilitates object recognition in adults, but less is known about development of this ability. In this study, we explored the developmental course of object recognition capacity in children using unimodal visual information, unimodal haptic information, and visuo-haptic information transfer in children from 4 years to 10 years and 11 months of age. Participants were tested through a clinical protocol, involving visual exploration of black-and-white photographs of common objects, haptic exploration of real objects, and visuo-haptic transfer of these two types of information. Results show an age-dependent development of object recognition abilities for visual, haptic, and visuo-haptic modalities. A significant effect of time on development of unimodal and crossmodal recognition skills was found. Moreover, our data suggest that multisensory processes for common object recognition are active at 4 years of age. They facilitate recognition of common objects, and, although not fully mature, are significant in adaptive behavior from the first years of age. The study of typical development of visuo-haptic processes in childhood is a starting point for future studies regarding object recognition in impaired populations.

Crystallization of protein–ligand complexes

International Nuclear Information System (INIS)

Hassell, Anne M.; An, Gang; Bledsoe, Randy K.; Bynum, Jane M.; Carter, H. Luke III; Deng, Su-Jun J.; Gampe, Robert T.; Grisard, Tamara E.; Madauss, Kevin P.; Nolte, Robert T.; Rocque, Warren J.; Wang, Liping; Weaver, Kurt L.; Williams, Shawn P.; Wisely, G. Bruce; Xu, Robert; Shewchuk, Lisa M.

2007-01-01

Methods presented for growing protein–ligand complexes fall into the categories of co-expression of the protein with the ligands of interest, use of the ligands during protein purification, cocrystallization and soaking the ligands into existing crystals. Obtaining diffraction-quality crystals has long been a bottleneck in solving the three-dimensional structures of proteins. Often proteins may be stabilized when they are complexed with a substrate, nucleic acid, cofactor or small molecule. These ligands, on the other hand, have the potential to induce significant conformational changes to the protein and ab initio screening may be required to find a new crystal form. This paper presents an overview of strategies in the following areas for obtaining crystals of protein–ligand complexes: (i) co-expression of the protein with the ligands of interest, (ii) use of the ligands during protein purification, (iii) cocrystallization and (iv) soaks

A new class of pyrazolo[5,1-c][1,2,4]triazines as γ-aminobutyric type A (GABAA) receptor subtype ligand: synthesis and pharmacological evaluation.

Science.gov (United States)

Guerrini, Gabriella; Ciciani, Giovanna; Daniele, Simona; Martini, Claudia; Costagli, Camilla; Guarino, Chiara; Selleri, Silvia

2018-05-15

A comparison between compounds with pyrazolo[1,5-a]pyrimidine structure (series 4-6) and pyrazolo[5,1-c][1,2,4]triazine core (series 9) as ligands at GABA A -receptor subtype, was evaluated. Moreover, for pyrazolotriazine derivatives having binding recognition, the interaction on recombinant rat α(1-3,5) GABA A receptor subtypes, was performed. Among these latter, emerge compounds 9c, 9k, 9l, 9m and 9n as α1-selective and 9h as α2-selective ligands. Copyright © 2018 Elsevier Ltd. All rights reserved.

Coupling ligand recognition to protein folding in an engineered variant of rabbit ileal lipid binding protein.

Science.gov (United States)

Kouvatsos, Nikolaos; Meldrum, Jill K; Searle, Mark S; Thomas, Neil R

2006-11-28

We have engineered a variant of the beta-clam shell protein ILBP which lacks the alpha-helical motif that caps the central binding cavity; the mutant protein is sufficiently destabilised that it is unfolded under physiological conditions, however, it unexpectedly binds its natural bile acid substrates with high affinity forming a native-like beta-sheet rich structure and demonstrating strong thermodynamic coupling between ligand binding and protein folding.

Adaptive Metric Kernel Regression

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

1998-01-01

Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

A structural and mutagenic blueprint for molecular recognition of strychnine and d-tubocurarine by different cys-loop receptors.

Directory of Open Access Journals (Sweden)

Marijke Brams

2011-03-01

Full Text Available Cys-loop receptors (CLR are pentameric ligand-gated ion channels that mediate fast excitatory or inhibitory transmission in the nervous system. Strychnine and d-tubocurarine (d-TC are neurotoxins that have been highly instrumental in decades of research on glycine receptors (GlyR and nicotinic acetylcholine receptors (nAChR, respectively. In this study we addressed the question how the molecular recognition of strychnine and d-TC occurs with high affinity and yet low specificity towards diverse CLR family members. X-ray crystal structures of the complexes with AChBP, a well-described structural homolog of the extracellular domain of the nAChRs, revealed that strychnine and d-TC adopt multiple occupancies and different ligand orientations, stabilizing the homopentameric protein in an asymmetric state. This introduces a new level of structural diversity in CLRs. Unlike protein and peptide neurotoxins, strychnine and d-TC form a limited number of contacts in the binding pocket of AChBP, offering an explanation for their low selectivity. Based on the ligand interactions observed in strychnine- and d-TC-AChBP complexes we performed alanine-scanning mutagenesis in the binding pocket of the human α1 GlyR and α7 nAChR and showed the functional relevance of these residues in conferring high potency of strychnine and d-TC, respectively. Our results demonstrate that a limited number of ligand interactions in the binding pocket together with an energetic stabilization of the extracellular domain are key to the poor selective recognition of strychnine and d-TC by CLRs as diverse as the GlyR, nAChR, and 5-HT(3R.

Aptamer-Based Molecular Recognition of Lysergamine, Metergoline and Small Ergot Alkaloids

Directory of Open Access Journals (Sweden)

Johan Robbens

2012-12-01

Full Text Available Ergot alkaloids are mycotoxins produced by fungi of the genus Claviceps, which infect cereal crops and grasses. The uptake of ergot alkaloid contaminated cereal products can be lethal to humans and animals. For food safety assessment, analytical techniques are currently used to determine the presence of ergot alkaloids in food and feed samples. However, the number of samples which can be analyzed is limited, due to the cost of the equipment and the need for skilled personnel. In order to compensate for the lack of rapid tests for the detection of ergot alkaloids, the aim of this study was to develop a specific recognition element for ergot alkaloids, which could be further applied to produce a colorimetric reaction in the presence of these toxins. As recognition elements, single-stranded DNA ligands were selected by using an iterative selection procedure named SELEX, i.e., Systematic Evolution of Ligands by EXponential enrichment. After several selection cycles, the resulting aptamers were cloned and sequenced. A surface plasmon resonance analysis enabled determination of the dissociation constants of the complexes of aptamers and lysergamine. Dissociation constants in the nanomolar range were obtained with three selected aptamers. One of the selected aptamers, having a dissociation constant of 44 nM, was linked to gold nanoparticles and it was possible to produce a colorimetric reaction in the presence of lysergamine. This system could also be applied to small ergot alkaloids in an ergot contaminated flour sample.

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

Science.gov (United States)

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

Impact of Sliding Window Length in Indoor Human Motion Modes and Pose Pattern Recognition Based on Smartphone Sensors

Directory of Open Access Journals (Sweden)

Gaojing Wang

2018-06-01

Full Text Available Human activity recognition (HAR is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applied to HAR. Data segmentation using a sliding window is a basic step during the HAR procedure, wherein the window length directly affects recognition performance. However, the window length is generally randomly selected without systematic study. In this study, we examined the impact of window length on smartphone sensor-based human motion and pose pattern recognition. With data collected from smartphone sensors, we tested a range of window lengths on five popular machine-learning methods: decision tree, support vector machine, K-nearest neighbor, Gaussian naïve Bayesian, and adaptive boosting. From the results, we provide recommendations for choosing the appropriate window length. Results corroborate that the influence of window length on the recognition of motion modes is significant but largely limited to pose pattern recognition. For motion mode recognition, a window length between 2.5–3.5 s can provide an optimal tradeoff between recognition performance and speed. Adaptive boosting outperformed the other methods. For pose pattern recognition, 0.5 s was enough to obtain a satisfactory result. In addition, all of the tested methods performed well.

Automatic anatomy recognition on CT images with pathology

Science.gov (United States)

Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

2016-03-01

Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone

KAUST Repository

Chen, Peng; Huang, Jianhua Z; Gao, Xin

2014-01-01

Protein-ligand binding is important for some proteins to perform their functions. Protein-ligand binding sites are the residues of proteins that physically bind to ligands. Despite of the recent advances in computational prediction

Secbase: database module to retrieve secondary structure elements with ligand binding motifs.

Science.gov (United States)

Koch, Oliver; Cole, Jason; Block, Peter; Klebe, Gerhard

2009-10-01

Secbase is presented as a novel extension module of Relibase. It integrates the information about secondary structure elements into the retrieval facilities of Relibase. The data are accessible via the extended Relibase user interface, and integrated retrieval queries can be addressed using an extended version of Reliscript. The primary information about alpha-helices and beta-sheets is used as provided by the PDB. Furthermore, a uniform classification of all turn families, based on recent clustering methods, and a new helix assignment that is based on this turn classification has been included. Algorithms to analyze the geometric features of helices and beta-strands were also implemented. To demonstrate the performance of the Secbase implementation, some application examples are given. They provide new insights into the involvement of secondary structure elements in ligand binding. A survey of water molecules detected next to the N-terminus of helices is analyzed to show their involvement in ligand binding. Additionally, the parallel oriented NH groups at the alpha-helix N-termini provide special binding motifs to bind particular ligand functional groups with two adjacent oxygen atoms, e.g., as found in negatively charged carboxylate or phosphate groups, respectively. The present study also shows that the specific structure of the first turn of alpha-helices provides a suitable explanation for stabilizing charged structures. The magnitude of the overall helix macrodipole seems to have no or only a minor influence on binding. Furthermore, an overview of the involvement of secondary structure elements with the recognition of some important endogenous ligands such as cofactors shows some distinct preference for particular binding motifs and amino acids.

Programmable molecular recognition based on the geometry of DNA nanostructures.

Science.gov (United States)

Woo, Sungwook; Rothemund, Paul W K

2011-07-10

From ligand-receptor binding to DNA hybridization, molecular recognition plays a central role in biology. Over the past several decades, chemists have successfully reproduced the exquisite specificity of biomolecular interactions. However, engineering multiple specific interactions in synthetic systems remains difficult. DNA retains its position as the best medium with which to create orthogonal, isoenergetic interactions, based on the complementarity of Watson-Crick binding. Here we show that DNA can be used to create diverse bonds using an entirely different principle: the geometric arrangement of blunt-end stacking interactions. We show that both binary codes and shape complementarity can serve as a basis for such stacking bonds, and explore their specificity, thermodynamics and binding rules. Orthogonal stacking bonds were used to connect five distinct DNA origami. This work, which demonstrates how a single attractive interaction can be developed to create diverse bonds, may guide strategies for molecular recognition in systems beyond DNA nanostructures.

Study on municipal road cracking and surface deformation based on image recognition

Science.gov (United States)

Yuan, Haitao; Wang, Shuai; Tan, Jizong

2017-05-01

In recent years, the digital image recognition technology of concrete structure cracks and deformation of binocular vision technology detection of civil engineering structure have made substantial development. As a result, people's understanding of the road engineering structure cracking and surface deformation recognition gives rise to a new situation. For the research on digital image concrete structure cracking and masonry structure surface deformation recognition technology, the key is to break through in the method, and to improve the traditional recognition technology and mode. Only in this way can we continuously improve the security level of the highway, to adapt to the new requirements of the development of new urbanization and modernization. This thesis focuses on and systematically analyzes the digital image road engineering structure cracking and key technologies of surface deformation recognition and its engineering applications. In addition, we change the concrete structure cracking and masonry structure surface deformation recognition pattern, and realize the breakthrough and innovation of the road structure safety testing means and methods.

Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

Science.gov (United States)

Fang, Fuming; Shinozaki, Takahiro

2018-01-01

Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

Postsurgical Disfigurement Influences Disgust Recognition: A Case-Control Study.

Science.gov (United States)

Lisan, Quentin; George, Nathalie; Hans, Stephane; Laccourreye, Ollivier; Lemogne, Cédric

Little is known about how emotion recognition may be modified in individuals prone to elicit disgust. We sought to determine if subjects with total laryngectomy would present a modified recognition of facial expressions of disgust. A total of 29 patients presenting with a history of advanced-stage laryngeal cancer were recruited, 17 being surgically treated (total laryngectomy) and 12 treated with chemoradiation therapy only. Based on a validated set of images of facial expressions of fear, disgust, surprise, happiness, sadness and anger displayed by 6 actors, we presented participants with expressions of each emotion at 5 levels of increasing intensity and measured their ability to recognize these emotions. Participants with (vs without) laryngectomy showed a higher threshold for the recognition of disgust (3.2. vs 2.7 images needed before emotion recognition, p = 0.03) and a lower success rate of correct recognition (75.5% vs 88.9%, p = 0.03). Subjects presenting with an aesthetic impairment of the head and neck showed poorer performance in disgust recognition when compared with those without disfigurement. These findings might relate either to some perceptual adaptation, habituation phenomenon, or to some higher-level processes related to emotion regulation strategies. Copyright © 2018 Academy of Consultation-Liaison Psychiatry. Published by Elsevier Inc. All rights reserved.

Simple test system for single molecule recognition force microscopy

International Nuclear Information System (INIS)

Riener, Christian K.; Stroh, Cordula M.; Ebner, Andreas; Klampfl, Christian; Gall, Alex A.; Romanin, Christoph; Lyubchenko, Yuri L.; Hinterdorfer, Peter; Gruber, Hermann J.

2003-01-01

We have established an easy-to-use test system for detecting receptor-ligand interactions on the single molecule level using atomic force microscopy (AFM). For this, avidin-biotin, probably the best characterized receptor-ligand pair, was chosen. AFM sensors were prepared containing tethered biotin molecules at sufficiently low surface concentrations appropriate for single molecule studies. A biotin tether, consisting of a 6 nm poly(ethylene glycol) (PEG) chain and a functional succinimide group at the other end, was newly synthesized and covalently coupled to amine-functionalized AFM tips. In particular, PEG 800 diamine was glutarylated, the mono-adduct NH 2 -PEG-COOH was isolated by ion exchange chromatography and reacted with biotin succinimidylester to give biotin-PEG-COOH which was then activated as N-hydroxysuccinimide (NHS) ester to give the biotin-PEG-NHS conjugate which was coupled to the aminofunctionalized AFM tip. The motional freedom provided by PEG allows for free rotation of the biotin molecule on the AFM sensor and for specific binding to avidin which had been adsorbed to mica surfaces via electrostatic interactions. Specific avidin-biotin recognition events were discriminated from nonspecific tip-mica adhesion by their typical unbinding force (∼40 pN at 1.4 nN/s loading rate), unbinding length (<13 nm), the characteristic nonlinear force-distance relation of the PEG linker, and by specific block with excess of free d-biotin. The convenience of the test system allowed to evaluate, and compare, different methods and conditions of tip aminofunctionalization with respect to specific binding and nonspecific adhesion. It is concluded that this system is well suited as calibration or start-up kit for single molecule recognition force microscopy

Minimal sulfated carbohydrates for recognition by L-selectin and the MECA-79 antibody.

Science.gov (United States)

Bruehl, R E; Bertozzi, C R; Rosen, S D

2000-10-20

Sulfated forms of sialyl-Le(X) containing Gal-6-SO(4) or GlcNAc-6-SO(4) have been implicated as potential recognition determinants on high endothelial venule ligands for L-selectin. The optimal configuration of sulfate esters on the N-acetyllactosamine (Galbeta1-->4GlcNAc) core of sulfosialyl-Le(X), however, remains unsettled. Using a panel of sulfated lactose (Galbeta1-->4Glc) neoglycolipids as substrates in direct binding assays, we found that 6',6-disulfolactose was the preferred structure for L-selectin, although significant binding to 6'- and 6-sulfolactose was observed as well. Binding was EDTA-sensitive and blocked by L-selectin-specific monoclonal antibodies. Surprisingly, 6', 6-disulfolactose was poorly recognized by MECA-79, a carbohydrate- and sulfate-dependent monoclonal antibody that binds competitively to L-selectin ligands. Instead, MECA-79 bound preferentially to 6-sulfolactose. The difference in preferred substrates between L-selectin and MECA-79 may explain the variable activity of MECA-79 as an inhibitor of lymphocyte adhesion to high endothelial venules in lymphoid organs. Our results suggest that both Gal-6-SO(4) and GlcNAc-6-SO(4) may contribute to L-selectin recognition, either as components of sulfosialyl-Le(X) capping groups or in internal structures. By contrast, only GlcNAc-6-SO(4) appears to contribute to MECA-79 binding.

A new class of PN3-pincer ligands for metal–ligand cooperative catalysis

KAUST Repository

Li, Huaifeng

2014-12-01

Work on a new class of PN3-pincer ligands for metal-ligand cooperative catalysis is reviewed. While the field of the pyridine-based PN3-transition metal pincer complexes is still relatively young, many important applications of these complexes have already emerged. In several cases, the PN3-pincer complexes for metal-ligand cooperative catalysis result in significantly improved or unprecedented activities. The synthesis and coordination chemistry of PN3-pincer ligands are briefly summarized first to cover the synthetic routes for their preparation, followed by a focus review on their applications in catalysis. A specific emphasis is placed on the later section about the role of PN3-pincer ligands\\' dearomatization-rearomatization steps during the catalytic cycles. The mechanistic insights from density functional theory (DFT) calculations are also discussed.

A new class of PN3-pincer ligands for metal–ligand cooperative catalysis

KAUST Repository

Li, Huaifeng; Zheng, Bin; Huang, Kuo-Wei

2014-01-01

Work on a new class of PN3-pincer ligands for metal-ligand cooperative catalysis is reviewed. While the field of the pyridine-based PN3-transition metal pincer complexes is still relatively young, many important applications of these complexes have already emerged. In several cases, the PN3-pincer complexes for metal-ligand cooperative catalysis result in significantly improved or unprecedented activities. The synthesis and coordination chemistry of PN3-pincer ligands are briefly summarized first to cover the synthetic routes for their preparation, followed by a focus review on their applications in catalysis. A specific emphasis is placed on the later section about the role of PN3-pincer ligands' dearomatization-rearomatization steps during the catalytic cycles. The mechanistic insights from density functional theory (DFT) calculations are also discussed.

Automatic identification of otological drilling faults: an intelligent recognition algorithm.

Science.gov (United States)

Cao, Tianyang; Li, Xisheng; Gao, Zhiqiang; Feng, Guodong; Shen, Peng

2010-06-01

This article presents an intelligent recognition algorithm that can recognize milling states of the otological drill by fusing multi-sensor information. An otological drill was modified by the addition of sensors. The algorithm was designed according to features of the milling process and is composed of a characteristic curve, an adaptive filter and a rule base. The characteristic curve can weaken the impact of the unstable normal milling process and reserve the features of drilling faults. The adaptive filter is capable of suppressing interference in the characteristic curve by fusing multi-sensor information. The rule base can identify drilling faults through the filtering result data. The experiments were repeated on fresh porcine scapulas, including normal milling and two drilling faults. The algorithm has high rates of identification. This study shows that the intelligent recognition algorithm can identify drilling faults under interference conditions. (c) 2010 John Wiley & Sons, Ltd.

Multistage Data Selection-based Unsupervised Speaker Adaptation for Personalized Speech Emotion Recognition

NARCIS (Netherlands)

Kim, Jaebok; Park, Jeong-Sik

This paper proposes an efficient speech emotion recognition (SER) approach that utilizes personal voice data accumulated on personal devices. A representative weakness of conventional SER systems is the user-dependent performance induced by the speaker independent (SI) acoustic model framework. But,

Ammonia formation by metal-ligand cooperative hydrogenolysis of a nitrido ligand

Science.gov (United States)

Askevold, Bjorn; Nieto, Jorge Torres; Tussupbayev, Samat; Diefenbach, Martin; Herdtweck, Eberhardt; Holthausen, Max C.; Schneider, Sven

2011-07-01

Bioinspired hydrogenation of N2 to ammonia at ambient conditions by stepwise nitrogen protonation/reduction with metal complexes in solution has experienced remarkable progress. In contrast, the highly desirable direct hydrogenation with H2 remains difficult. In analogy to the heterogeneously catalysed Haber-Bosch process, such a reaction is conceivable via metal-centred N2 splitting and unprecedented hydrogenolysis of the nitrido ligands to ammonia. We report the synthesis of a ruthenium(IV) nitrido complex. The high nucleophilicity of the nitrido ligand is demonstrated by unusual N-C coupling with π-acidic CO. Furthermore, the terminal nitrido ligand undergoes facile hydrogenolysis with H2 at ambient conditions to produce ammonia in high yield. Kinetic and quantum chemical examinations of this reaction suggest cooperative behaviour of a phosphorus-nitrogen-phosphorus pincer ligand in rate-determining heterolytic hydrogen splitting.

iNKT Cells and Their potential Lipid Ligands during Viral Infection

Directory of Open Access Journals (Sweden)

Anunya eOpasawatchai

2015-07-01

Full Text Available Invariant natural killer T (iNKT cells are a unique population of lipid reactive CD1d restricted innate-like T lymphocytes. Despite being a minor population, they serve as an early source of cytokines and promote immunological crosstalk thus bridging innate and adaptive immunity. Diseases ranging from allergy, autoimmunity, and cancer as well as infectious diseases, including viral infection, have been reported to be influenced by iNKT cells. However, it remains unclear how iNKT cells are activated during viral infection, as virus derived lipid antigens have not been reported. Cytokines may activate iNKT cells during infections from influenza and murine cytomegalovirus (MCMV, although CD1d dependent activation is evident in other viral infections. Several viruses, such as dengue virus (DENV, induce CD1d upregulation which correlates with iNKT cell activation. In contrast, Herpes simplex virus type 1 (HSV-1, Human immunodeficiency virus (HIV, Epstein-Barr virus (EBV and Human papiloma virus (HPV promote CD1d downregulation as a strategy to evade iNKT cell recognition. These observations suggest the participation of a CD1d-dependent process in the activation of iNKT cells in response to viral infection. Endogenous lipid ligands, including phospholipids as well as glycosphingolipids, such as glucosylceramide have been proposed to mediate iNKT cell activation. Pro-inflammatory signals produced during viral infection may stimulate iNKT cells through enhanced CD1d dependent endogenous lipid presentation. Furthermore, viral infection may alter lipid composition and inhibit endogenous lipid degradation. Recent advances in this field are reviewed.

Reduction of dinitrogen ligands

International Nuclear Information System (INIS)

Richards, R.L.

1983-01-01

Processes of dinitrogen ligand reduction in complexes of transition metals are considered. The basic character of the dinitrogen ligand is underlined. Data on X-ray photoelectronic spectroscopy and intensities of bands ν (N 2 ) in IR-spectra of nitrogen complexes are given. The mechanism of protonation of an edge dinitrogen ligand is discussed. Model systems and mechanism of nitrogenogenase are compared

How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

Science.gov (United States)

Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

2015-01-01

The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy. Copyright © 2014 Elsevier B.V. All rights reserved.

Biochip microsystem for bioinformatics recognition and analysis

Science.gov (United States)

Lue, Jaw-Chyng (Inventor); Fang, Wai-Chi (Inventor)

2011-01-01

A system with applications in pattern recognition, or classification, of DNA assay samples. Because DNA reference and sample material in wells of an assay may be caused to fluoresce depending upon dye added to the material, the resulting light may be imaged onto an embodiment comprising an array of photodetectors and an adaptive neural network, with applications to DNA analysis. Other embodiments are described and claimed.

Pathogen recognition in the innate immune response.

Science.gov (United States)

Kumar, Himanshu; Kawai, Taro; Akira, Shizuo

2009-04-28

Immunity against microbial pathogens primarily depends on the recognition of pathogen components by innate receptors expressed on immune and non-immune cells. Innate receptors are evolutionarily conserved germ-line-encoded proteins and include TLRs (Toll-like receptors), RLRs [RIG-I (retinoic acid-inducible gene-I)-like receptors] and NLRs (Nod-like receptors). These receptors recognize pathogens or pathogen-derived products in different cellular compartments, such as the plasma membrane, the endosomes or the cytoplasm, and induce the expression of cytokines, chemokines and co-stimulatory molecules to eliminate pathogens and instruct pathogen-specific adaptive immune responses. In the present review, we will discuss the recent progress in the study of pathogen recognition by TLRs, RLRs and NLRs and their signalling pathways.

Modulation of neonatal microbial recognition: TLR-mediated innate immune responses are specifically and differentially modulated by human milk.

Science.gov (United States)

LeBouder, Emmanuel; Rey-Nores, Julia E; Raby, Anne-Catherine; Affolter, Michael; Vidal, Karine; Thornton, Catherine A; Labéta, Mario O

2006-03-15

The mechanisms controlling innate microbial recognition in the neonatal gut are still to be fully understood. We have sought specific regulatory mechanisms operating in human breast milk relating to TLR-mediated microbial recognition. In this study, we report a specific and differential modulatory effect of early samples (days 1-5) of breast milk on ligand-induced cell stimulation via TLRs. Although a negative modulation was exerted on TLR2 and TLR3-mediated responses, those via TLR4 and TLR5 were enhanced. This effect was observed in human adult and fetal intestinal epithelial cell lines, monocytes, dendritic cells, and PBMC as well as neonatal blood. In the latter case, milk compensated for the low capacity of neonatal plasma to support responses to LPS. Cell stimulation via the IL-1R or TNFR was not modulated by milk. This, together with the differential effect on TLR activation, suggested that the primary effect of milk is exerted upstream of signaling proximal to TLR ligand recognition. The analysis of TLR4-mediated gene expression, used as a model system, showed that milk modulated TLR-related genes differently, including those coding for signal intermediates and regulators. A proteinaceous milk component of > or =80 kDa was found to be responsible for the effect on TLR4. Notably, infant milk formulations did not reproduce the modulatory activity of breast milk. Together, these findings reveal an unrecognized function of human milk, namely, its capacity to influence neonatal microbial recognition by modulating TLR-mediated responses specifically and differentially. This in turn suggests the existence of novel mechanisms regulating TLR activation.

The role of metalloproteinase ADAM17 in regulating ICOS ligand-mediated humoral immune responses

DEFF Research Database (Denmark)

Marczynska, Joanna; Ozga, Aleksandra; Wlodarczyk, Agnieszka

2014-01-01

results in spleen and lymph node enlargement, as well as increased levels of Ag-specific class-switched Ig production following immunization with OVA together with anti-CD40 mAbs and polyinosinic-polycytidylic acid. Moreover, we demonstrate that the costimulatory ligand ICOS ligand (ICOSL) is selectively...... downregulated on the surface of B cells in an ADAM17-specific manner, although it is not proteolitically processed by recombinant ADAM17 in vitro. Finally, we show that higher cell surface levels of ICOSL in ADAM17(ex/ex) mice may contribute to the development of excessive Ab responses. Therefore, our data...... suggest a functional link between ADAM17 and ICOSL in controlling adaptive immune responses....

Limitations of science and adapting to Nature

International Nuclear Information System (INIS)

Narasimhan, T N

2007-01-01

Historically, science has pursued a premise that Nature can be understood fully, its future predicted precisely, and its behavior controlled at will. However, emerging knowledge indicates that the nature of Earth and biological systems transcends the limits of science, questioning the premise of knowing, prediction, and control. This knowledge has led to the recognition that, for civilized human survival, technological society has to adapt to the constraints of these systems. Simultaneously, spurred by explosive developments in the understanding of materials (non-biological and biological), applied scientific research pursues a contrary goal of controlling the material world, with the promise of spectacular economic growth and human well-being. If adaptation to Nature is so important, why does applied research pursue a contrary course? Adapting to Nature requires a recognition of the limitations of science, and espousal of human values. Although the concept of adapting to Nature is accepted by some, especially conservation ecologists, such an acceptance may not exist in other fields. Also, in a world dominated by democratic ideals of freedom and liberty, the discipline required for adapting to Nature may often be overridden by competition among various segments of society to exercise their respective rights. In extreme cases of catastrophic failure of Earth or biological systems, the imperative for adaptation may fall victim to instinct for survival. In essence, although adequate scientific know-how and technological competence exists to facilitate adaptation to Nature, choosing between that and the pursuit of controlling Nature entails human judgment. What that choice may be when humans have to survive under severe environmental stress cannot be predicted

Limitations of science and adapting to Nature

Energy Technology Data Exchange (ETDEWEB)

Narasimhan, T N [Department of Materials Science and Engineering, Department of Environmental Science, Policy and Management, 210 Hearst Memorial Mining Building, University of California, Berkeley, CA 94720-1760 (United States)

2007-07-15

Historically, science has pursued a premise that Nature can be understood fully, its future predicted precisely, and its behavior controlled at will. However, emerging knowledge indicates that the nature of Earth and biological systems transcends the limits of science, questioning the premise of knowing, prediction, and control. This knowledge has led to the recognition that, for civilized human survival, technological society has to adapt to the constraints of these systems. Simultaneously, spurred by explosive developments in the understanding of materials (non-biological and biological), applied scientific research pursues a contrary goal of controlling the material world, with the promise of spectacular economic growth and human well-being. If adaptation to Nature is so important, why does applied research pursue a contrary course? Adapting to Nature requires a recognition of the limitations of science, and espousal of human values. Although the concept of adapting to Nature is accepted by some, especially conservation ecologists, such an acceptance may not exist in other fields. Also, in a world dominated by democratic ideals of freedom and liberty, the discipline required for adapting to Nature may often be overridden by competition among various segments of society to exercise their respective rights. In extreme cases of catastrophic failure of Earth or biological systems, the imperative for adaptation may fall victim to instinct for survival. In essence, although adequate scientific know-how and technological competence exists to facilitate adaptation to Nature, choosing between that and the pursuit of controlling Nature entails human judgment. What that choice may be when humans have to survive under severe environmental stress cannot be predicted.

MR1-restricted MAIT cells display ligand discrimination and pathogen selectivity through distinct T cell receptor usage

DEFF Research Database (Denmark)

Gold, Marielle C.; McLaren, James E.; Reistetter, Joseph A.

2015-01-01

with this interpretation, MAIT cell clones with distinct TCRs responded differentially to a riboflavin metabolite. These results suggest that MAIT cells can discriminate between pathogen-derived ligands in a clonotype-dependent manner, providing a basis for adaptive memory via recruitment of specific repertoires shaped...

Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions

Directory of Open Access Journals (Sweden)

Slobodan Beroš

2012-10-01

Full Text Available The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.

Applications of evolutionary computation in image processing and pattern recognition

CERN Document Server

Cuevas, Erik; Perez-Cisneros, Marco

2016-01-01

This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an...

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

Directory of Open Access Journals (Sweden)

Min Peng

2017-10-01

Full Text Available Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

Science.gov (United States)

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

Science.gov (United States)

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

Ligand modeling and design

Energy Technology Data Exchange (ETDEWEB)

Hay, B.P. [Pacific Northwest National Lab., Richland, WA (United States)

1997-10-01

The purpose of this work is to develop and implement a molecular design basis for selecting organic ligands that would be used in the cost-effective removal of specific radionuclides from nuclear waste streams. Organic ligands with metal ion specificity are critical components in the development of solvent extraction and ion exchange processes that are highly selective for targeted radionuclides. The traditional approach to the development of such ligands involves lengthy programs of organic synthesis and testing, which in the absence of reliable methods for screening compounds before synthesis, results in wasted research effort. The author`s approach breaks down and simplifies this costly process with the aid of computer-based molecular modeling techniques. Commercial software for organic molecular modeling is being configured to examine the interactions between organic ligands and metal ions, yielding an inexpensive, commercially or readily available computational tool that can be used to predict the structures and energies of ligand-metal complexes. Users will be able to correlate the large body of existing experimental data on structure, solution binding affinity, and metal ion selectivity to develop structural design criteria. These criteria will provide a basis for selecting ligands that can be implemented in separations technologies through collaboration with other DOE national laboratories and private industry. The initial focus will be to select ether-based ligands that can be applied to the recovery and concentration of the alkali and alkaline earth metal ions including cesium, strontium, and radium.

Ligand identification using electron-density map correlations

International Nuclear Information System (INIS)

Terwilliger, Thomas C.; Adams, Paul D.; Moriarty, Nigel W.; Cohn, Judith D.

2007-01-01

An automated ligand-fitting procedure is applied to (F o − F c )exp(iϕ c ) difference density for 200 commonly found ligands from macromolecular structures in the Protein Data Bank to identify ligands from density maps. A procedure for the identification of ligands bound in crystal structures of macromolecules is described. Two characteristics of the density corresponding to a ligand are used in the identification procedure. One is the correlation of the ligand density with each of a set of test ligands after optimization of the fit of that ligand to the density. The other is the correlation of a fingerprint of the density with the fingerprint of model density for each possible ligand. The fingerprints consist of an ordered list of correlations of each the test ligands with the density. The two characteristics are scored using a Z-score approach in which the correlations are normalized to the mean and standard deviation of correlations found for a variety of mismatched ligand-density pairs, so that the Z scores are related to the probability of observing a particular value of the correlation by chance. The procedure was tested with a set of 200 of the most commonly found ligands in the Protein Data Bank, collectively representing 57% of all ligands in the Protein Data Bank. Using a combination of these two characteristics of ligand density, ranked lists of ligand identifications were made for representative (F o − F c )exp(iϕ c ) difference density from entries in the Protein Data Bank. In 48% of the 200 cases, the correct ligand was at the top of the ranked list of ligands. This approach may be useful in identification of unknown ligands in new macromolecular structures as well as in the identification of which ligands in a mixture have bound to a macromolecule

Surveillance of a nuclear reactor core by use of a pattern recognition method

International Nuclear Information System (INIS)

Invernizzi, Michel.

1982-07-01

A pattern recognition system is described for the surveillance of a PWR reactor. This report contains four chapters. The first one succinctly deals with statistical pattern recognition principles. In the second chapter we show how a surveillance problem may be treated by pattern recognition and we present methods for surveillances (detection of abnormalities), controls (kind of running recognition) and diagnotics (kind of abnormality recognition). The third chapter shows a surveillance method of a nuclear plant. The signals used are the neutron noise observations made by the ionization chambers inserted in the reactor. Abnormality is defined in opposition with the training set witch is supposed to be an exhaustive summary of normality. In the fourth chapter we propose a scheme for an adaptative recognition and a method based on classes modelisations by hyper-spheres. This method has been tested on simulated training sets in two-dimensional feature spaces. It gives solutions to problems of non-linear separability [fr

Ligand-induced association of surface immunoglobulin with the detergent insoluble cytoskeleton may involve an 89K protein

International Nuclear Information System (INIS)

Gupta, S.K.; Woda, B.

1986-01-01

Membrane immunoglobulin of B-lymphocytes is thought to play an important role in antigen recognition and cellular activation. Binding of cross-linking ligands to surface immunoglobulin (SIg) on intact cells converts it to a detergent insoluble state, and this conversion is associated with the transmission of a mitogenic signal. Insolubilized membrane proteins may be solubilized by incubating the detergent insoluble cytoskeletons in buffers which convert F-actin to G-actin [(Buffer 1), 0.34M sucrose, 0.5mM ATP, 0.5mM Dithiothrietol and lmM EDTA]. Immunoprecipitation of SIg from the detergent soluble fraction of 35 S-methionine labeled non ligand treated rat B-cells results in the co-isolation of an 89K protein and a 44K protein, presumably actin. The 89K protein is not associated with the fraction of endogenous detergent insoluble SIg. On treatment of rat B cells with cross-linking ligand (anti-Ig) the 89K protein becomes detergent insoluble along with most of the SIg and co-isolates with SIg on immunoprecipitation of the detergent insoluble, buffer l solubilized fraction. The migration of the SIg-associated 89K protein from the detergent soluble fraction to the detergent insoluble fraction after ligand treatment, suggests that this protein might be involved in linking SIg to the underlying cytoskeleton and could be involved in the transmission of a mitogenic signal

Stimulus effects and the mediation of recognition memory.

Science.gov (United States)

McAdoo, Ryan M; Key, Kylie N; Gronlund, Scott D

2018-04-19

Two broad approaches characterize the type of evidence that mediates recognition memory: discrete state and continuous. Discrete-state models posit a thresholded memory process that provides accurate information about an item (it is detected) or, failing that, no mnemonic information about the item. Continuous models, in contrast, posit the existence of graded mnemonic information about an item. Evidence favoring 1 approach over the other has been mixed, suggesting the possibility that the mediation of recognition memory may be adaptable and influenced by other factors. We tested this possibility with 2 experiments that varied the semantic similarity of word targets and fillers. Experiment 1, which used semantically similar fillers, displayed evidence of continuous mediation (contrary to Kellen & Klauer, 2015), whereas Experiment 2, which used semantically dissimilar fillers, displayed evidence of discrete mediation. The results have implications for basic theories of recognition memory, as well as for theories of applied domains like eyewitness identification. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Schiff base ligand

Indian Academy of Sciences (India)

Unknown

Low-temperature stoichiometric Schiff base reaction in air in 3 : 1 mole ratio between benz- aldehyde and triethylenetetramine (trien) in methanol yields a novel tetraaza µ-bis(bidentate) acyclic ligand L. It was .... electrochemical work was performed as reported in ..... change in ligand shape through change in oxidation.

DMBT1 functions as pattern-recognition molecule for poly-sulfated and poly-phosphorylated ligands

DEFF Research Database (Denmark)

End, Caroline; Bikker, Floris; Renner, Marcus

2009-01-01

at unraveling the molecular basis of its function in mucosal protection and of its broad pathogen-binding specificity. We report that DMBT1 directly interacts with dextran sulfate sodium (DSS) and carrageenan, a structurally similar sulfated polysaccharide, which is used as a texturizer and thickener in human...... dietary products. However, binding of DMBT1 does not reduce the cytotoxic effects of these agents to intestinal epithelial cells in vitro. DSS and carrageenan compete for DMBT1-mediated bacterial aggregation via interaction with its bacterial-recognition motif. Competition and ELISA studies identify poly...

Social capital, conflict, and adaptive collaborative governance

NARCIS (Netherlands)

McDougall, C.L.; Ram Banjade, Mani

2015-01-01

Previously lineal and centralized natural resource management and development paradigms have shifted toward the recognition of complexity and dynamism of social-ecological systems, and toward more adaptive, decentralized, and collaborative models. However, certain messy and surprising dynamics

Evaluation of Adaptive Noise Management Technologies for School-Age Children with Hearing Loss.

Science.gov (United States)

Wolfe, Jace; Duke, Mila; Schafer, Erin; Jones, Christine; Rakita, Lori

2017-05-01

Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations. The objective of this study was to compare speech recognition, speech intelligibility ratings (SIRs), and sound preferences of children using hearing aids equipped with and without adaptive noise management technologies. A single-group, repeated measures design was used to evaluate performance differences obtained in four simulated environments. In each simulated environment, participants were tested in a basic listening program with minimal noise management features, a manual program designed for that scene, and the hearing instruments' adaptive operating system that steered hearing instrument parameterization based on the characteristics of the environment. Twelve children with mild to moderately severe sensorineural hearing loss. Speech recognition and SIRs were evaluated in three hearing aid programs with and without noise management technologies across two different test sessions and various listening environments. Also, the participants' perceptual hearing performance in daily real-world listening situations with two of the hearing aid programs was evaluated during a four- to six-week field trial that took place between the two laboratory sessions. On average, the use of adaptive noise management technology improved sentence recognition in noise for speech presented in front of the participant but resulted in a decrement in performance for signals arriving from behind when the participant was facing forward. However, the improvement

The thermodynamic effects of ligand structure on the molecular recognition of mononuclear ruthenium polypyridyl complexes with B-DNA

Science.gov (United States)

The ruthenium(II) polypyridyl complexes (RPCs), [(phen)2Ru(tatpp)]Cl2 (3Cl2) and [(phen)2Ru (tatpp)Ru(phen)2]Cl4 (4Cl4), containing the large planar and redox-active tetraazatetrapyrido- pentacene (tatpp) ligand, cleave DNA in the presence of reducing agents in cell-free assays and show significant...

A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

Science.gov (United States)

Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

2012-07-01

We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Complement activating soluble pattern recognition molecules with collagen-like regions, mannan-binding lectin, ficolins and associated proteins

DEFF Research Database (Denmark)

Thiel, Steffen

2007-01-01

Mannan-binding lectin (MBL), L-ficolin, M-ficolin and H-ficolin are all complement activating soluble pattern recognition molecules with recognition domains linked to collagen-like regions. All four may form complexes with four structurally related proteins, the three MBL-associated serine...... proteases (MASPs), MASP-1, MASP-2 and MASP-3, and a smaller MBL-associated protein (MAp19). The four recognition molecules recognize patterns of carbohydrate or acetyl-group containing ligands. After binding to the relevant targets all four are able to activate the complement system. We thus have a system...... where four different and/or overlapping patterns of microbial origin or patterns of altered-self may be recognized, but in all cases the signalling molecules, the MASPs, are shared. MASP-1 and MASP-3 are formed from one gene, MASP1/3, by alternative splicing generating two different mRNAs from a single...

A Spatial Frequency Account of the Detriment that Local Processing of Navon Letters Has on Face Recognition

Science.gov (United States)

Hills, Peter J.; Lewis, Michael B.

2009-01-01

Five minutes of processing the local features of a Navon letter causes a detriment in subsequent face-recognition performance (Macrae & Lewis, 2002). We hypothesize a perceptual after effect explanation of this effect in which face recognition is less accurate after adapting to high-spatial frequencies at high contrasts. Five experiments were…

ProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites.

Science.gov (United States)

Konc, Janez; Janežič, Dušanka

2014-07-01

The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites to the query protein. Such ligand prediction supports many activities, e.g. drug repurposing. The ProBiS-ligands web server, an extension of the ProBiS web server, is open and free to all users at http://probis.cmm.ki.si/ligands. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Development of Spatial Frequency Biases in Face Recognition

Science.gov (United States)

Leonard, Hayley C.; Karmiloff-Smith, Annette; Johnson, Mark H.

2010-01-01

Previous research has suggested that a mid-band of spatial frequencies is critical to face recognition in adults, but few studies have explored the development of this bias in children. We present a paradigm adapted from the adult literature to test spatial frequency biases throughout development. Faces were presented on a screen with particular…

Neural Mechanisms and Information Processing in Recognition Systems

Directory of Open Access Journals (Sweden)

Mamiko Ozaki

2014-10-01

Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

Interaction of calreticulin with CD40 ligand, TRAIL and Fas ligand

DEFF Research Database (Denmark)

Duus, K; Pagh, R T; Holmskov, U

2007-01-01

is utilized by many other functionally diverse molecules and in this work the interaction of calreticulin with C1q and structurally similar molecules was investigated. In addition to C1q and MBL, CD40 ligand (CD40L), tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) and Fas ligand (FasL) were...... found to bind calreticulin strongly. A low level or no binding was observed for adiponectin, tumour necrosis factor-alpha (TNF-alpha), CD30L, surfactant protein-A and -D and collagen VIII. The interaction with calreticulin required a conformational change in CD40L, TRAIL and FasL and showed the same...

View-invariant gait recognition method by three-dimensional convolutional neural network

Science.gov (United States)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Tracking and recognition face in videos with incremental local sparse representation model

Science.gov (United States)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Calreticulin discriminates the proximal region at the N-glycosylation site of Glc1Man9GlcNAc2 ligand

Energy Technology Data Exchange (ETDEWEB)

Hirano, Makoto; Adachi, Yuka [Department of Materials and Life Science, Seikei University, 3-3-1 Kichijoji-kita, Musashino, Tokyo 180-8633 (Japan); Ito, Yukishige [Synthetic Cellular Chemistry Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); ERATO, Japan Science and Technology Agency, Ito Glycotrilogy Project, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Totani, Kiichiro, E-mail: ktotani@st.seikei.ac.jp [Department of Materials and Life Science, Seikei University, 3-3-1 Kichijoji-kita, Musashino, Tokyo 180-8633 (Japan)

2015-10-23

Calreticulin (CRT) is well known as a lectin-like chaperone that recognizes Glc1Man9GlcNAc2 (G1M9)-glycoproteins in the endoplasmic reticulum (ER). However, whether CRT can directly interact with the aglycone moiety (protein portion) of the glycoprotein remains controversial. To improve our understanding of CRT interactions, structure-defined G1M9-derivatives with different aglycones (–OH, –Gly–NH{sub 2}, and –Gly–Glu–{sup t}Bu) were used as CRT ligands, and their interactions with recombinant CRT were analyzed using thermal shift analysis. The results showed that CRT binds strongly to a G1M9-ligand in the order –Gly–Glu–{sup t}Bu > –Gly–NH{sub 2} > –OH, which is the same as that of the reglucosylation of Man9GlcNAc2 (M9)-derivatives by the folding sensor enzyme UGGT (UDP-glucose: glycoprotein glucosyltransferase). Our results indicate that, similar to UGGT, CRT discriminates the proximal region at the N-glycosylation site, suggesting a similar mechanism mediating the recognition of aglycone moieties in the ER glycoprotein quality control system. - Highlights: • Glc1Man9GlcNAc2 (G1M9) ligands with different aglycones were chemically prepared. • Calreticulin (CRT) discriminates the aglycone of Glc1Man9GlcNAc2 (G1M9) ligand. • CRT binds with G1M9 ligands in a similar manner to folding sensor enzyme.

Enhancement of antiviral activity of collectin trimers through cross-linking and mutagenesis of the carbohydrate recognition domain

DEFF Research Database (Denmark)

White, Mitchell R; Boland, Patrick; Tecle, Tesfaldet

2010-01-01

Surfactant protein D (SP-D) plays important roles in innate defense against respiratory viruses [including influenza A viruses (IAVs)]. Truncated trimers composed of its neck and carbohydrate recognition domains (NCRDs) bind various ligands; however, they have minimal inhibitory activity for IAV......., complementary strategies, namely cross-linking of NCRDs through various means and mutagenesis of CRD residues to increase viral binding. These findings may be relevant for antiviral therapy....

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

Bitopic Ligands and Metastable Binding Sites

DEFF Research Database (Denmark)

Fronik, Philipp; Gaiser, Birgit I; Sejer Pedersen, Daniel

2017-01-01

of orthosteric binding sites. Bitopic ligands have been employed to address the selectivity problem by combining (linking) an orthosteric ligand with an allosteric modulator, theoretically leading to high-affinity subtype selective ligands. However, it remains a challenge to identify suitable allosteric binding...... that have been reported to date, this type of bitopic ligands would be composed of two identical pharmacophores. Herein, we outline the concept of bitopic ligands, review metastable binding sites, and discuss their potential as a new source of allosteric binding sites....

Towards Adaptive Spoken Dialog Systems

CERN Document Server

Schmitt, Alexander

2013-01-01

In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and  accurate use.  Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted  recordings several thousand real users from commercial and non-commercial SDS. Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer m...

Foreign Language Analysis and Recognition (FLARe) Initial Progress

Science.gov (United States)

2012-11-29

speaker diarization code was optimized to execute faster and yield a lower Diarization Error Rate (DER). Minimizing the file read and write operations...PLP features were calculated using the same procedure described in Section 2.1.1 A second set of models was estimated that include Speaker Adaptive...non-SAT HMMs. Constrained Maximum Likelihood Linear Regression (CMLLR) transforms were estimated for each speaker , and recognition lattices were

Semisupervised kernel marginal Fisher analysis for face recognition.

Science.gov (United States)

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

Reactor noise analysis by statistical pattern recognition methods

International Nuclear Information System (INIS)

Howington, L.C.; Gonzalez, R.C.

1976-01-01

A multivariate statistical pattern recognition system for reactor noise analysis is presented. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, updating, and data compacting capabilities. System design emphasizes control of the false-alarm rate. Its abilities to learn normal patterns, to recognize deviations from these patterns, and to reduce the dimensionality of data with minimum error were evaluated by experiments at the Oak Ridge National Laboratory (ORNL) High-Flux Isotope Reactor. Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the pattern recognition system

Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

Directory of Open Access Journals (Sweden)

Arnout Voet

Full Text Available One of the underlying principles in drug discovery is that a biologically active compound is complimentary in shape and molecular recognition features to its receptor. This principle infers that molecules binding to the same receptor may share some common features. Here, we have investigated whether the electrostatic similarity can be used for the discovery of small molecule protein-protein interaction inhibitors (SMPPIIs. We have developed a method that can be used to evaluate the similarity of electrostatic potentials between small molecules and known protein ligands. This method was implemented in a software called EleKit. Analyses of all available (at the time of research SMPPII structures indicate that SMPPIIs bear some similarities of electrostatic potential with the ligand proteins of the same receptor. This is especially true for the more polar SMPPIIs. Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.

Shape adaptive, robust iris feature extraction from noisy iris images.

Science.gov (United States)

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-10-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

Stages of processing in associative recognition: evidence from behavior, EEG, and classification.

Science.gov (United States)

Borst, Jelmer P; Schneider, Darryl W; Walsh, Matthew M; Anderson, John R

2013-12-01

In this study, we investigated the stages of information processing in associative recognition. We recorded EEG data while participants performed an associative recognition task that involved manipulations of word length, associative fan, and probe type, which were hypothesized to affect the perceptual encoding, retrieval, and decision stages of the recognition task, respectively. Analyses of the behavioral and EEG data, supplemented with classification of the EEG data using machine-learning techniques, provided evidence that generally supported the sequence of stages assumed by a computational model developed in the Adaptive Control of Thought-Rational cognitive architecture. However, the results suggested a more complex relationship between memory retrieval and decision-making than assumed by the model. Implications of the results for modeling associative recognition are discussed. The study illustrates how a classifier approach, in combination with focused manipulations, can be used to investigate the timing of processing stages.

A neuroanatomical predictor of mirror self-recognition in chimpanzees.

Science.gov (United States)

Hecht, E E; Mahovetz, L M; Preuss, T M; Hopkins, W D

2017-01-01

The ability to recognize one's own reflection is shared by humans and only a few other species, including chimpanzees. However, this ability is highly variable across individual chimpanzees. In humans, self-recognition involves a distributed, right-lateralized network including frontal and parietal regions involved in the production and perception of action. The superior longitudinal fasciculus (SLF) is a system of white matter tracts linking these frontal and parietal regions. The current study measured mirror self-recognition (MSR) and SLF anatomy in 60 chimpanzees using diffusion tensor imaging. Successful self-recognition was associated with greater rightward asymmetry in the white matter of SLFII and SLFIII, and in SLFIII's gray matter terminations in Broca's area. We observed a visible progression of SLFIII's prefrontal extension in apes that show negative, ambiguous, and compelling evidence of MSR. Notably, SLFIII's terminations in Broca's area are not right-lateralized or particularly pronounced at the population level in chimpanzees, as they are in humans. Thus, chimpanzees with more human-like behavior show more human-like SLFIII connectivity. These results suggest that self-recognition may have co-emerged with adaptations to frontoparietal circuitry. © The Author (2016). Published by Oxford University Press.

Gait Recognition Based on Outermost Contour

Directory of Open Access Journals (Sweden)

Lili Liu

2011-10-01

Full Text Available Gait recognition aims to identify people by the way they walk. In this paper, a simple but e ective gait recognition method based on Outermost Contour is proposed. For each gait image sequence, an adaptive silhouette extraction algorithm is firstly used to segment the frames of the sequence and a series of postprocessing is applied to obtain the normalized silhouette images with less noise. Then a novel feature extraction method based on Outermost Contour is performed. Principal Component Analysis (PCA is adopted to reduce the dimensionality of the distance signals derived from the Outermost Contours of silhouette images. Then Multiple Discriminant Analysis (MDA is used to optimize the separability of gait features belonging to di erent classes. Nearest Neighbor (NN classifier and Nearest Neighbor classifier with respect to class Exemplars (ENN are used to classify the final feature vectors produced by MDA. In order to verify the e ectiveness and robustness of our feature extraction algorithm, we also use two other classifiers: Backpropagation Neural Network (BPNN and Support Vector Machine (SVM for recognition. Experimental results on a gait database of 100 people show that the accuracy of using MDA, BPNN and SVM can achieve 97.67%, 94.33% and 94.67%, respectively.

Spectrophotometric method for determination of bifunctional macrocyclic ligands in macrocyclic ligand-protein conjugates

International Nuclear Information System (INIS)

Dadachova, E.; Chappell, L.L.; Brechbiel, M.W.

1999-01-01

A simple spectrophotometric assay for determination of bifunctional polyazacarboxylate-macrocyclic ligands of different sizes that are conjugated to proteins has been developed for: 12-membered macrocycle DOTA (2-[4-nitrobenzyl]-1, 4, 7, 10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid) and analogs, the 15-membered PEPA macrocycle (2-[4-nitrobenzyl]-1,4,7,10,13-pentaazacyclopentadecane-N,N',N'',N''',N'''' -pentaacetic acid), and the large 18-membered macrocycle HEHA (1,4,7,10,13,16-hexaazacyclooctadecane-N,N',N'',N''',N''''-hexaacetic acid). The method is based on titration of the blue-colored 1:1 Pb(II)-Arsenazo III (AAIII) complex with the polyazacarboxylate macrocyclic ligand in the concentration range of 0-2.5 μM, wherein color change occurring upon transchelation of the Pb(II) from the AAIII to the polyazamacrocyclic ligand is monitored at 656 nm. The assay is performed at ambient temperature within 20 min without any interfering interaction between the protein and Pb(II)-AA(III) complex. Thus, this method also provides a ligand-to-protein ratio (L/P ratio) that reflects the effective number of ligands per protein molecule available to radiolabeling. The method is not suitable for 14-membered TETA macrocycle (2-[4-nitrobenzyl]-1, 4, 8, 11-tetraazacyclotetradecane N,N',N'',N'''-tetraacetic acid) because of low stability constant of Pb(II)-TETA complex. The method is rapid, simple and may be customized for other polyazacarboxylate macrocyclic ligands

Airfuge centrifugation procedure for the measurement of ligand binding to membrane-associated and detergent-solubilized plasma membrane receptors

Energy Technology Data Exchange (ETDEWEB)

Li, E L.F.; Perdue, J F [Lady Davis Institute, Sir Mortimer B. Davis Jewish General Hospital, Montreal, Quebec, Canada

1980-10-01

A method is described in which high-speed centrifugation of membranes through an oil phase is used to separate membrane-bound and detergent-solubilized polypeptide receptor-iodinated ligand complexes from unbound ligands. Three centrifuges, the Brinkmann Eppendorf (5412), the Beckman Microfuge B and the Beckman Airfuge were evaluated for this capability. Under the conditions described, the Beckman Airfuge surpassed the others in recovering previously /sup 125/I- and /sup 32/P-labelled cell membranes. The Airfuge method was compared with the more classically employed membrane filtration method to measure specific (/sup 125/I)insulin and (/sup 125/I)thrombin binding to human placental membranes and an enriched plasma membrane fraction from mouse embryo fibroblasts, respectively, and found to be 4 to 5 times more sensitive. For example, specific binding of ligand to its receptor was demonstrated with 5 ..mu..g of protein. With slight modifications, the polyethyleneglycol 6000 method of precipitating /sup 125/I-labelled ligand-soluble receptor complexes can be adapted to the Airfuge sedimentation through oil procedure.

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

Rosetta Ligand docking with flexible XML protocols.

Science.gov (United States)

Lemmon, Gordon; Meiler, Jens

2012-01-01

RosettaLigand is premiere software for predicting how a protein and a small molecule interact. Benchmark studies demonstrate that 70% of the top scoring RosettaLigand predicted interfaces are within 2Å RMSD from the crystal structure [1]. The latest release of Rosetta ligand software includes many new features, such as (1) docking of multiple ligands simultaneously, (2) representing ligands as fragments for greater flexibility, (3) redesign of the interface during docking, and (4) an XML script based interface that gives the user full control of the ligand docking protocol.

CRISPR-Cas: Adapting to change.

Science.gov (United States)

Jackson, Simon A; McKenzie, Rebecca E; Fagerlund, Robert D; Kieper, Sebastian N; Fineran, Peter C; Brouns, Stan J J

2017-04-07

Bacteria and archaea are engaged in a constant arms race to defend against the ever-present threats of viruses and invasion by mobile genetic elements. The most flexible weapons in the prokaryotic defense arsenal are the CRISPR-Cas adaptive immune systems. These systems are capable of selective identification and neutralization of foreign DNA and/or RNA. CRISPR-Cas systems rely on stored genetic memories to facilitate target recognition. Thus, to keep pace with a changing pool of hostile invaders, the CRISPR memory banks must be regularly updated with new information through a process termed CRISPR adaptation. In this Review, we outline the recent advances in our understanding of the molecular mechanisms governing CRISPR adaptation. Specifically, the conserved protein machinery Cas1-Cas2 is the cornerstone of adaptive immunity in a range of diverse CRISPR-Cas systems. Copyright © 2017, American Association for the Advancement of Science.

Ligand-receptor Interactions by NMR Spectroscopy

Directory of Open Access Journals (Sweden)

Novak. P.

2008-04-01

Full Text Available Today NMR spectroscopy is a method of choice for elucidation of interactions between biomolecules and the potential ligands. Knowledge on these interactions is an essential prerequisite for the rational drug design. The most important contribution of NMR to drug design a few years ago was the 3D structure determination of proteins. Besides delivering the 3D structures of the free proteins as a raw material for the modeling studies on ligand binding, NMR can directly yield valuable experimental data on the biologically important protein-ligand complexes. In addition to X-ray diffraction, NMR spectroscopy can provide information on the internal protein dynamics ordynamics of intermolecular interactions. Changes in NMR parameters allow us to detect ("SAR by NMR" and quantitatively determine binding affinities (titration, diffusion NMR experiments, etc. of potential ligands. Also, it is possible to determine the binding site and conformations of ligands, receptors and receptor-ligand complexes with the help of NMR methods such as tr-NOESY. Epitopes or functional groups responsible for binding of ligands to the receptor can be identified by employing STD or WaterLOGSY experiments. In this review are described some of the most frequent NMR methods for the characterization of the interactions between biomolecules and ligands, together with their advantages and disadvantages.

A Dynamic Time Warping Approach to Real-Time Activity Recognition for Food Preparation

Science.gov (United States)

Pham, Cuong; Plötz, Thomas; Olivier, Patrick

We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.

Authentication: From Passwords to Biometrics: An implementation of a speaker recognition system on Android

OpenAIRE

Heimark, Erlend

2012-01-01

We implement a biometric authentication system on the Android platform, which is based on text-dependent speaker recognition. The Android version used in the application is Android 4.0. The application makes use of the Modular Audio Recognition Framework, from which many of the algorithms are adapted in the processes of preprocessing and feature extraction. In addition, we employ the Dynamic Time Warping (DTW) algorithm for the comparison of different voice features. A training procedure is i...

State recognition of the viscoelastic sandwich structure based on the adaptive redundant second generation wavelet packet transform, permutation entropy and the wavelet support vector machine

International Nuclear Information System (INIS)

Qu, Jinxiu; Zhang, Zhousuo; Guo, Ting; Luo, Xue; Sun, Chuang; Li, Bing; Wen, Jinpeng

2014-01-01

The viscoelastic sandwich structure is widely used in mechanical equipment, yet the structure always suffers from damage during long-term service. Therefore, state recognition of the viscoelastic sandwich structure is very necessary for monitoring structural health states and keeping the equipment running with high reliability. Through the analysis of vibration response signals, this paper presents a novel method for this task based on the adaptive redundant second generation wavelet packet transform (ARSGWPT), permutation entropy (PE) and the wavelet support vector machine (WSVM). In order to tackle the non-linearity existing in the structure vibration response, the PE is introduced to reveal the state changes of the structure. In the case of complex non-stationary vibration response signals, in order to obtain more effective information regarding the structural health states, the ARSGWPT, which can adaptively match the characteristics of a given signal, is proposed to process the vibration response signals, and then multiple PE features are extracted from the resultant wavelet packet coefficients. The WSVM, which can benefit from the conventional SVM as well as wavelet theory, is applied to classify the various structural states automatically. In this study, to achieve accurate and automated state recognition, the ARSGWPT, PE and WSVM are combined for signal processing, feature extraction and state classification, respectively. To demonstrate the effectiveness of the proposed method, a typical viscoelastic sandwich structure is designed, and the different degrees of preload on the structure are used to characterize the various looseness states. The test results show that the proposed method can reliably recognize the different looseness states of the viscoelastic sandwich structure, and the WSVM can achieve a better classification performance than the conventional SVM. Moreover, the superiority of the proposed ARSGWPT in processing the complex vibration response

MicroRNA-mediated down-regulation of NKG2D ligands contributes to glioma immune escape.

Science.gov (United States)

Codo, Paula; Weller, Michael; Meister, Gunter; Szabo, Emese; Steinle, Alexander; Wolter, Marietta; Reifenberger, Guido; Roth, Patrick

2014-09-15

Malignant gliomas are intrinsic brain tumors with a dismal prognosis. They are well-adapted to hypoxic conditions and poorly immunogenic. NKG2D is one of the major activating receptors of natural killer (NK) cells and binds to several ligands (NKG2DL). Here we evaluated the impact of miRNA on the expression of NKG2DL in glioma cells including stem-like glioma cells. Three of the candidate miRNA predicted to target NKG2DL were expressed in various glioma cell lines as well as in glioblastomas in vivo: miR-20a, miR-93 and miR-106b. LNA inhibitor-mediated miRNA silencing up-regulated cell surface NKG2DL expression, which translated into increased susceptibility to NK cell-mediated lysis. This effect was reversed by neutralizing NKG2D antibodies, confirming that enhanced lysis upon miRNA silencing was mediated through the NKG2D system. Hypoxia, a hallmark of glioblastomas in vivo, down-regulated the expression of NKG2DL on glioma cells, associated with reduced susceptibility to NK cell-mediated lysis. This process, however, was not mediated through any of the examined miRNA. Accordingly, both hypoxia and the expression of miRNA targeting NKG2DL may contribute to the immune evasion of glioma cells at the level of the NKG2D recognition pathway. Targeting miRNA may therefore represent a novel approach to increase the immunogenicity of glioblastoma.

A Ferrocene-Based Catecholamide Ligand: the Consequences of Ligand Swivel for Directed Supramolecular Self-Assembly

Energy Technology Data Exchange (ETDEWEB)

Mugridge, Jeffrey; Fiedler, Dorothea; Raymond, Kenneth

2010-02-04

A ferrocene-based biscatecholamide ligand was prepared and investigated for the formation of metal-ligand supramolecular assemblies with different metals. Reaction with Ge(IV) resulted in the formation of a variety of Ge{sub n}L{sub m} coordination complexes, including [Ge{sub 2}L{sub 3}]{sup 4-} and [Ge{sub 2}L{sub 2}({mu}-OMe){sub 2}]{sup 2-}. The ligand's ability to swivel about the ferrocenyl linker and adopt different conformations accounts for formation of many different Ge{sub n}L{sub m} species. This study demonstrates why conformational ligand rigidity is essential in the rational design and directed self-assembly of supramolecular complexes.

Biotechnological Fluorescent Ligands of the Bradykinin B1 Receptor: Protein Ligands for a Peptide Receptor.

Directory of Open Access Journals (Sweden)

Xavier Charest-Morin

Full Text Available The bradykinin (BK B1 receptor (B1R is a peculiar G protein coupled receptor that is strongly regulated to the point of being inducible in immunopathology. Limited clinical evidence suggests that its expression in peripheral blood mononuclear cells is a biomarker of active inflammatory states. In an effort to develop a novel imaging/diagnostic tool, we report the rational design and testing of a fusion protein that is a ligand of the human B1R but not likely to label peptidases. This ligand is composed of a fluorescent protein (FP (enhanced green FP [EGFP] or mCherry prolonged at its N-terminus by a spacer peptide and a classical peptide agonist or antagonist (des-Arg9-BK, [Leu8]des-Arg9-BK, respectively. The design of the spacer-ligand joint peptide was validated by a competition assay for [3H]Lys-des-Arg9-BK binding to the human B1R applied to 4 synthetic peptides of 18 or 19 residues. The labeling of B1R-expressing cells with EGFP or mCherry fused with 7 of such peptides was performed in parallel (microscopy. Both assays indicated that the best design was FP-(Asn-Glyn-Lys-des-Arg9-BK; n = 15 was superior to n = 5, suggesting benefits from minimizing steric hindrance between the FP and the receptor. Cell labeling concerned mostly plasma membranes and was inhibited by a B1R antagonist. EGFP-(Asn-Gly15-Lys-des-Arg9-BK competed for the binding of [3H]Lys-des-Arg9-BK to human recombinant B1R, being only 10-fold less potent than the unlabeled form of Lys-des-Arg9-BK to do so. The fusion protein did not label HEK 293a cells expressing recombinant human BK B2 receptors or angiotensin converting enzyme. This study identifies a modular C-terminal sequence that can be adapted to protein cargoes, conferring high affinity for the BK B1R, with possible applications in diagnostic cytofluorometry, histology and drug delivery (e.g., in oncology.

Macrocyclic G-quadruplex ligands

DEFF Research Database (Denmark)

Nielsen, M C; Ulven, Trond

2010-01-01

are macrocyclic structures which have been modeled after the natural product telomestatin or from porphyrin-based ligands discovered in the late 1990s. These two structural classes of G-quadruplex ligands are reviewed here with special attention to selectivity and structure-activity relationships, and with focus...

Synthesis and Guest Recognition of Switchable Pt-Salphen Based Molecular Tweezers

Directory of Open Access Journals (Sweden)

Lorien Benda

2018-04-01

Full Text Available Molecular tweezers are artificial receptors that have an open cavity generated by two recognition units pre-organized by a spacer. Switchable molecular tweezers, using a stimuli-responsive spacer, are particularly appealing as prototypes of the molecular machines that combine mechanical motion and allosteric recognition properties. In this present study, the synthesis of switchable molecular tweezers composed of a central terpyridine unit substituted in 4,4″ positions by two Pt(II-salphen complexes is reported. The terpyridine ligand can be reversibly converted upon Zn(II coordination from a free ‘U’-shaped closed form to a coordinated ‘W’ open form. This new substitution pattern enables a reverse control of the mechanical motion compared to the previously reported 6,6″ substituted terpyridine-based tweezers. Guest binding studies with aromatic guests showed an intercalation of coronene in the cavity created by the Pt-salphen moieties in the closed conformation. The formation of 1:1 host-guest complex was investigated by a combination of NMR studies and DFT calculations.

Conformational diversity of flexible ligand in metal-organic frameworks controlled by size-matching mixed ligands

International Nuclear Information System (INIS)

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi; Yu, Lei; Xie, Yi-Xin; Han, Lei

2015-01-01

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H_2ndc) or 4,4′-(hydroxymethylene)dibenzoic acid (H_2hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd_2(2,6-ndc)_2(bpp)(DMF)]·2DMF (1) and [Cd_3(hmdb)_3(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations in 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process. - Graphical abstract: Compound 1 exhibits a 3D self-penetrating 6-connected framework based on dinuclear cluster, and 2 displays an infinite 3D ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster. The flexible 1,3-bis(4-pyridyl)propane ligand displays different conformations in 1 and 2, which successfully controlled by size-matching mixed ligands during the self-assembly process.

Conformational diversity of flexible ligand in metal-organic frameworks controlled by size-matching mixed ligands

Energy Technology Data Exchange (ETDEWEB)

Hua, Xiu-Ni; Qin, Lan; Yan, Xiao-Zhi; Yu, Lei; Xie, Yi-Xin; Han, Lei, E-mail: hanlei@nbu.edu.cn

2015-12-15

Hydrothermal reactions of N-auxiliary flexible exo-bidentate ligand 1,3-bis(4-pyridyl)propane (bpp) and carboxylates ligands naphthalene-2,6-dicarboxylic acid (2,6-H{sub 2}ndc) or 4,4′-(hydroxymethylene)dibenzoic acid (H{sub 2}hmdb), in the presence of cadmium(II) salts have given rise to two novel metal-organic frameworks based on flexible ligands (FL-MOFs), namely, [Cd{sub 2}(2,6-ndc){sub 2}(bpp)(DMF)]·2DMF (1) and [Cd{sub 3}(hmdb){sub 3}(bpp)]·2DMF·2EtOH (2) (DMF=N,N-Dimethylformamide). Single-crystal X-ray diffraction analyses revealed that compound 1 exhibits a three-dimensional self-penetrating 6-connected framework based on dinuclear cluster second building unit. Compound 2 displays an infinite three-dimensional ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster and V-shaped organic linkers. The flexible bpp ligand displays different conformations in 1 and 2, which are successfully controlled by size-matching mixed ligands during the self-assembly process. - Graphical abstract: Compound 1 exhibits a 3D self-penetrating 6-connected framework based on dinuclear cluster, and 2 displays an infinite 3D ‘Lucky Clover’ shape (2,10)-connected network based on the trinuclear cluster. The flexible 1,3-bis(4-pyridyl)propane ligand displays different conformations in 1 and 2, which successfully controlled by size-matching mixed ligands during the self-assembly process.

Information adaptation the interplay between Shannon information and semantic information in cognition

CERN Document Server

Haken, Hermann

2015-01-01

This monograph demonstrates the interplay between Shannon information and semantic information in cognition. It shows that Shannon’s information acts as driving force for the formation of semantic information; and vice versa, namely, that semantic information participates in the formation of Shannonian information. The authors show that in cognition, Shannonian and semantic information are interrelated as two aspects of a cognitive process termed as information adaptation. In the latter the mind/brain adapts to the environment by the deflating and/or inflating of the information conveyed by the environment. In the process of information adaptation, quantitative variations in Shannon’s information entail different meanings while different meanings affect the quantity of information. The book illustrates the above conceptually and mathematically by reference to three cognitive processes: pattern recognition, face learning and the recognition of a moving object.

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

A General Ligand Design for Gold Catalysis allowing Ligand-Directed Anti Nucleophilic Attack of Alkynes

Science.gov (United States)

Wang, Yanzhao; Wang, Zhixun; Li, Yuxue; Wu, Gongde; Cao, Zheng; Zhang, Liming

2014-01-01

Most homogenous gold catalyses demand ≥0.5 mol % catalyst loading. Due to the high cost of gold, these reactions are unlikely to be applicable in medium or large scale applications. Here we disclose a novel ligand design based on the privileged biphenyl-2-phosphine framework that offers a potentially general approach to dramatically lowering catalyst loading. In this design, an amide group at the 3’ position of the ligand framework directs and promotes nucleophilic attack at the ligand gold complex-activated alkyne, which is unprecedented in homogeneous gold catalysis considering the spatial challenge of using ligand to reach antiapproaching nucleophile in a linear P-Au-alkyne centroid structure. With such a ligand, the gold(I) complex becomes highly efficient in catalyzing acid addition to alkynes, with a turnover number up to 99,000. Density functional theory calculations support the role of the amide moiety in directing the attack of carboxylic acid via hydrogen bonding. PMID:24704803

Adaptive Matrices and Filters for Color Texture Classification

NARCIS (Netherlands)

Giotis, Ioannis; Bunte, Kerstin; Petkov, Nicolai; Biehl, Michael

In this paper we introduce an integrative approach towards color texture classification and recognition using a supervised learning framework. Our approach is based on Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure, which is defined in the Fourier domain,

Secondary ligand-directed assembly of Co(II) coordination polymers based on a pyridine carboxylate ligand

International Nuclear Information System (INIS)

Cao, Ke-Li; Zhang, Yi-Ping; Cai, Yi-Ni; Xu, Xiao-Wei; Feng, Yun-Long

2014-01-01

To investigate the influence of hydrogen bonds and secondary ligands on the structures and properties of the resulting frameworks, five new Co(II) compounds have been synthesized by the reactions of Co(II) salts and 3,5-bis(pyridin-4-ylmethoxy)benzoic acid (HL) with four rationally selected dicarboxylic acid ligands. Without secondary ligand, we got one compound [CoL 2 (H 2 O) 2 ] n ·2nH 2 O (1), which possesses a 1D chain structure. In the presence of ancillary ligands, namely, 1,3-adamantanedicarboxylic acid (H 2 adbc), terephthalic acid (H 2 tpa), thiophene-2,5-dicarboxylic acid (H 2 tdc) and 1,4-benzenedithioacetic acid (H 2 bdtc), four 3D structures [Co 2 L 2 (adbc)] n ·nH 2 O (2), [Co 2 L 2 (tpa)] n (3), [Co 2 L 2 (tdc)] n (4), [Co 2 L 2 (bdtc)(H 2 O)] n (5) were obtained, respectively. It can be observed from the architectures of 1–5 that hydrogen bonds and secondary ligands both have great effects on the spatial connective fashions, resulting in the formation of various dimensional compounds. The XRPD, TGA data of title polymers and the magnetic properties for 2 and 5 have also been investigated. - Graphical abstract: The structural differences show that the ancillary ligands have great effects on the spatial connective fashions, resulting in the formation of various dimensional compounds. - Highlights: • Five new Co(II) coordination polymers have been synthesized by solvothermal reactions based on 3,5-bis(pyridin-4-ylmethoxy)benzoic acid (HL). • The long-flexible ligand (HL) is a good candidate to produce interpenetrating architectures. • The secondary dicarboxylic acid ligands play important roles in the spatial connective fashions and the formation of various dimensional compounds. • The magnetism studies show that both 2 and 5 exhibit antiferromagnetic interactions

Novel bispidine ligands with a possible application in nuclear medicine; Neue Bispidin-Liganden mit potenzieller Anwendung in der Nuklearmedizin

Energy Technology Data Exchange (ETDEWEB)

Rudolf, Henning

2013-10-24

Due to our current way of life and the environmental influences we are exposed in the industrial nations, cancer diseases turn out to be a more and more serious threat to our civilization. The ongoing research during the last decades leads to a better insight in cancer diseases and enables an earlier recognition of developing carcinoma. The detection of pathological tissue changes at an early stage increases the patients' chances of cure. Magnetic resonance tomography (MRT) and computed tomography (CT) as well as radiopharmaceutically assisted imaging techniques, like positron emission tomography (PET) and scintigraphy are an indispensable clinical tool in the oncological early diagnosis. By the development of multimodality imaging agents that combine the benefits of several imaging techniques, the early recognition of tumors can be more efficient and in consequence a matching therapy can be applied. This thesis deals with the synthesis of novel bispidine based ligands and their transition metal complexes as potential mono- and bimodal imaging agents for a {sup 64}Cu-assisted radiopharmaceutical application in positron emission tomography (PET) and optical imaging (OI). The synthesized ligands L and L{sup OH} are offering the opportunity to build up a ruthenium(II) polypyridine complex by one of the ligand's donor sets, to act as a fluorescence dye for optical imaging (OI), and to coordinate {sup 64}Cu{sup II} by the ligand's vacant cavity for positron emission tomography (PET). The Ru{sup II} complex exhibits two different fluorescence activities with two different lifetimes and only one of the two fluorescences is quenched by subsequent complexation of Cu{sup II}. The calculated Cu{sup II} stability constant of L and L{sup OH} is similar to that of the isomeric ligand N{sub 2}py{sub 2} which has been already evaluated as a {sup 64}Cu-radiotracer. Further transition metal complexes of Fe{sup II}, Fe{sup III} and Mn{sup II} are dealing with

Blind Recognition of Binary BCH Codes for Cognitive Radios

Directory of Open Access Journals (Sweden)

Jing Zhou

2016-01-01

Full Text Available A novel algorithm of blind recognition of Bose-Chaudhuri-Hocquenghem (BCH codes is proposed to solve the problem of Adaptive Coding and Modulation (ACM in cognitive radio systems. The recognition algorithm is based on soft decision situations. The code length is firstly estimated by comparing the Log-Likelihood Ratios (LLRs of the syndromes, which are obtained according to the minimum binary parity check matrixes of different primitive polynomials. After that, by comparing the LLRs of different minimum polynomials, the code roots and generator polynomial are reconstructed. When comparing with some previous approaches, our algorithm yields better performance even on very low Signal-Noise-Ratios (SNRs with lower calculation complexity. Simulation results show the efficiency of the proposed algorithm.

CMPO-functionalized C{sub 3}-symmetric tripodal ligands in liquid/liquid extractions : efficient, selective recognition of Pu(IV) with low affinity for 3+ metal ions.

Energy Technology Data Exchange (ETDEWEB)

Matloka, K.; Sah, A. K.; Peters, M. W.; Srinivasan, P.; Gelis, A. V.; Regalbuto, M.; Scott, M. J.; Univ. of Florida

2007-12-10

Structural modifications of carbamoylmethylphosphine oxide (CPMO)-functionalized triphenoxymethane platforms are described, and the influence of these changes on the ability of the ligand to extract actinides from simulated acidic nuclear waste streams has been evaluated. The ligand system has been shown to have excellent binding efficiency and a selectivity for An(IV) in comparison to the a simple monomeric CMPO ligand under analogous conditions. Both the extraction efficiency and selectivity are strongly dependent on the flexibility and electronic properties of the ligating units in the triphenoxymethane construct. The Tb(III) and Bi(III) nitrate complexes of tris-CMPO derivatives have been isolated, and their structures were elucidated by NMR, ESI FT-ICR MS, and X-ray analysis, providing information on the interactions between metal ions and the tris-CMPO molecules.

Using self-organizing maps adaptive resonance theory (CARTMAP) for manufacturing feature recognition

Science.gov (United States)

Yu, Jason S.; Dagli, Cihan H.

1993-10-01

The invariant image preprocessing of moment invariants generates an invariant representation of object features which are insensitive to position, orientation, size, illusion, and contrast change. In this study ARTMAP is used for 3-D object recognition of manufacturing parts through these invariant characteristics. The analog of moment invariants created through the image preprocessing is interpreted by a binary code which is used to predict the manufacturing part through ARTMAP.

Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.

Science.gov (United States)

Arcos-García, Álvaro; Álvarez-García, Juan A; Soria-Morillo, Luis M

2018-03-01

This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structural pattern recognition methods based on string comparison for fusion databases

International Nuclear Information System (INIS)

Dormido-Canto, S.; Farias, G.; Dormido, R.; Vega, J.; Sanchez, J.; Duro, N.; Vargas, H.; Ratta, G.; Pereira, A.; Portas, A.

2008-01-01

Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed

Structural pattern recognition methods based on string comparison for fusion databases

Energy Technology Data Exchange (ETDEWEB)

Dormido-Canto, S. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain)], E-mail: sebas@dia.uned.es; Farias, G.; Dormido, R. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain); Sanchez, J.; Duro, N.; Vargas, H. [Dpto. Informatica y Automatica - UNED 28040, Madrid (Spain); Ratta, G.; Pereira, A.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, 28040, Madrid (Spain)

2008-04-15

Databases for fusion experiments are designed to store several million waveforms. Temporal evolution signals show the same patterns under the same plasma conditions and, therefore, pattern recognition techniques allow the identification of similar plasma behaviours. This article is focused on the comparison of structural pattern recognition methods. A pattern can be composed of simpler sub-patterns, where the most elementary sub-patterns are known as primitives. Selection of primitives is an essential issue in structural pattern recognition methods, because they determine what types of structural components can be constructed. However, it should be noted that there is not a general solution to extract structural features (primitives) from data. So, four different ways to compute the primitives of plasma waveforms are compared: (1) constant length primitives, (2) adaptive length primitives, (3) concavity method and (4) concavity method for noisy signals. Each method defines a code alphabet and, in this way, the pattern recognition problem is carried out via string comparisons. Results of the four methods with the TJ-II stellarator databases will be discussed.

Specific ability of sulfur-ligands on removal of 203Hg-labeled organomercury from hemoglobin in comparison with nitrogen-ligands

International Nuclear Information System (INIS)

Hojo, Yasuji; Sugiura, Yukio; Tanaka, Hisashi

1975-01-01

Removal of 203 Hg-labeled organomercurials, bound to sulfhydryl groups of hemoglobin, by various chelating agents was investigated by the use of equilibrium dialysis. Organomercurials employed were chlormerodrin, methylmercury, ethylmercury and phenylmercury compounds. Higher and more specific effects of the sulfur-ligands, such as penicillamine and glutathione, on removal of organomercurial were found as compared with those of the nitrogen-ligands such as EDTA, glycine and polymethylenediamines. Linear correlation was observed between the degree of organomercury elimination from hemoglobin and the stability constant (log K 1 ) of 1:1 organomercury complex in both the sulfur- and nitrogen-ligand systems and at the same value of log K 1 , the elimination-effect of sulfur-ligands was extremely greater than that of the nitrogen-ligands. The relationship between the average percentage of removal and the Taft's polar substituent constant of organic moiety of the metal was also linear among the organomercury compounds other than chlormerodrin. The average removal percentage by sulfur-ligands increased in the order, ethylmercury>methylmercury>phenylmercury, while that of the nitrogen-ligands was not different among the organomercurials investigated. In addition, direct ligand-exchange reaction between hemoglobin-SH and the ligand coordinating-atom (S or N) against organomercurials rather than Ssub(N2) reaction via the ternary complex, hemoglobin-S-RHg-ligand, is postulated. (auth.)

Speech recognition: impact on workflow and report availability

International Nuclear Information System (INIS)

Glaser, C.; Trumm, C.; Nissen-Meyer, S.; Francke, M.; Kuettner, B.; Reiser, M.

2005-01-01

With ongoing technical refinements speech recognition systems (SRS) are becoming an increasingly attractive alternative to traditional methods of preparing and transcribing medical reports. The two main components of any SRS are the acoustic model and the language model. Features of modern SRS with continuous speech recognition are macros with individually definable texts and report templates as well as the option to navigate in a text or to control SRS or RIS functions by speech recognition. The best benefit from SRS can be obtained if it is integrated into a RIS/RIS-PACS installation. Report availability and time efficiency of the reporting process (related to recognition rate, time expenditure for editing and correcting a report) are the principal determinants of the clinical performance of any SRS. For practical purposes the recognition rate is estimated by the error rate (unit ''word''). Error rates range from 4 to 28%. Roughly 20% of them are errors in the vocabulary which may result in clinically relevant misinterpretation. It is thus mandatory to thoroughly correct any transcribed text as well as to continuously train and adapt the SRS vocabulary. The implementation of SRS dramatically improves report availability. This is most pronounced for CT and CR. However, the individual time expenditure for (SRS-based) reporting increased by 20-25% (CR) and according to literature data there is an increase by 30% for CT and MRI. The extent to which the transcription staff profits from SRS depends largely on its qualification. Online dictation implies a workload shift from the transcription staff to the reporting radiologist. (orig.) [de

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones

Science.gov (United States)

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-01-01

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters. PMID:26690439

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones.

Science.gov (United States)

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-12-10

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones

Directory of Open Access Journals (Sweden)

Jing Chen

2015-12-01

Full Text Available Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

A role for carbohydrate recognition in mammalian sperm-egg binding

International Nuclear Information System (INIS)

Clark, Gary F.

2014-01-01

Highlights: • Mammalian sperm-egg binding as a carbohydrate dependent species recognition event. • The role of carbohydrate recognition in human, mouse and pig sperm-egg binding. • Historical perspective and future directions for research focused on gamete binding. - Abstract: Mammalian fertilization usually requires three sequential cell–cell interactions: (i) initial binding of sperm to the specialized extracellular matrix coating the egg known as the zona pellucida (ZP); (ii) binding of sperm to the ZP via the inner acrosomal membrane that is exposed following the induction of acrosomal exocytosis; and (iii) adhesion of acrosome-reacted sperm to the plasma membrane of the egg cell, enabling subsequent fusion of these gametes. The focus of this review is on the initial binding of intact sperm to the mammalian ZP. Evidence collected over the past fifty years has confirmed that this interaction relies primarily on the recognition of carbohydrate sequences presented on the ZP by lectin-like egg binding proteins located on the plasma membrane of sperm. There is also evidence that the same carbohydrate sequences that mediate binding also function as ligands for lectins on lymphocytes that can inactivate immune responses, likely protecting the egg and the developing embryo up to the stage of blastocyst hatching. The literature related to initial sperm-ZP binding in the three major mammalian models (human, mouse and pig) is discussed. Historical perspectives and future directions for research related to this aspect of gamete adhesion are also presented

A role for carbohydrate recognition in mammalian sperm-egg binding

Energy Technology Data Exchange (ETDEWEB)

Clark, Gary F., E-mail: clarkgf@health.missouri.edu

2014-08-01

Highlights: • Mammalian sperm-egg binding as a carbohydrate dependent species recognition event. • The role of carbohydrate recognition in human, mouse and pig sperm-egg binding. • Historical perspective and future directions for research focused on gamete binding. - Abstract: Mammalian fertilization usually requires three sequential cell–cell interactions: (i) initial binding of sperm to the specialized extracellular matrix coating the egg known as the zona pellucida (ZP); (ii) binding of sperm to the ZP via the inner acrosomal membrane that is exposed following the induction of acrosomal exocytosis; and (iii) adhesion of acrosome-reacted sperm to the plasma membrane of the egg cell, enabling subsequent fusion of these gametes. The focus of this review is on the initial binding of intact sperm to the mammalian ZP. Evidence collected over the past fifty years has confirmed that this interaction relies primarily on the recognition of carbohydrate sequences presented on the ZP by lectin-like egg binding proteins located on the plasma membrane of sperm. There is also evidence that the same carbohydrate sequences that mediate binding also function as ligands for lectins on lymphocytes that can inactivate immune responses, likely protecting the egg and the developing embryo up to the stage of blastocyst hatching. The literature related to initial sperm-ZP binding in the three major mammalian models (human, mouse and pig) is discussed. Historical perspectives and future directions for research related to this aspect of gamete adhesion are also presented.

Ligand cluster-based protein network and ePlatton, a multi-target ligand finder.

Science.gov (United States)

Du, Yu; Shi, Tieliu

2016-01-01

Small molecules are information carriers that make cells aware of external changes and couple internal metabolic and signalling pathway systems with each other. In some specific physiological status, natural or artificial molecules are used to interact with selective biological targets to activate or inhibit their functions to achieve expected biological and physiological output. Millions of years of evolution have optimized biological processes and pathways and now the endocrine and immune system cannot work properly without some key small molecules. In the past thousands of years, the human race has managed to find many medicines against diseases by trail-and-error experience. In the recent decades, with the deepening understanding of life and the progress of molecular biology, researchers spare no effort to design molecules targeting one or two key enzymes and receptors related to corresponding diseases. But recent studies in pharmacogenomics have shown that polypharmacology may be necessary for the effects of drugs, which challenge the paradigm, 'one drug, one target, one disease'. Nowadays, cheminformatics and structural biology can help us reasonably take advantage of the polypharmacology to design next-generation promiscuous drugs and drug combination therapies. 234,591 protein-ligand interactions were extracted from ChEMBL. By the 2D structure similarity, 13,769 ligand emerged from 156,151 distinct ligands which were recognized by 1477 proteins. Ligand cluster- and sequence-based protein networks (LCBN, SBN) were constructed, compared and analysed. For assisting compound designing, exploring polypharmacology and finding possible drug combination, we integrated the pathway, disease, drug adverse reaction and the relationship of targets and ligand clusters into the web platform, ePlatton, which is available at http://www.megabionet.org/eplatton. Although there were some disagreements between the LCBN and SBN, communities in both networks were largely the same

Unaware person recognition from the body when face identification fails.

Science.gov (United States)

Rice, Allyson; Phillips, P Jonathon; Natu, Vaidehi; An, Xiaobo; O'Toole, Alice J

2013-11-01

How does one recognize a person when face identification fails? Here, we show that people rely on the body but are unaware of doing so. State-of-the-art face-recognition algorithms were used to select images of people with almost no useful identity information in the face. Recognition of the face alone in these cases was near chance level, but recognition of the person was accurate. Accuracy in identifying the person without the face was identical to that in identifying the whole person. Paradoxically, people reported relying heavily on facial features over noninternal face and body features in making their identity decisions. Eye movements indicated otherwise, with gaze duration and fixations shifting adaptively toward the body and away from the face when the body was a better indicator of identity than the face. This shift occurred with no cost to accuracy or response time. Human identity processing may be partially inaccessible to conscious awareness.

Immobilisation of ligands by radio-derivatized polymers; Immobilisering av ligander med radioderiverte polymerer

Energy Technology Data Exchange (ETDEWEB)

Varga, J.M.; Fritsch, P.

1995-01-30

The invention relates to radio-derivatized polymers and a method of producing them by contacting non-polymerizable conjugands with radiolysable polymers in the presence of irradiation. The resulting radio-derivatized polymers can be further linked with ligand of organic or inorganic nature to immobilize such ligands. 2 figs., 5 tabs.

Adapted Physical Education and Therapeutic Recreation in Schools

Science.gov (United States)

Etzel-Wise, D; Mears, B

2004-01-01

Adapted physical education is a mandated service, whereas therapeutic recreation and traditional recreation are considered related services under the Individuals with Disabilities Education Act. In this article, the authors describe the distinctions between the services, recognition of need for referral, methods of assessment, sample…

Sensor agnostic object recognition using a map seeking circuit

Science.gov (United States)

Overman, Timothy L.; Hart, Michael

2012-05-01

Automatic object recognition capabilities are traditionally tuned to exploit the specific sensing modality they were designed to. Their successes (and shortcomings) are tied to object segmentation from the background, they typically require highly skilled personnel to train them, and they become cumbersome with the introduction of new objects. In this paper we describe a sensor independent algorithm based on the biologically inspired technology of map seeking circuits (MSC) which overcomes many of these obstacles. In particular, the MSC concept offers transparency in object recognition from a common interface to all sensor types, analogous to a USB device. It also provides a common core framework that is independent of the sensor and expandable to support high dimensionality decision spaces. Ease in training is assured by using commercially available 3D models from the video game community. The search time remains linear no matter how many objects are introduced, ensuring rapid object recognition. Here, we report results of an MSC algorithm applied to object recognition and pose estimation from high range resolution radar (1D), electrooptical imagery (2D), and LIDAR point clouds (3D) separately. By abstracting the sensor phenomenology from the underlying a prior knowledge base, MSC shows promise as an easily adaptable tool for incorporating additional sensor inputs.

Ignoring Memory Hints: The Stubborn Influence of Environmental Cues on Recognition Memory

Science.gov (United States)

Selmeczy, Diana; Dobbins, Ian G.

2017-01-01

Recognition judgments can benefit from the use of environmental cues that signal the general likelihood of encountering familiar versus unfamiliar stimuli. While incorporating such cues is often adaptive, there are circumstances (e.g., eyewitness testimony) in which observers should fully ignore environmental cues in order to preserve memory…

A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

Science.gov (United States)

Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748

Recognition of lyso-phospholipids by human natural killer T lymphocytes.

Directory of Open Access Journals (Sweden)

Lisa M Fox

2009-10-01

Full Text Available Natural killer T (NKT cells are a subset of T lymphocytes with potent immunoregulatory properties. Recognition of self-antigens presented by CD1d molecules is an important route of NKT cell activation; however, the molecular identity of specific autoantigens that stimulate human NKT cells remains unclear. Here, we have analyzed human NKT cell recognition of CD1d cellular ligands. The most clearly antigenic species was lyso-phosphatidylcholine (LPC. Diacylated phosphatidylcholine and lyso-phosphoglycerols differing in the chemistry of the head group stimulated only weak responses from human NKT cells. However, lyso-sphingomyelin, which shares the phosphocholine head group of LPC, also activated NKT cells. Antigen-presenting cells pulsed with LPC were capable of stimulating increased cytokine responses by NKT cell clones and by freshly isolated peripheral blood lymphocytes. These results demonstrate that human NKT cells recognize cholinated lyso-phospholipids as antigens presented by CD1d. Since these lyso-phospholipids serve as lipid messengers in normal physiological processes and are present at elevated levels during inflammatory responses, these findings point to a novel link between NKT cells and cellular signaling pathways that are associated with human disease pathophysiology.

Leadership as an Emergent Phenomenon: A Framework for Complexity and Adaptability

National Research Council Canada - National Science Library

Martinez, Sandra M

2008-01-01

The recognition by some military leaders about the need for a different paradigm of leadership that responds to requirements for adaptability in complex environments has not necessarily translated into action...

The Development of Adaptive Decision Making: Recognition-Based Inference in Children and Adolescents

Science.gov (United States)

Horn, Sebastian S.; Ruggeri, Azzurra; Pachur, Thorsten

2016-01-01

Judgments about objects in the world are often based on probabilistic information (or cues). A frugal judgment strategy that utilizes memory (i.e., the ability to discriminate between known and unknown objects) as a cue for inference is the recognition heuristic (RH). The usefulness of the RH depends on the structure of the environment,…

Reactivity of halide and pseudohalide ligands

International Nuclear Information System (INIS)

Kukushkin, Yu.N.

1987-01-01

Reactivity of halide and pseudohalide (cyanide, azide, thiocyanate, cyanate) ligands tending to form bridge bonds in transition metal (Re, Mo, W) complexes is considered. Complexes where transition metal salts are ligands of other, complex-forming ion, are described. Transformation of innerspheric pseudohalide ligands is an important way of directed synthesis of these metal coordination compounds

Metal-ligand cooperative activation of nitriles by a ruthenium complex with a de-aromatized PNN pincer ligand

NARCIS (Netherlands)

Eijsink, Linda E; Perdriau, Sébastien C P; de Vries, Johannes G; Otten, Edwin

2016-01-01

The pincer complex (PNN)RuH(CO), with a de-aromatized pyridine in the ligand backbone, is shown to react with nitriles in a metal-ligand cooperative manner. This leads to the formation of a series of complexes with new Ru-N(nitrile) and C(ligand)-C(nitrile) bonds. The initial nitrile cycloaddition

Spoken language identification system adaptation in under-resourced environments

CSIR Research Space (South Africa)

Kleynhans, N

2013-12-01

Full Text Available Speech Recognition (ASR) systems in the developing world is severely inhibited. Given that few task-specific corpora exist and speech technology systems perform poorly when deployed in a new environment, we investigate the use of acoustic model adaptation...

Character Recognition Using Genetically Trained Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

1998-10-01

Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

Action recognition using mined hierarchical compound features.

Science.gov (United States)

Gilbert, Andrew; Illingworth, John; Bowden, Richard

2011-05-01

The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial domain, their 3D (space-time) counterparts typically form the basic components used to describe actions, and in action recognition the features used are often engineered to fire sparsely. This is to ensure that the problem is tractable; however, this can sacrifice recognition accuracy as it cannot be assumed that the optimum features in terms of class discrimination are obtained from this approach. In contrast, we propose to initially use an overcomplete set of simple 2D corners in both space and time. These are grouped spatially and temporally using a hierarchical process, with an increasing search area. At each stage of the hierarchy, the most distinctive and descriptive features are learned efficiently through data mining. This allows large amounts of data to be searched for frequently reoccurring patterns of features. At each level of the hierarchy, the mined compound features become more complex, discriminative, and sparse. This results in fast, accurate recognition with real-time performance on high-resolution video. As the compound features are constructed and selected based upon their ability to discriminate, their speed and accuracy increase at each level of the hierarchy. The approach is tested on four state-of-the-art data sets, the popular KTH data set to provide a comparison with other state-of-the-art approaches, the Multi-KTH data set to illustrate performance at simultaneous multiaction classification, despite no explicit localization information provided during training. Finally, the recent Hollywood and Hollywood2 data sets provide challenging complex actions taken from commercial movie sequences. For all four data sets, the proposed hierarchical

Towards ligand docking including explicit interface water molecules.

Directory of Open Access Journals (Sweden)

Gordon Lemmon

Full Text Available Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta's ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9:1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes [1]. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.

СHIRAL RECOGNITION OF CYSTEINE MOLECULES BY CHIRAL CdSe AND CdS QUANTUM DOTS

Directory of Open Access Journals (Sweden)

M. V. Mukhina

2015-11-01

Full Text Available Here, we report the investigation of mechanism of chiral molecular recognition of cysteine biomolecules by chiral CdSe and CdS semiconductor nanocrystals. To observe chiral recognition process, we prepared enantioenriched ensembles of the nanocrystals capped with achiral ligand. The enantioenriched samples of intrinsically chiral CdSe quantum dots were prepared by separation of initial racemic mixture of the nanocrystals using chiral phase transfer from chloroform to water driven by L- and D-cysteine. Chiral molecules of cysteine and penicillamine were substituted for achiral molecules of dodecanethiol on the surfaces of CdSe and CdS samples, respectively, via reverse phase transfer from water to chloroform. We estimated an efficiency of the hetero- (d-L or l-D and homocomplexes (l-L formation by comparing the extents of corresponding complexing reactions. Using circular dichroism spectroscopy data we show an ability of nanocrystals enantiomers to discriminate between left-handed and right-handed enantiomers of biomolecules via preferential formation of heterocomplexes. Development of approaches for obtaining chiral nanocrystals via chiral phase transfer offers opportunities for investigation of molecular recognition at the nano/bio interfaces.

Adapting Speech Recognition in Augmented Reality for Mobile Devices in Outdoor Environments

OpenAIRE

Pascoal, Rui; Ribeiro, Ricardo; Batista, Fernando; de Almeida, Ana

2017-01-01

This paper describes the process of integrating automatic speech recognition (ASR) into a mobile application and explores the benefits and challenges of integrating speech with augmented reality (AR) in outdoor environments. The augmented reality allows end-users to interact with the information displayed and perform tasks, while increasing the user’s perception about the real world by adding virtual information to it. Speech is the most natural way of communication: it allows hands-free inte...

CD8 T Cell Sensory Adaptation Dependent on TCR Avidity for Self-Antigens

DEFF Research Database (Denmark)

Marquez, M.-E.; Ellmeier, W.; Sanchez-Guajardo, Vanesa Maria

2005-01-01

dephosphorylation of linker for activation of T cells and ERK upon activation. Normal TCR levels and cytokine production were restored by culturing cells in the absence of TCR/spMHC interaction, demonstrating dynamic tuning of peripheral T cell responses. The effect of avidity for self-ligand(s) on this sensory...... ZAP-YEEI cells were enhanced. Our data provide support for central and peripheral sensory T cell adaptation induced as a function of TCR avidity for self-ligands and signaling level. This may contribute to buffer excessive autoreactivity while optimizing TCR repertoire usage....

Structural basis of RNA folding and recognition in an AMP-RNA aptamer complex.

Science.gov (United States)

Jiang, F; Kumar, R A; Jones, R A; Patel, D J

1996-07-11

The catalytic properties of RNA and its well known role in gene expression and regulation are the consequence of its unique solution structures. Identification of the structural determinants of ligand recognition by RNA molecules is of fundamental importance for understanding the biological functions of RNA, as well as for the rational design of RNA Sequences with specific catalytic activities. Towards this latter end, Szostak et al. used in vitro selection techniques to isolate RNA sequences ('aptamers') containing a high-affinity binding site for ATP, the universal currency of cellular energy, and then used this motif to engineer ribozymes with polynucleotide kinase activity. Here we present the solution structure, as determined by multidimensional NMR spectroscopy and molecular dynamics calculations, of both uniformly and specifically 13C-, 15N-labelled 40-mer RNA containing the ATP-binding motif complexed with AMP. The aptamer adopts an L-shaped structure with two nearly orthogonal stems, each capped proximally by a G x G mismatch pair, binding the AMP ligand at their junction in a GNRA-like motif.

Language Model Combination and Adaptation Using Weighted Finite State Transducers

Science.gov (United States)

Liu, X.; Gales, M. J. F.; Hieronymus, J. L.; Woodland, P. C.

2010-01-01

In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences

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

Science.gov (United States)

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.

Conformational change of adenosine deaminase during ligand-exchange in a crystal.

Science.gov (United States)

Kinoshita, Takayoshi; Tada, Toshiji; Nakanishi, Isao

2008-08-15

Adenosine deaminase (ADA) perpetuates chronic inflammation by degrading extracellular adenosine which is toxic for lymphocytes. ADA has two distinct conformations: open form and closed form. From the crystal structures with various ligands, the non-nucleoside type inhibitors bind to the active site occupying the critical water-binding-position and sustain the open form of apo-ADA. In contrast, substrate mimics do not occupy the critical position, and induce the large conformational change to the closed form. However, it is difficult to predict the binding of (+)-erythro-9-(2-hydroxy-3-nonyl)adenine (EHNA), as it possesses characteristic parts of both the substrate and the non-nucleoside inhibitors. The crystal structure shows that EHNA binds to the open form through a novel recognition of the adenine base accompanying conformational change from the closed form of the PR-ADA complex in crystalline state.

Crystallization of bi-functional ligand protein complexes.

Science.gov (United States)

Antoni, Claudia; Vera, Laura; Devel, Laurent; Catalani, Maria Pia; Czarny, Bertrand; Cassar-Lajeunesse, Evelyn; Nuti, Elisa; Rossello, Armando; Dive, Vincent; Stura, Enrico Adriano

2013-06-01

Homodimerization is important in signal transduction and can play a crucial role in many other biological systems. To obtaining structural information for the design of molecules able to control the signalization pathways, the proteins involved will have to be crystallized in complex with ligands that induce dimerization. Bi-functional drugs have been generated by linking two ligands together chemically and the relative crystallizability of complexes with mono-functional and bi-functional ligands has been evaluated. There are problems associated with crystallization with such ligands, but overall, the advantages appear to be greater than the drawbacks. The study involves two matrix metalloproteinases, MMP-12 and MMP-9. Using flexible and rigid linkers we show that it is possible to control the crystal packing and that by changing the ligand-enzyme stoichiometric ratio, one can toggle between having one bi-functional ligand binding to two enzymes and having the same ligand bound to each enzyme. The nature of linker and its point of attachment on the ligand can be varied to aid crystallization, and such variations can also provide valuable structural information about the interactions made by the linker with the protein. We report here the crystallization and structure determination of seven ligand-dimerized complexes. These results suggest that the use of bi-functional drugs can be extended beyond the realm of protein dimerization to include all drug design projects. Copyright © 2013 Elsevier Inc. All rights reserved.

Chirality as a tool in nucleic acid recognition: principles and relevance in biotechnology and in medicinal chemistry.

Science.gov (United States)

Corradini, Roberto; Sforza, Stefano; Tedeschi, Tullia; Marchelli, Rosangela

2007-05-05

The understanding of the interaction of chiral species with DNA or RNA is very important for the development of new tools in biology and of new drugs. Several cases in which chirality is a crucial point in determining the DNA binding mode are reviewed and discussed, with the aim of illustrating how chirality can be considered as a tool for improving the understanding of mechanisms and the effectiveness of nucleic acid recognition. The review is divided into two parts: the former describes examples of chiral species interacting with DNA: intercalators, metal complexes, and groove binders; the latter part is dedicated to chirality in DNA analogs, with discussion of phosphate stereochemistry and chirality of ribose substitutes, in particular of peptide nucleic acids (PNAs) for which a number of works have been published recently dealing with the effect of chirality in DNA recognition. The discussion is intended to show how enantiomeric recognition originates at the molecular level, by exploiting the enormous progresses recently achieved in the field of structural characterization of complexes formed by nucleic acid with their ligands by crystallographic and spectroscopic methods. Examples of application of the DNA binding molecules described and the role of chirality in DNA recognition relevant for biotechnology or medicinal chemistry are reported. (c) 2007 Wiley-Liss, Inc.

Autocrine signal transmission with extracellular ligand degradation

Science.gov (United States)

Muratov, C B; Posta, F; Shvartsman, S Y

2009-03-01

Traveling waves of cell signaling in epithelial layers orchestrate a number of important processes in developing and adult tissues. These waves can be mediated by positive feedback autocrine loops, a mode of cell signaling where binding of a diffusible extracellular ligand to a cell surface receptor can lead to further ligand release. We formulate and analyze a biophysical model that accounts for ligand-induced ligand release, extracellular ligand diffusion and ligand-receptor interaction. We focus on the case when the main mode for ligand degradation is extracellular and analyze the problem with the sharp threshold positive feedback nonlinearity. We derive expressions that link the speed of propagation and other characteristics of traveling waves to the parameters of the biophysical processes, such as diffusion rates, receptor expression level, etc. Analyzing the derived expressions we found that traveling waves in such systems can exhibit a number of unusual properties, e.g. non-monotonic dependence of the speed of propagation on ligand diffusivity. Our results for the fully developed traveling fronts can be used to analyze wave initiation from localized perturbations, a scenario that frequently arises in the in vitro models of epithelial wound healing, and guide future modeling studies of cell communication in epithelial layers.

Cell-specific targeting by heterobivalent ligands.

Science.gov (United States)

Josan, Jatinder S; Handl, Heather L; Sankaranarayanan, Rajesh; Xu, Liping; Lynch, Ronald M; Vagner, Josef; Mash, Eugene A; Hruby, Victor J; Gillies, Robert J

2011-07-20

Current cancer therapies exploit either differential metabolism or targeting to specific individual gene products that are overexpressed in aberrant cells. The work described herein proposes an alternative approach--to specifically target combinations of cell-surface receptors using heteromultivalent ligands ("receptor combination approach"). As a proof-of-concept that functionally unrelated receptors can be noncovalently cross-linked with high avidity and specificity, a series of heterobivalent ligands (htBVLs) were constructed from analogues of the melanocortin peptide ligand ([Nle(4), dPhe(7)]-α-MSH) and the cholecystokinin peptide ligand (CCK-8). Binding of these ligands to cells expressing the human Melanocortin-4 receptor and the Cholecystokinin-2 receptor was analyzed. The MSH(7) and CCK(6) were tethered with linkers of varying rigidity and length, constructed from natural and/or synthetic building blocks. Modeling data suggest that a linker length of 20-50 Å is needed to simultaneously bind these two different G-protein coupled receptors (GPCRs). These ligands exhibited up to 24-fold enhancement in binding affinity to cells that expressed both (bivalent binding), compared to cells with only one (monovalent binding) of the cognate receptors. The htBVLs had up to 50-fold higher affinity than that of a monomeric CCK ligand, i.e., Ac-CCK(6)-NH(2). Cell-surface targeting of these two cell types with labeled heteromultivalent ligand demonstrated high avidity and specificity, thereby validating the receptor combination approach. This ability to noncovalently cross-link heterologous receptors and target individual cells using a receptor combination approach opens up new possibilities for specific cell targeting in vivo for therapy or imaging.

Applying perceptual and adaptive learning techniques for teaching introductory histopathology

Directory of Open Access Journals (Sweden)

Sally Krasne

2013-01-01

Full Text Available Background: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem. Methods: We adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses that appear during a learning session based on each learner′s accuracy and response time (RT. We developed a perceptual and adaptive learning module (PALM that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a "Score" that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness. Results: Accuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1 st -year students, but not significantly so for 2 nd -year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1 st and 2 nd year students suggesting good retention of pattern recognition. Student evaluations were very favorable. Conclusion: A web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students.

Diverse modes of galacto-specific carbohydrate recognition by a family 31 glycoside hydrolase from Clostridium perfringens.

Directory of Open Access Journals (Sweden)

Julie M Grondin

Full Text Available Clostridium perfringens is a commensal member of the human gut microbiome and an opportunistic pathogen whose genome encodes a suite of putative large, multi-modular carbohydrate-active enzymes that appears to play a role in the interaction of the bacterium with mucin-based carbohydrates. Among the most complex of these is an enzyme that contains a presumed catalytic module belonging to glycoside hydrolase family 31 (GH31. This large enzyme, which based on its possession of a GH31 module is a predicted α-glucosidase, contains a variety of non-catalytic ancillary modules, including three CBM32 modules that to date have not been characterized. NMR-based experiments demonstrated a preference of each module for galacto-configured sugars, including the ability of all three CBM32s to recognize the common mucin monosaccharide GalNAc. X-ray crystal structures of the CpGH31 CBM32s, both in apo form and bound to GalNAc, revealed the finely-tuned molecular strategies employed by these sequentially variable CBM32s in coordinating a common ligand. The data highlight that sequence similarities to previously characterized CBMs alone are insufficient for identifying the molecular mechanism of ligand binding by individual CBMs. Furthermore, the overlapping ligand binding profiles of the three CBMs provide a fail-safe mechanism for the recognition of GalNAc among the dense eukaryotic carbohydrate networks of the colonic mucosa. These findings expand our understanding of ligand targeting by large, multi-modular carbohydrate-active enzymes, and offer unique insights into of the expanding ligand-binding preferences and binding site topologies observed in CBM32s.

Relative preservation of the recognition of positive facial expression "happiness" in Alzheimer disease.

Science.gov (United States)

Maki, Yohko; Yoshida, Hiroshi; Yamaguchi, Tomoharu; Yamaguchi, Haruyasu

2013-01-01

Positivity recognition bias has been reported for facial expression as well as memory and visual stimuli in aged individuals, whereas emotional facial recognition in Alzheimer disease (AD) patients is controversial, with possible involvement of confounding factors such as deficits in spatial processing of non-emotional facial features and in verbal processing to express emotions. Thus, we examined whether recognition of positive facial expressions was preserved in AD patients, by adapting a new method that eliminated the influences of these confounding factors. Sensitivity of six basic facial expressions (happiness, sadness, surprise, anger, disgust, and fear) was evaluated in 12 outpatients with mild AD, 17 aged normal controls (ANC), and 25 young normal controls (YNC). To eliminate the factors related to non-emotional facial features, averaged faces were prepared as stimuli. To eliminate the factors related to verbal processing, the participants were required to match the images of stimulus and answer, avoiding the use of verbal labels. In recognition of happiness, there was no difference in sensitivity between YNC and ANC, and between ANC and AD patients. AD patients were less sensitive than ANC in recognition of sadness, surprise, and anger. ANC were less sensitive than YNC in recognition of surprise, anger, and disgust. Within the AD patient group, sensitivity of happiness was significantly higher than those of the other five expressions. In AD patient, recognition of happiness was relatively preserved; recognition of happiness was most sensitive and was preserved against the influences of age and disease.

Mixed-ligand Pt(II) dithione-dithiolato complexes: influence of the dicyanobenzodithiolato ligand on the second-order NLO properties.

Science.gov (United States)

Espa, Davide; Pilia, Luca; Marchiò, Luciano; Artizzu, Flavia; Serpe, Angela; Mercuri, Maria Laura; Simão, Dulce; Almeida, Manuel; Pizzotti, Maddalena; Tessore, Francesca; Deplano, Paola

2012-03-28

The mixed-ligand dithiolene complex [Pt(Bz(2)pipdt)(dcbdt)] (1) bearing the two ligands Bz(2)pipdt = 1,4-dibenzyl-piperazine-3,2-dithione and dcbdt = dicyanobenzodithiolato, has been synthesized, characterized and studied to evaluate its second-order optical nonlinearity. The dithione/dithiolato character of the two ligands gives rise to an asymmetric distribution of the charge in the molecule. This is reflected by structural data showing that in the C(2)S(2)PtS(2)C(2) dithiolene core the four sulfur atoms define a square-planar coordination environment of the metal where the Pt-S bond distances involving the two ligands are similar, while the C-S bond distances in the C(2)S(2) units exhibit a significant difference in Bz(2)pipdt (dithione) and dcbdt (dithiolato). 1 shows a moderately strong absorption peak in the visible region, which can be related to a HOMO-LUMO transition, where the dcbdt ligand (dithiolato) contributes mostly to the HOMO, and the Bz(2)pipdt one (dithione) mostly to the LUMO. Thus this transition has ligand-to-ligand charge transfer (CT) character with some contribution of the metal and undergoes negative solvatochromism and molecular quadratic optical nonlinearity (μβ(0) = -1296 × 10(-48) esu), which was determined by the EFISH (electric-field-induced second-harmonic generation) technique and compared with the values of similar complexes on varying the dithiolato ligand (mnt = maleonitriledithiolato, dmit = 2-thioxo-1,3-dithiole-4,5-dithiolato). Theoretical calculations help to elucidate the role of the dithiolato ligands in affecting the molecular quadratic optical nonlinearity of these complexes.

Delivering organisational adaptation through legislative mechanisms: Evidence from the Adaptation Reporting Power (Climate Change Act 2008).

Science.gov (United States)

Jude, S R; Drew, G H; Pollard, S J T; Rocks, S A; Jenkinson, K; Lamb, R

2017-01-01

There is increasing recognition that organisations, particularly in key infrastructure sectors, are potentially vulnerable to climate change and extreme weather events, and require organisational responses to ensure they are resilient and adaptive. However, detailed evidence of how adaptation is facilitated, implemented and reported, particularly through legislative mechanisms is lacking. The United Kingdom Climate Change Act (2008), introduced the Adaptation Reporting Power, enabling the Government to direct so-called reporting authorities to report their climate change risks and adaptation plans. We describe the authors' unique role and experience supporting the Department for Environment, Food and Rural Affairs (Defra) during the Adaptation Reporting Power's first round. An evaluation framework, used to review the adaptation reports, is presented alongside evidence on how the process provides new insights into adaptation activities and triggered organisational change in 78% of reporting authorities, including the embedding of climate risk and adaptation issues. The role of legislative mechanisms and risk-based approaches in driving and delivering adaptation is discussed alongside future research needs, including the development of organisational maturity models to determine resilient and well adapting organisations. The Adaptation Reporting Power process provides a basis for similar initiatives in other countries, although a clear engagement strategy to ensure buy-in to the process and research on its long-term legacy, including the potential merits of voluntary approaches, is required. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Role of ligands in permanganate oxidation of organics.

Science.gov (United States)

Jiang, Jin; Pang, Su-Yan; Ma, Jun

2010-06-01

We previously demonstrated that several ligands such as phosphate, pyrophosphate, EDTA, and humic acid could significantly enhance permanganate oxidation of triclosan (one phenolic biocide), which was explained by the contribution of ligand-stabilized reactive manganese intermediates in situ formed upon permanganate reduction. To further understand the underlying mechanism, we comparatively investigated the influence of ligands on permanganate oxidation of bisphenol A (BPA, one phenolic endocrine-disrupting chemical), carbamazepine (CBZ, a pharmaceutical containing the olefinic group), and methyl p-tolyl sulfoxide (TMSO, a typical oxygen-atom acceptor). Selected ligands exerted oxidation enhancement for BPA but had negligible influence for CBZ and TMSO. This was mainly attributed to the effects of identified Mn(III) complexes, which would otherwise disproportionate spontaneously in the absence of ligands. The one-electron oxidant Mn(III) species exhibited no reactivity toward CBZ and TMSO for which the two-electron oxygen donation may be the primary oxidation mechanism but readily oxidized BPA. The latter case was a function of pH, the complexing ligand, and the molar [Mn(III)]:[ligand] ratio, generally consistent with the patterns of ligand-affected permanganate oxidation. Moreover, the combination of the one-electron reduction of Mn(III) (Mn(III) + e(-) -->Mn(II)) and the Mn(VII)/Mn(II) reaction in excess ligands (Mn(VII) + 4Mn(II) ----> (ligands) 5Mn(III)) suggested a catalytic role of the Mn(III)/Mn(II) pair in permanganate oxidation of some phenolics in the presence of ligands.

Differential expression of ligands for NKG2D and DNAM-1 receptors by epithelial ovarian cancer-derived exosomes and its influence on NK cell cytotoxicity.

Science.gov (United States)

Labani-Motlagh, Alireza; Israelsson, Pernilla; Ottander, Ulrika; Lundin, Eva; Nagaev, Ivan; Nagaeva, Olga; Dehlin, Eva; Baranov, Vladimir; Mincheva-Nilsson, Lucia

2016-04-01

Cancers constitutively produce and secrete into the blood and other biofluids 30-150 nm-sized endosomal vehicles called exosomes. Cancer-derived exosomes exhibit powerful influence on a variety of biological mechanisms to the benefit of the tumors that produce them. We studied the immunosuppressive ability of epithelial ovarian cancer (EOC) exosomes on two cytotoxic pathways of importance for anticancer immunity-the NKG2D receptor-ligand pathway and the DNAM-1-PVR/nectin-2 pathway. Using exosomes, isolated from EOC tumor explant and EOC cell-line culture supernatants, and ascitic fluid from EOC patients, we studied the expression of NKG2D and DNAM-1 ligands on EOC exosomes and their ability to downregulate the cognate receptors. Our results show that EOC exosomes differentially and constitutively express NKG2D ligands from both MICA/B and ULBP families on their surface, while DNAM-1 ligands are more seldom expressed and not associated with the exosomal membrane surface. Consequently, the NKG2D ligand-bearing EOC exosomes significantly downregulated the NKG2D receptor expression on peripheral blood mononuclear cells (PBMC) while the DNAM-1 receptor was unaffected. The downregulation of NKG2D receptor expression was coupled to inhibition of NKG2D receptor-ligand-mediated degranulation and cytotoxicity measured in vitro with OVCAR-3 and K562 cells as targets. The EOC exosomes acted as a decoy impairing the NKG2D mediated cytotoxicity while the DNAM-1 receptor-ligand system remained unchanged. Taken together, our results support and explain the mechanism behind the recently reported finding that in EOC, NK-cell recognition and killing of tumor cells was mainly dependent on DNAM-1 signaling while the contribution of the NKG2D receptor-ligand pathway was complementary and uncertain.

Determination of ligand binding modes in weak protein–ligand complexes using sparse NMR data

Energy Technology Data Exchange (ETDEWEB)

Mohanty, Biswaranjan; Williams, Martin L.; Doak, Bradley C.; Vazirani, Mansha; Ilyichova, Olga [Monash University, Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences (Australia); Wang, Geqing [La Trobe University, La Trobe Institute for Molecular Bioscience (Australia); Bermel, Wolfgang [Bruker Biospin GmbH (Germany); Simpson, Jamie S.; Chalmers, David K. [Monash University, Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences (Australia); King, Glenn F. [The University of Queensland, Institute for Molecular Bioscience (Australia); Mobli, Mehdi, E-mail: m.mobli@uq.edu.au [The University of Queensland, Centre for Advanced Imaging (Australia); Scanlon, Martin J., E-mail: martin.scanlon@monash.edu [Monash University, Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences (Australia)

2016-11-15

We describe a general approach to determine the binding pose of small molecules in weakly bound protein–ligand complexes by deriving distance constraints between the ligand and methyl groups from all methyl-containing residues of the protein. We demonstrate that using a single sample, which can be prepared without the use of expensive precursors, it is possible to generate high-resolution data rapidly and obtain the resonance assignments of Ile, Leu, Val, Ala and Thr methyl groups using triple resonance scalar correlation data. The same sample may be used to obtain Met {sup ε}CH{sub 3} assignments using NOESY-based methods, although the superior sensitivity of NOESY using [U-{sup 13}C,{sup 15}N]-labeled protein makes the use of this second sample more efficient. We describe a structural model for a weakly binding ligand bound to its target protein, DsbA, derived from intermolecular methyl-to-ligand nuclear Overhauser enhancements, and demonstrate that the ability to assign all methyl resonances in the spectrum is essential to derive an accurate model of the structure. Once the methyl assignments have been obtained, this approach provides a rapid means to generate structural models for weakly bound protein–ligand complexes. Such weak complexes are often found at the beginning of programs of fragment based drug design and can be challenging to characterize using X-ray crystallography.

Channel Compensation for Speaker Recognition using MAP Adapted PLDA and Denoising DNNs

Science.gov (United States)

2016-06-21

05 Jabra Cellphone Earwrap Mic 06 Motorola Cellphone Earbud 07 Olympus Pearlcorder 08 Radio Shack Computer Desktop Mic Table 1: Mixer 1 and 2...EER and min DCF vs λ for 2cov map adapt PLDA the MAP adapted PLDA model using a λ of 0.5. The remain- ing rows demonstrate the impact of the feature...degrading perfor- mance on conversational telephone speech. To assess the per- formance impact of the denoising DNN on telephony data we evaluated the

Radiation induced ligand loss from cobalt complexes

International Nuclear Information System (INIS)

Funston, A. M.; McFadyen, W.D.; Tregloan, P.A.

2000-01-01

Full text: Due to the rapid nature of ligand dissociation from cobalt(II) complexes the study of the rate of ligand dissociation necessitates the use of a technique such as pulse radiolysis. This allows the rapid reduction of the corresponding cobalt(III) complex by a reducing radical, such as the aquated electron, to form the cobalt(II) complex. However, to date, no systematic study of either the mechanism of reduction or the influence of the electronic structure on the rate of ligand dissociation has been carried out. In order to understand these processes more fully the mechanism of reduction of a range of related cobalt(III) complexes by the aquated electron and the subsequent rate of ligand dissociation from the resulting cobalt(II) complexes is being investigated. It has been found that a number of processes are observed following the initial rapid reaction of the cobalt(III) complex with the aquated electron. Ultimately ligand loss is observed. Depending upon the complex, the initial processes observed may include the formation of coordinated radicals and electron transfer within the complex. For complexes containing aromatic ligands such as 2,2'-bipyridine, 1,10-phenanthroline and dipyrido[3,2-a:2',3'-c]phenazine the formation of a coordinated radical is observed as the initial reduction step. The kinetics of ligand dissociation of these complexes has been determined. The loss of monodentate ligands is fast and has been indistinguishable from the reduction processes when aromatic ligands are also present in the complex. However, for diamine chelates and diimine chelates spectra of the transient species can be resolved

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Recognition memory is improved by a structured temporal framework during encoding

Directory of Open Access Journals (Sweden)

Sathesan eThavabalasingam

2016-01-01

Full Text Available In order to function optimally within our environment, we continuously extract temporal patterns from our experiences and formulate expectations that facilitate adaptive behavior. Given that our memories are embedded within spatiotemporal contexts, an intriguing possibility is that mnemonic processes are sensitive to the temporal structure of events. To test this hypothesis, in a series of behavioral experiments we manipulated the regularity of interval durations at encoding to create temporally structured and unstructured frameworks. Our findings revealed enhanced recognition memory (d’ for stimuli that were explicitly encoded within a temporally structured versus unstructured framework. Encoding information within a temporally structured framework was also associated with a reduction in the negative effects of proactive interference and was linked to greater recollective recognition memory. Furthermore, rhythmic temporal structure was found to enhance recognition memory for incidentally encoded information. Collectively, these results support the possibility that we possess a greater capacity to learn and subsequently remember temporally structured information.

Climate change adaptation and social sciences

International Nuclear Information System (INIS)

Charles, L.

2013-01-01

Climate change subjects societies to a large range of uncertainties concerning the future and their development orientation. It came up as a scientific global problem, extended to political concerns first at a global and then national scales. Though it has long been the object of economic approaches which have notably contributed to its recognition, particularly the Stern Report, social sciences have hardly been mobilized as part of policies to counteract it. Social sciences strongly question the notion of climate change being built as a global scale transcendent phenomenon, analyzed by several authors. With the rise of adaptation policies, the question becomes even more important. Adaptation first comes up as a spontaneous behaviour, independent of policy, in close relationship to social dimensions as a basic way through which climate change is grasped collectively. Thus adaptation policies' social aspects need to be carefully worked in relation with more general goals for adaptation policies to be implemented efficiently, on the basis of wide interactions between local and global scales. (author)

Synthesis and characterization of mixed ligand chiral nanoclusters

KAUST Repository

Guven, Zekiye P.; Ustbas, Burcin; Harkness, Kellen M.; Coskun, Hikmet; Joshi, Chakra Prasad; Besong, Tabot M.D.; Stellacci, Francesco; Bakr, Osman; Akbulut, Ozge

2016-01-01

Chiral mixed ligand silver nanoclusters were synthesized in the presence of a chiral and an achiral ligand. While the chiral ligand led mostly to the formation of nanoparticles, the presence of the achiral ligand drastically increased the yield of nanoclusters with enhanced chiral properties. © 2016 The Royal Society of Chemistry.

Synthesis and characterization of mixed ligand chiral nanoclusters

KAUST Repository

Guven, Zekiye P.

2016-06-22

Chiral mixed ligand silver nanoclusters were synthesized in the presence of a chiral and an achiral ligand. While the chiral ligand led mostly to the formation of nanoparticles, the presence of the achiral ligand drastically increased the yield of nanoclusters with enhanced chiral properties. © 2016 The Royal Society of Chemistry.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

Science.gov (United States)

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Identifying Marine Copper-Binding Ligands in Seawater

Science.gov (United States)

Whitby, H.; Hollibaugh, J. T.; Maldonado, M. T.; Ouchi, S.; van den Berg, S. M.

2016-02-01

Complexation reactions are important because they affect the bioavailability of trace metals such as copper and iron. For example, organic complexation can determine whether copper is a limiting or a toxic micronutrient at natural levels. Copper competes with iron for complexing ligands, and when iron is limiting, copper can also substitute for iron in some metabolic pathways. The speciation of copper can be measured using complexing capacity titrations, which provide the concentration of individual ligand classes (L1, L2 etc.) and the complex stabilities (log K). Using methods recently developed in our laboratory, we show that the ligands within these classes can be measured independently of titrations, thus confirming the titration method and simultaneously identifying the ligands within each class. Thiols were identified as the L1 ligand class and humic compounds as the weaker L2 class in samples from coastal Georgia, USA, collected monthly from April to December. Log K values of the ligand complexes were consistent with values expected for thiols and humic substances. Recent results from culture studies and from samples collected along Line P, a coastal - oceanic transect in the HNLC region of the NE subarctic Pacific, will be presented in comparison to the estuarine results. This comparison will help to broaden our perspective on copper complexation and the ligands responsible, furthering our understanding of ligand sources and life cycles.

Conformational entropy changes upon lactose binding to the carbohydrate recognition domain of galectin-3

International Nuclear Information System (INIS)

Diehl, Carl; Genheden, Samuel; Modig, Kristofer; Ryde, Ulf; Akke, Mikael

2009-01-01

The conformational entropy of proteins can make significant contributions to the free energy of ligand binding. NMR spin relaxation enables site-specific investigation of conformational entropy, via order parameters that parameterize local reorientational fluctuations of rank-2 tensors. Here we have probed the conformational entropy of lactose binding to the carbohydrate recognition domain of galectin-3 (Gal3), a protein that plays an important role in cell growth, cell differentiation, cell cycle regulation, and apoptosis, making it a potential target for therapeutic intervention in inflammation and cancer. We used 15 N spin relaxation experiments and molecular dynamics simulations to monitor the backbone amides and secondary amines of the tryptophan and arginine side chains in the ligand-free and lactose-bound states of Gal3. Overall, we observe good agreement between the experimental and computed order parameters of the ligand-free and lactose-bound states. Thus, the 15 N spin relaxation data indicate that the molecular dynamics simulations provide reliable information on the conformational entropy of the binding process. The molecular dynamics simulations reveal a correlation between the simulated order parameters and residue-specific backbone entropy, re-emphasizing that order parameters provide useful estimates of local conformational entropy. The present results show that the protein backbone exhibits an increase in conformational entropy upon binding lactose, without any accompanying structural changes

Substrate coated with receptor and labelled ligand for assays

International Nuclear Information System (INIS)

1980-01-01

Improvements in the procedures for assaying ligands are described. The assay consists of a polystyrene tube on which receptors are present for both the ligand to be assayed and a radioactively labelled form of the ligand. The receptors on the bottom portion of the tube are also coated with labelled ligands, thus eliminating the necessity for separate addition of the labelled ligand and sample during an assay. Examples of ligands to which this method is applicable include polypeptides, nucleotides, nucleosides and proteins. Specific examples are given in which the ligand to be assayed is digoxin, the labelled form of the ligand is 3-0-succinyl digoxyigenin tyrosine ( 125 I) and the receptor is digoxin antibody. (U.K.)

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor.

Science.gov (United States)

Malo, Marcus; Persson, Ronnie; Svensson, Peder; Luthman, Kristina; Brive, Lars

2013-03-01

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

Directory of Open Access Journals (Sweden)

Yuanshen Zhao

2016-01-01

Full Text Available Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion.

Science.gov (United States)

Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

2016-01-29

Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

Deep Belief Networks Based Toponym Recognition for Chinese Text

Directory of Open Access Journals (Sweden)

Shu Wang

2018-06-01

Full Text Available In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo

Correcting binding parameters for interacting ligand-lattice systems

Science.gov (United States)

Hervy, Jordan; Bicout, Dominique J.

2017-07-01

Binding of ligands to macromolecules is central to many functional and regulatory biological processes. Key parameters characterizing ligand-macromolecule interactions are the stoichiometry, inducing the number of ligands per macromolecule binding site, and the dissociation constant, quantifying the ligand-binding site affinity. Both these parameters can be obtained from analyses of classical saturation experiments using the standard binding equation that offers the great advantage of mathematical simplicity but becomes an approximation for situations of interest when a ligand binds and covers more than one single binding site on the macromolecule. Using the framework of car-parking problem with latticelike macromolecules where each ligand can cover simultaneously several consecutive binding sites, we showed that employing the standard analysis leads to underestimation of binding parameters, i.e., ligands appear larger than they actually are and their affinity is also greater than it is. Therefore, we have derived expressions allowing to determine the ligand size and true binding parameters (stoichiometry and dissociation constant) as a function of apparent binding parameters retrieved from standard saturation experiments.

Increased deficits in emotion recognition and regulation in children and adolescents with exogenous obesity.

Science.gov (United States)

Percinel, Ipek; Ozbaran, Burcu; Kose, Sezen; Simsek, Damla Goksen; Darcan, Sukran

2018-03-01

In this study we aimed to evaluate emotion recognition and emotion regulation skills of children with exogenous obesity between the ages of 11 and 18 years and compare them with healthy controls. The Schedule for Affective Disorders and Schizophrenia for School Aged Children was used for psychiatric evaluations. Emotion recognition skills were evaluated using Faces Test and Reading the Mind in the Eyes Test. The Difficulties in Emotions Regulation Scale was used for evaluating skills of emotion regulation. Children with obesity had lower scores on Faces Test and Reading the Mind in the Eyes Test, and experienced greater difficulty in emotional regulation skills. Improved understanding of emotional recognition and emotion regulation in young people with obesity may improve their social adaptation and help in the treatment of their disorder. To the best of our knowledge, this is the first study to evaluate both emotional recognition and emotion regulation functions in obese children and obese adolescents between 11 and 18 years of age.

Development of immobilized ligands for actinide separations

International Nuclear Information System (INIS)

Paine, R.T.

1994-01-01

Primary goals during this grant period were to (1) synthesize new bifunctional chelating ligands, (2) characterize the structural features of the Ln and An coordination complexes formed by these ligands, (3) use structural data to iteratively design new classes of multifunctional ligands, and (4) explore additional routes for attachment of key ligands to solid supports that could be useful for chromatographic separations. Some highlights of recently published work as well as a summary of submitted, unpublished and/or still in progress research are outlined

The pattern recognition molecule ficolin-1 exhibits differential binding to lymphocyte subsets, providing a novel link between innate and adaptive immunity

DEFF Research Database (Denmark)

Genster, Ninette; Ma, Ying Jie; Munthe-Fog, Lea

2014-01-01

is unknown. Recognition of healthy host cells by a pattern recognition molecule constitutes a potential hazard to self cells and tissues, emphasizing the importance of further elucidating the reported self-recognition. In the current study we investigated the potential recognition of lymphocytes by ficolin-1...... and demonstrated that CD56(dim) NK-cells and both CD4(+) and CD8(+) subsets of activated T-cells were recognized by ficolin-1. In contrast we did not detect binding of ficolin-1 to CD56(bright) NK-cells, NKT-cells, resting T-cells or B-cells. Furthermore, we showed that the protein-lymphocyte interaction occurred...

Reflowing-driven paragraph recognition for electronic books in PDF

Science.gov (United States)

Fang, Jing; Tang, Zhi; Gao, Liangcai

2011-01-01

When reading electronic books on handheld devices, content sometimes should be reflowed and recomposed to adapt for small-screen mobile devices. According to people's reading practice, it is reasonable to reflow the text content based on paragraphs. Hence, this paper addresses the requirement and proposes a set of novel methods on paragraph recognition for electronic books in PDF. The proposed methods consist of three steps, namely, physical structure analysis, paragraph segmentation, and reading order detection. We make use of locally ordered property of PDF documents and layout style of books to improve traditional page recognition results. In addition, we employ the optimal matching of Bipartite Graph technology to detect paragraphs' reading order. Experiments show that our methods achieve high accuracy. It is noteworthy that, the research has been applied in a commercial software package for Chinese E-book production.

Manduca sexta recognition and resistance among allopolyploid Nicotiana host plants

OpenAIRE

Lou, Yonggen; Baldwin, Ian T.

2003-01-01

Allopolyploid speciation occurs instantly when the genomes of different species combine to produce self-fertile offspring and has played a central role in the evolution of higher plants, but its consequences for adaptive responses are unknown. We compare herbivore-recognition and -resistance responses of the diploid species and putative ancestral parent Nicotiana attenuata with those of the two derived allopolyploid species Nicotiana clevelandii and Nicotiana bigelovii. Manduca sexta larvae a...

Semantic Network Adaptation Based on QoS Pattern Recognition for Multimedia Streams

Science.gov (United States)

Exposito, Ernesto; Gineste, Mathieu; Lamolle, Myriam; Gomez, Jorge

This article proposes an ontology based pattern recognition methodology to compute and represent common QoS properties of the Application Data Units (ADU) of multimedia streams. The use of this ontology by mechanisms located at different layers of the communication architecture will allow implementing fine per-packet self-optimization of communication services regarding the actual application requirements. A case study showing how this methodology is used by error control mechanisms in the context of wireless networks is presented in order to demonstrate the feasibility and advantages of this approach.

Entangled zinc-ditetrazolate frameworks involving in situ ligand synthesis and topological modulation by various secondary N-donor ligands

International Nuclear Information System (INIS)

Li Yunwu; Chen Weilin; Wang Yonghui; Li Yangguang; Wang Enbo

2009-01-01

The introduction of various secondary N-donor ligands into an in situ ditetrazolate-ligand synthesis system of terephthalonitrile, NaN 3 and ZnCl 2 led to the formation of three new entangled frameworks Zn(pdtz)(4,4'-bipy).3H 2 O (1), [Zn(pdtz)(bpp)] 2 .3H 2 O (2) and Zn(pdtz) 0.5 (N 3 )(2,2'-bipy) (3) (4,4'-bipy=4,4'-bipyridine; bpp=1,3-bis(4-pyridyl)propane; 2,2'-bipy=2,2'-bipyridine; H 2 pdtz=5,5'-1,4-phenylene-ditetrazole). The formation of pdtz 2- ligand involves the Sharpless [2+3] cycloaddition reaction between terephthalonitrile and NaN 3 in the presence of Zn 2+ ion as a Lewis-acid catalyst under hydrothermal conditions. Compound 1 exhibits a fivefold interpenetrating 3D framework based on the diamondoid topology. Compound 2 displays a twofold parallel interpenetrating framework based on the wavelike individual network. Compound 3 possesses a 2D puckered network. These new Zn-ditetrazolate frameworks are highly dependent on the modulation of different secondary N-donor ligands. Their luminescent properties were investigated. - Graphical abstract: Three new entangled frameworks were prepared by an in situ ditetrazolate-ligand synthesis system assisted with various auxiliary N-donor ligands. The entangled structures can be modulated by different secondary ligands.

Contribution to automatic speech recognition. Analysis of the direct acoustical signal. Recognition of isolated words and phoneme identification

International Nuclear Information System (INIS)

Dupeyrat, Benoit

1981-01-01

This report deals with the acoustical-phonetic step of the automatic recognition of the speech. The parameters used are the extrema of the acoustical signal (coded in amplitude and duration). This coding method, the properties of which are described, is simple and well adapted to a digital processing. The quality and the intelligibility of the coded signal after reconstruction are particularly satisfactory. An experiment for the automatic recognition of isolated words has been carried using this coding system. We have designed a filtering algorithm operating on the parameters of the coding. Thus the characteristics of the formants can be derived under certain conditions which are discussed. Using these characteristics the identification of a large part of the phonemes for a given speaker was achieved. Carrying on the studies has required the development of a particular methodology of real time processing which allowed immediate evaluation of the improvement of the programs. Such processing on temporal coding of the acoustical signal is extremely powerful and could represent, used in connection with other methods an efficient tool for the automatic processing of the speech.(author) [fr

Building social-ecological resilience through adaptive comanagement in the Cache River Watershed of southern Illinois

Science.gov (United States)

Kofi. Akamani

2014-01-01

There is growing recognition that the sustainable governance of water resources requires building social-ecological resilience against future surprises. Adaptive comanagement, a distinct institutional mechanism that combines the learning focus of adaptive management with the multilevel linkages of comanagement, has recently emerged as a promising mechanism for building...

Selective extraction of trivalent actinides with hard-soft mixed donor ligands: role of intra-ligand synergism

International Nuclear Information System (INIS)

Ghanty, Tapan K.

2016-01-01

In recent years, considerable attention has been given to understand the coordination chemistry of trivalent lanthanide (Ln) and actinide (An) with various ligands because of its close link with the nuclear waste management processes. It is well known that lanthanide-actinide separation is a challenging and difficult task because of very similar chemical properties of these two series of ions, which are associated with similar ionic radii and coordination numbers. Recently, we have introduced a new concept, 'intra-ligand synergism', where hard donor atom, such as, oxygen preferentially binds to trivalent actinides (An(III)) as compared to the valence iso-electronic trivalent lanthanides (Ln(III)) in presence of another soft donor centre. In the present work, the conventional concept of selective complexation of actinides with soft donor ligands (either S or N donor) has been modified through exploiting this concept, and thereby the higher selectivity of 1,10-phenanthroline-2,9-dicarboxylamide (PDAM) based ligands, namely PDAM and its isobutyl and decyl derivatives towards Am(III) ion has been predicted theoretically through density functional calculations. Subsequently, several such amide derivatives have been synthesized to optimize the solubility of the ligands in organic phase. Finally, solvent extraction experiments have been carried out to validate the theoretical prediction on the selectivity of oxygen donor ligands towards Am(III) as compared to Eu(III), and a maximum separation factor of about 51 has been achieved experimentally using 2,9-bis(N-decylaminocarbonyl)-1,10-phenanthroline ligand. The separation factor is increased with the decrease in pH, which is very interesting since extraction of the Am 3+ ion is considered to be important under highly acidic conditions from the nuclear waste management point of view. (author)

Synthesis, spectral, thermal and biological studies of mixed ligand complexes with newly prepared Schiff base and 1,10-phenanthroline ligands

Science.gov (United States)

Abd El-Halim, Hanan F.; Mohamed, Gehad G.; Khalil, Eman A. M.

2017-10-01

A series of mixed ligand complexes were prepared from the Schiff base (L1) as a primary ligand, prepared by condensation of oxamide and furan-2-carbaldehyde, and 1,10-phenanthroline (1,10-phen) as a secondary ligand. The Schiff base ligand and its mixed ligand chelates were characterized based on elemental analysis, IR, 1H NMR, thermal analysis, UV-Visible, mass, molar conductance, magnetic moment. X-ray diffraction, solid reflectance and ESR also have been studied. The mixed ligand complexes were found to have the formulae of [M(L1) (1,10-phen)]Clm.nH2O (M = Cr(III) and Fe(III) (m = 3) (n = 0); M = Mn(II), Cu(II) and Cd(II) (m = 2) (n = 0); and M = Co(II) (m = 2) (n = 1), Ni(II) (m = 2) (n = 2) and Zn(II) (m = 2) (n = 3)) and that the geometrical structure of the complexes were octahedral. The parameters of thermodynamic using Coats-Redfern and Horowitz-Metzger equations were calculated. The synthesized Schiff base ligand, 1,10-phenanthroline ligand and Their mixed ligand complexes were also investigated for their antibacterial and antifungal activity against bacterial species (Gram-Ve bacteria: Pseudomonas aeruginosa and Escherichia coli) and (Gram + Ve bacteria: Bacillus subtilis and Streptococcus pneumonia) and fungi (Aspergillus fumigates and Candida albicans). The anticancer activity of the new compounds had been tested against breast (MFC7) and colon (HCT-116) cell lines. The results showed high activity for the synthesized compounds.

Autocrine signal transmission with extracellular ligand degradation

International Nuclear Information System (INIS)

Muratov, C B; Posta, F; Shvartsman, S Y

2009-01-01

Traveling waves of cell signaling in epithelial layers orchestrate a number of important processes in developing and adult tissues. These waves can be mediated by positive feedback autocrine loops, a mode of cell signaling where binding of a diffusible extracellular ligand to a cell surface receptor can lead to further ligand release. We formulate and analyze a biophysical model that accounts for ligand-induced ligand release, extracellular ligand diffusion and ligand–receptor interaction. We focus on the case when the main mode for ligand degradation is extracellular and analyze the problem with the sharp threshold positive feedback nonlinearity. We derive expressions that link the speed of propagation and other characteristics of traveling waves to the parameters of the biophysical processes, such as diffusion rates, receptor expression level, etc. Analyzing the derived expressions we found that traveling waves in such systems can exhibit a number of unusual properties, e.g. non-monotonic dependence of the speed of propagation on ligand diffusivity. Our results for the fully developed traveling fronts can be used to analyze wave initiation from localized perturbations, a scenario that frequently arises in the in vitro models of epithelial wound healing, and guide future modeling studies of cell communication in epithelial layers

Dockomatic - automated ligand creation and docking.

Science.gov (United States)

Bullock, Casey W; Jacob, Reed B; McDougal, Owen M; Hampikian, Greg; Andersen, Tim

2010-11-08

The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI) application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions. DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations. DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management.

Dockomatic - automated ligand creation and docking

Directory of Open Access Journals (Sweden)

Hampikian Greg

2010-11-01

Full Text Available Abstract Background The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions. Results DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations. Conclusions DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management.

Speech Recognition for the iCub Platform

Directory of Open Access Journals (Sweden)

Bertrand Higy

2018-02-01

Full Text Available This paper describes open source software (available at https://github.com/robotology/natural-speech to build automatic speech recognition (ASR systems and run them within the YARP platform. The toolkit is designed (i to allow non-ASR experts to easily create their own ASR system and run it on iCub and (ii to build deep learning-based models specifically addressing the main challenges an ASR system faces in the context of verbal human–iCub interactions. The toolkit mostly consists of Python, C++ code and shell scripts integrated in YARP. As additional contribution, a second codebase (written in Matlab is provided for more expert ASR users who want to experiment with bio-inspired and developmental learning-inspired ASR systems. Specifically, we provide code for two distinct kinds of speech recognition: “articulatory” and “unsupervised” speech recognition. The first is largely inspired by influential neurobiological theories of speech perception which assume speech perception to be mediated by brain motor cortex activities. Our articulatory systems have been shown to outperform strong deep learning-based baselines. The second type of recognition systems, the “unsupervised” systems, do not use any supervised information (contrary to most ASR systems, including our articulatory systems. To some extent, they mimic an infant who has to discover the basic speech units of a language by herself. In addition, we provide resources consisting of pre-trained deep learning models for ASR, and a 2.5-h speech dataset of spoken commands, the VoCub dataset, which can be used to adapt an ASR system to the typical acoustic environments in which iCub operates.

One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

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Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

2016-05-10

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

Pyoverdine, the Major Siderophore in Pseudomonas aeruginosa, Evades NGAL Recognition

Directory of Open Access Journals (Sweden)

Mary E. Peek

2012-01-01

Full Text Available Pseudomonas aeruginosa is the most common pathogen that persists in the cystic fibrosis lungs. Bacteria such as P. aeruginosa secrete siderophores (iron-chelating molecules and the host limits bacterial growth by producing neutrophil-gelatinase-associated lipocalin (NGAL that specifically scavenges bacterial siderophores, therefore preventing bacteria from establishing infection. P. aeruginosa produces a major siderophore known as pyoverdine, found to be important for bacterial virulence and biofilm development. We report that pyoverdine did not bind to NGAL, as measured by tryptophan fluorescence quenching, while enterobactin bound to NGAL effectively causing a strong response. The experimental data indicate that pyoverdine evades NGAL recognition. We then employed a molecular modeling approach to simulate the binding of pyoverdine to human NGAL using NGAL’s published crystal structures. The docking of pyoverdine to NGAL predicted nine different docking positions; however, neither apo- nor ferric forms of pyoverdine docked into the ligand-binding site in the calyx of NGAL where siderophores are known to bind. The molecular modeling results offer structural support that pyoverdine does not bind to NGAL, confirming the results obtained in the tryptophan quenching assay. The data suggest that pyoverdine is a stealth siderophore that evades NGAL recognition allowing P. aeruginosa to establish chronic infections in CF lungs.

Descriptor Data Bank (DDB): A Cloud Platform for Multiperspective Modeling of Protein-Ligand Interactions.

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Ashtawy, Hossam M; Mahapatra, Nihar R

2018-01-22

Protein-ligand (PL) interactions play a key role in many life processes such as molecular recognition, molecular binding, signal transmission, and cell metabolism. Examples of interaction forces include hydrogen bonding, hydrophobic effects, steric clashes, electrostatic contacts, and van der Waals attractions. Currently, a large number of hypotheses and perspectives to model these interaction forces are scattered throughout the literature and largely forgotten. Instead, had they been assembled and utilized collectively, they would have substantially improved the accuracy of predicting binding affinity of protein-ligand complexes. In this work, we present Descriptor Data Bank (DDB), a data-driven platform on the cloud for facilitating multiperspective modeling of PL interactions. DDB is an open-access hub for depositing, hosting, executing, and sharing descriptor extraction tools and data for a large number of interaction modeling hypotheses. The platform also implements a machine-learning (ML) toolbox for automatic descriptor filtering and analysis and scoring function (SF) fitting and prediction. The descriptor filtering module is used to filter out irrelevant and/or noisy descriptors and to produce a compact subset from all available features. We seed DDB with 16 diverse descriptor extraction tools developed in-house and collected from the literature. The tools altogether generate over 2700 descriptors that characterize (i) proteins, (ii) ligands, and (iii) protein-ligand complexes. The in-house descriptors we extract are protein-specific which are based on pairwise primary and tertiary alignment of protein structures followed by clustering and trilateration. We built and used DDB's ML library to fit SFs to the in-house descriptors and those collected from the literature. We then evaluated them on several data sets that were constructed to reflect real-world drug screening scenarios. We found that multiperspective SFs that were constructed using a large number

Speech Recognition

Directory of Open Access Journals (Sweden)

Adrian Morariu

2009-01-01

Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

Recognition of speaker-dependent continuous speech with KEAL

Science.gov (United States)

Mercier, G.; Bigorgne, D.; Miclet, L.; Le Guennec, L.; Querre, M.

1989-04-01

A description of the speaker-dependent continuous speech recognition system KEAL is given. An unknown utterance, is recognized by means of the followng procedures: acoustic analysis, phonetic segmentation and identification, word and sentence analysis. The combination of feature-based, speaker-independent coarse phonetic segmentation with speaker-dependent statistical classification techniques is one of the main design features of the acoustic-phonetic decoder. The lexical access component is essentially based on a statistical dynamic programming technique which aims at matching a phonemic lexical entry containing various phonological forms, against a phonetic lattice. Sentence recognition is achieved by use of a context-free grammar and a parsing algorithm derived from Earley's parser. A speaker adaptation module allows some of the system parameters to be adjusted by matching known utterances with their acoustical representation. The task to be performed, described by its vocabulary and its grammar, is given as a parameter of the system. Continuously spoken sentences extracted from a 'pseudo-Logo' language are analyzed and results are presented.

Stable Toll-Like Receptor 10 Knockdown in THP-1 Cells Reduces TLR-Ligand-Induced Proinflammatory Cytokine Expression

Directory of Open Access Journals (Sweden)

Hai Van Le

2016-06-01

Full Text Available Toll-like receptor 10 (TLR10 is the only orphan receptor whose natural ligand and function are unknown among the 10 human TLRs. In this study, to test whether TLR10 recognizes some known TLR ligands, we established a stable TLR10 knockdown human monocytic cell line THP-1 using TLR10 short hairpin RNA lentiviral particle and puromycin selection. Among 60 TLR10 knockdown clones that were derived from each single transduced cell, six clones were randomly selected, and then one of those clones, named E7, was chosen for the functional study. E7 exhibited approximately 50% inhibition of TLR10 mRNA and protein expression. Of all the TLRs, only the expression of TLR10 changed significantly in this cell line. Additionally, phorbol 12-myristate 13-acetate-induced macrophage differentiation of TLR10 knockdown cells was not affected in the knockdown cells. When exposed to TLR ligands, such as synthetic diacylated lipoprotein (FSL-1, lipopolysaccharide (LPS, and flagellin, significant induction of proinflammatory cytokine gene expression including Interleukin-8 (IL-8, Interleukin-1 beta (IL-1β, Tumor necrosis factor-alpha (TNF-α and Chemokine (C–C Motif Ligand 20 (CCL20 expression, was found in the control THP-1 cells, whereas the TLR10 knockdown cells exhibited a significant reduction in the expression of IL-8, IL-1β, and CCL20. TNF-α was the only cytokine for which the expression did not decrease in the TLR10 knockdown cells from that measured in the control cells. Analysis of putative binding sites for transcription factors using a binding-site-prediction program revealed that the TNF-α promoter does not have putative binding sites for AP-1 or c-Jun, comprising a major transcription factor along with NF-κB for TLR signaling. Our results suggest that TLR10 is involved in the recognition of FSL-1, LPS, and flagellin and TLR-ligand-induced expression of TNF-α does not depend on TLR10.

Stable Toll-Like Receptor 10 Knockdown in THP-1 Cells Reduces TLR-Ligand-Induced Proinflammatory Cytokine Expression.

Science.gov (United States)

Le, Hai Van; Kim, Jae Young

2016-06-01

Toll-like receptor 10 (TLR10) is the only orphan receptor whose natural ligand and function are unknown among the 10 human TLRs. In this study, to test whether TLR10 recognizes some known TLR ligands, we established a stable TLR10 knockdown human monocytic cell line THP-1 using TLR10 short hairpin RNA lentiviral particle and puromycin selection. Among 60 TLR10 knockdown clones that were derived from each single transduced cell, six clones were randomly selected, and then one of those clones, named E7, was chosen for the functional study. E7 exhibited approximately 50% inhibition of TLR10 mRNA and protein expression. Of all the TLRs, only the expression of TLR10 changed significantly in this cell line. Additionally, phorbol 12-myristate 13-acetate-induced macrophage differentiation of TLR10 knockdown cells was not affected in the knockdown cells. When exposed to TLR ligands, such as synthetic diacylated lipoprotein (FSL-1), lipopolysaccharide (LPS), and flagellin, significant induction of proinflammatory cytokine gene expression including Interleukin-8 (IL-8), Interleukin-1 beta (IL-1β), Tumor necrosis factor-alpha (TNF-α) and Chemokine (C-C Motif) Ligand 20 (CCL20) expression, was found in the control THP-1 cells, whereas the TLR10 knockdown cells exhibited a significant reduction in the expression of IL-8, IL-1β, and CCL20. TNF-α was the only cytokine for which the expression did not decrease in the TLR10 knockdown cells from that measured in the control cells. Analysis of putative binding sites for transcription factors using a binding-site-prediction program revealed that the TNF-α promoter does not have putative binding sites for AP-1 or c-Jun, comprising a major transcription factor along with NF-κB for TLR signaling. Our results suggest that TLR10 is involved in the recognition of FSL-1, LPS, and flagellin and TLR-ligand-induced expression of TNF-α does not depend on TLR10.

Recognition and Toleration

DEFF Research Database (Denmark)

Lægaard, Sune

2010-01-01

Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...... or interpretations of recognition and toleration are considered, confusing and problematic uses of the terms are noted, and the compatibility of toleration and recognition is discussed. The article argues that there is a range of legitimate and importantly different conceptions of both toleration and recognition...

Superior voice recognition in a patient with acquired prosopagnosia and object agnosia.

Science.gov (United States)

Hoover, Adria E N; Démonet, Jean-François; Steeves, Jennifer K E

2010-11-01

Anecdotally, it has been reported that individuals with acquired prosopagnosia compensate for their inability to recognize faces by using other person identity cues such as hair, gait or the voice. Are they therefore superior at the use of non-face cues, specifically voices, to person identity? Here, we empirically measure person and object identity recognition in a patient with acquired prosopagnosia and object agnosia. We quantify person identity (face and voice) and object identity (car and horn) recognition for visual, auditory, and bimodal (visual and auditory) stimuli. The patient is unable to recognize faces or cars, consistent with his prosopagnosia and object agnosia, respectively. He is perfectly able to recognize people's voices and car horns and bimodal stimuli. These data show a reverse shift in the typical weighting of visual over auditory information for audiovisual stimuli in a compromised visual recognition system. Moreover, the patient shows selectively superior voice recognition compared to the controls revealing that two different stimulus domains, persons and objects, may not be equally affected by sensory adaptation effects. This also implies that person and object identity recognition are processed in separate pathways. These data demonstrate that an individual with acquired prosopagnosia and object agnosia can compensate for the visual impairment and become quite skilled at using spared aspects of sensory processing. In the case of acquired prosopagnosia it is advantageous to develop a superior use of voices for person identity recognition in everyday life. Copyright © 2010 Elsevier Ltd. All rights reserved.

Synthesis of novel '4+1' Tc(III)/Re(III) mixed-ligand complexes with dendritically modified ligands

International Nuclear Information System (INIS)

Gniazdowska, E.; Kuenstler, J.U.; Stephan, H.; Pietzsch, H.J.

2006-01-01

Coordination chemistry of technetium and rhenium attracts a considerable interest due to the nuclear medicine applications of their radionuclides. Inert, so-called '3+1' or '4+1' technetium/rhenium mixed-ligand complexes open a new way to application of 99 mTc/ 188 Re labeled compounds in tumor diagnosis and therapy. In the presented paper, authors describe the synthesis and study of novel 99 mTc/ 188 Re complexes with dendritically functionalized tetradentate (tripodal chelator 2,2',2''-nitrilotris(ethanethiol), NS 3 and carboxyl group-bearing ligand, NS 3 (COOH) 3 ) and monodentate (dendritically modified isocyanide, CN-R(COOMe) 3 and isocyanide-modified peptide, CN-GGY) ligands. To verify the identity of the prepared n.c.a. complexes, non-radioactive analogous '4+1' Re compounds were synthesized. The experimental data show that a dendritic modification of the tetradentate/monodentate ligands changes the complex lipophilicity and does not influence its stability

On the Time Course of Vocal Emotion Recognition

Science.gov (United States)

Pell, Marc D.; Kotz, Sonja A.

2011-01-01

How quickly do listeners recognize emotions from a speaker's voice, and does the time course for recognition vary by emotion type? To address these questions, we adapted the auditory gating paradigm to estimate how much vocal information is needed for listeners to categorize five basic emotions (anger, disgust, fear, sadness, happiness) and neutral utterances produced by male and female speakers of English. Semantically-anomalous pseudo-utterances (e.g., The rivix jolled the silling) conveying each emotion were divided into seven gate intervals according to the number of syllables that listeners heard from sentence onset. Participants (n = 48) judged the emotional meaning of stimuli presented at each gate duration interval, in a successive, blocked presentation format. Analyses looked at how recognition of each emotion evolves as an utterance unfolds and estimated the “identification point” for each emotion. Results showed that anger, sadness, fear, and neutral expressions are recognized more accurately at short gate intervals than happiness, and particularly disgust; however, as speech unfolds, recognition of happiness improves significantly towards the end of the utterance (and fear is recognized more accurately than other emotions). When the gate associated with the emotion identification point of each stimulus was calculated, data indicated that fear (M = 517 ms), sadness (M = 576 ms), and neutral (M = 510 ms) expressions were identified from shorter acoustic events than the other emotions. These data reveal differences in the underlying time course for conscious recognition of basic emotions from vocal expressions, which should be accounted for in studies of emotional speech processing. PMID:22087275

Molecular Recognition Involving Anthraquinone Derivatives and Molecular Clips

Science.gov (United States)

Alaparthi, Madhubabu

In the past, we have demonstrated that 1,8-anthraquinone-18-crown-5 (1) and its heterocyclic derivatives act as luminescent hosts for a variety of cations of environmental and clinical concern. We report here a series of heteroatom-substituted macrocycles containing an anthraquinone moiety as a fluorescent signaling unit and a cyclic polyheteroether chain as the receptor. Sulfur, selenium, and tellurium derivatives of 1,8-anthraquinone-18-crown-5 (1) were synthesized by reacting sodium sulfide (Na2S), sodium selenide (Na2Se) and sodium telluride (Na2Te) with 1,8-bis(2-bromoethylethyleneoxy)anthracene - 9,10-dione in a 1:1 ratio (2,3, and 6). These sensors bind metal ions in a 1:1 ratio (7 and 8), and the optical properties of the new complexes were examined and the sulfur and selenium analogues show that selectivity for Pb(II) is markedly improved as compared to the oxygen analogue 1 which was competitive for Ca(II) ion. Selective reduction of 1 yields secondary alcohols where either one or both of the anthraquinone carbonyl groups has been reduced ( 15 and 9). A new mechanism for the fluorescence detection of metal cations in solution is introduced involving a unique keto-enol tautomerization. Reduction of 1 yields the doubly reduced secondary alcohol, 9. 9 acts as a chemodosimeter for Al(III) ion producing a strong blue emission due to the formation of the anthracene fluorophore, 10, via dehydration of the internal secondary alcohol in DMSO/aqueous solution. The enol form is not the most thermodynamically stable form under these conditions however, and slowly converts to the keto form 11.. Currently we are focusing on cucurbituril derivatives, also described as molecular clips due to their folded geometry used as molecular recognition hosts. We first investigated the synthesis and characterization of aromatic methoxy/catechol terminated cucurbituril units that act as hosts for small solvent molecules, such as CH2Cl2, CH3CN, DMF, and MeOH, through dual pi...H-C T

The thermodynamic signature of ligand binding to histone deacetylase-like amidohydrolases is most sensitive to the flexibility in the L2-loop lining the active site pocket.

Science.gov (United States)

Meyners, Christian; Krämer, Andreas; Yildiz, Özkan; Meyer-Almes, Franz-Josef

2017-07-01

The analysis of the thermodynamic driving forces of ligand-protein binding has been suggested to be a key component for the selection and optimization of active compounds into drug candidates. The binding enthalpy as deduced from isothermal titration calorimetry (ITC) is usually interpreted assuming single-step binding of a ligand to one conformation of the target protein. Although successful in many cases, these assumptions are oversimplified approximations of the reality with flexible proteins and complicated binding mechanism in many if not most cases. The relationship between protein flexibility and thermodynamic signature of ligand binding is largely understudied. Directed mutagenesis, X-ray crystallography, enzyme kinetics and ITC methods were combined to dissect the influence of loop flexibility on the thermodynamics and mechanism of ligand binding to histone deacetylase (HDAC)-like amidohydrolases. The general ligand-protein binding mechanism comprises an energetically demanding gate opening step followed by physical binding. Increased flexibility of the L2-loop in HDAC-like amidohydrolases facilitates access of ligands to the binding pocket resulting in predominantly enthalpy-driven complex formation. The study provides evidence for the great importance of flexibility adjacent to the active site channel for the mechanism and observed thermodynamic driving forces of molecular recognition in HDAC like enzymes. The flexibility or malleability in regions adjacent to binding pockets should be given more attention when designing better drug candidates. The presented case study also suggests that the observed binding enthalpy of protein-ligand systems should be interpreted with caution, since more complicated binding mechanisms may obscure the significance regarding potential drug likeness. Copyright © 2017 Elsevier B.V. All rights reserved.

Structural insight into the recognition of complement C3 activation products by integrin receptors

DEFF Research Database (Denmark)

Bajic, Goran

2015-01-01

fragment C3a called anaphylatoxin. Complement leads to opsonization as the proteolytic fragment C3b becomes covalently linked to the activator surface through a reactive thioester. Self-surfaces are protected by complement regulators, whereas complement activation vividly amplifies on pathogens...... and their clearance by dendritic cells is mediated by αMβ2. The central molecule in my project, αMβ2 integrin, recognizes many diverse ligands including iC3b, but the molecular basis for such recognition was lacking. During my PhD I have obtained a major breakthrough in the dissection of iC3b interaction with αMβ2. I...

Bexarotene ligand pharmaceuticals.

Science.gov (United States)

Hurst, R E

2000-12-01

Bexarotene (LGD-1069), from Ligand, was the first retinoid X receptor (RXR)-selective, antitumor retinoid to enter clinical trials. The company launched the drug for the treatment of cutaneous T-cell lymphoma (CTCL), as Targretin capsules, in the US in January 2000 [359023]. The company filed an NDA for Targretin capsules in June 1999, and for topical gel in December 1999 [329011], [349982] specifically for once-daily oral administration for the treatment of patients with early-stage CTCL who have not tolerated other therapies, patients with refractory or persistent early stage CTCL and patients with refractory advanced stage CTCL. The FDA approved Targretin capsules at the end of December 1999 for once-daily oral treatment of all stages of CTCL in patients refractory to at least one prior systemic therapy, at an initial dose of 300 mg/m2/day. After an NDA was submitted in December 1999 for Targretin gel, the drug received Priority Review status for use as a treatment of cutaneous lesions in patients with stage IA, IB or IIA CTCL [354836]. The FDA issued an approvable letter in June 2000, and granted marketing clearance for CTCL in the same month [370687], [372768], [372769], [373279]. Ligand had received Orphan Drug designation for this indication [329011]. At the request of the FDA, Ligand agreed to carry out certain post-approval phase IV and pharmacokinetic studies [351604]. The company filed an MAA with the EMEA for Targretin Capsules to treat lymphoma in November 1999 [348944]. The NDA for Targretin gel is based on a multicenter phase III trial that was conducted in the US, Canada, Europe and Australia involving 50 patients and a multicenter phase I/II clinical program involving 67 patients. Targretin gel was evaluated for the treatment of patients with early stage CTCL (IA-IIA) who were refractory to, intolerant to, or reached a response plateau for at least 6 months on at least two prior therapies. Efficacy results exceeded the protocol-defined response

Structural coupling of SH2-kinase domains links Fes and Abl substrate recognition and kinase activation.

Science.gov (United States)

Filippakopoulos, Panagis; Kofler, Michael; Hantschel, Oliver; Gish, Gerald D; Grebien, Florian; Salah, Eidarus; Neudecker, Philipp; Kay, Lewis E; Turk, Benjamin E; Superti-Furga, Giulio; Pawson, Tony; Knapp, Stefan

2008-09-05

The SH2 domain of cytoplasmic tyrosine kinases can enhance catalytic activity and substrate recognition, but the molecular mechanisms by which this is achieved are poorly understood. We have solved the structure of the prototypic SH2-kinase unit of the human Fes tyrosine kinase, which appears specialized for positive signaling. In its active conformation, the SH2 domain tightly interacts with the kinase N-terminal lobe and positions the kinase alphaC helix in an active configuration through essential packing and electrostatic interactions. This interaction is stabilized by ligand binding to the SH2 domain. Our data indicate that Fes kinase activation is closely coupled to substrate recognition through cooperative SH2-kinase-substrate interactions. Similarly, we find that the SH2 domain of the active Abl kinase stimulates catalytic activity and substrate phosphorylation through a distinct SH2-kinase interface. Thus, the SH2 and catalytic domains of active Fes and Abl pro-oncogenic kinases form integrated structures essential for effective tyrosine kinase signaling.

Identification of Histamine H3 Receptor Ligands Using a New Crystal Structure Fragment-based Method

DEFF Research Database (Denmark)

Frandsen, Ida Osborn; Boesgaard, Michael W; Fidom, Kimberley

2017-01-01

Virtual screening offers an efficient alternative to high-throughput screening in the identification of pharmacological tools and lead compounds. Virtual screening is typically based on the matching of target structures or ligand pharmacophores to commercial or in-house compound catalogues....... The complete pharmacophore fragment library is freely available through the GPCR database, GPCRdb, allowing the successful application herein to be repeated for most of the 285 class A GPCR targets. The method could also easily be adapted to other protein families....

LASSO-ligand activity by surface similarity order: a new tool for ligand based virtual screening.

Science.gov (United States)

Reid, Darryl; Sadjad, Bashir S; Zsoldos, Zsolt; Simon, Aniko

2008-01-01

Virtual Ligand Screening (VLS) has become an integral part of the drug discovery process for many pharmaceutical companies. Ligand similarity searches provide a very powerful method of screening large databases of ligands to identify possible hits. If these hits belong to new chemotypes the method is deemed even more successful. eHiTS LASSO uses a new interacting surface point types (ISPT) molecular descriptor that is generated from the 3D structure of the ligand, but unlike most 3D descriptors it is conformation independent. Combined with a neural network machine learning technique, LASSO screens molecular databases at an ultra fast speed of 1 million structures in under 1 min on a standard PC. The results obtained from eHiTS LASSO trained on relatively small training sets of just 2, 4 or 8 actives are presented using the diverse directory of useful decoys (DUD) dataset. It is shown that over a wide range of receptor families, eHiTS LASSO is consistently able to enrich screened databases and provides scaffold hopping ability.

LASSO—ligand activity by surface similarity order: a new tool for ligand based virtual screening

Science.gov (United States)

Reid, Darryl; Sadjad, Bashir S.; Zsoldos, Zsolt; Simon, Aniko

2008-06-01

Virtual Ligand Screening (VLS) has become an integral part of the drug discovery process for many pharmaceutical companies. Ligand similarity searches provide a very powerful method of screening large databases of ligands to identify possible hits. If these hits belong to new chemotypes the method is deemed even more successful. eHiTS LASSO uses a new interacting surface point types (ISPT) molecular descriptor that is generated from the 3D structure of the ligand, but unlike most 3D descriptors it is conformation independent. Combined with a neural network machine learning technique, LASSO screens molecular databases at an ultra fast speed of 1 million structures in under 1 min on a standard PC. The results obtained from eHiTS LASSO trained on relatively small training sets of just 2, 4 or 8 actives are presented using the diverse directory of useful decoys (DUD) dataset. It is shown that over a wide range of receptor families, eHiTS LASSO is consistently able to enrich screened databases and provides scaffold hopping ability.

Cognitive penetrability and emotion recognition in human facial expressions

Directory of Open Access Journals (Sweden)

Francesco eMarchi

2015-06-01

Full Text Available Do our background beliefs, desires, and mental images influence our perceptual experience of the emotions of others? In this paper, we will address the possibility of cognitive penetration of perceptual experience in the domain of social cognition. In particular, we focus on emotion recognition based on the visual experience of facial expressions. After introducing the current debate on cognitive penetration, we review examples of perceptual adaptation for facial expressions of emotion. This evidence supports the idea that facial expressions are perceptually processed as wholes. That is, the perceptual system integrates lower-level facial features, such as eyebrow orientation, mouth angle etc., into facial compounds. We then present additional experimental evidence showing that in some cases, emotion recognition on the basis of facial expression is sensitive to and modified by the background knowledge of the subject. We argue that such sensitivity is best explained as a difference in the visual experience of the facial expression, not just as a modification of the judgment based on this experience. The difference in experience is characterized as the result of the interference of background knowledge with the perceptual integration process for faces. Thus, according to the best explanation, we have to accept cognitive penetration in some cases of emotion recognition. Finally, we highlight a recent model of social vision in order to propose a mechanism for cognitive penetration used in the face-based recognition of emotion.

Synthesis and characterization β-ketoamine ligands

Science.gov (United States)

Zaid, Nurzati Amani Mohamed; Hassan, Nur Hasyareeda; Karim, Nurul Huda Abd

2018-04-01

β-ketoamine ligands are important members of heterodonor ligand because of their ease of preparation and modification of both steric and/or electronic effects. Complexes with β-ketoamine has received much less attention and there has been no study about this complex with β-ketoamine in ionic liquid reported. Two type of β-ketoamine ligands which are 4-amino-3-pentene-2-onato (A) and 3-amino-2-butenoic acid methyl ester (B) have been synthesized in this work. The resulting compound formed was characterized using standard spectroscopic and structural techniques which includes 1H and 13C, NMR spectroscopy and FTIR spectroscopy. The 1H and 13C NMR spectrum displayed all the expected signals with correct integration and multiplicity. And it is proved that there are some differences between two ligands as observed in NMR and FTIR spectrum.

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

Science.gov (United States)

Katić, Darko; Julliard, Chantal; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie; Jannin, Pierre; Gibaud, Bernard

2015-09-01

The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial. However, most existing systems do not represent knowledge in a reusable way, hindering also reuse of data. Our purpose is therefore to make our computational models of medical knowledge sharable, extensible and interoperational with established knowledge representations in the form of the LapOntoSPM ontology. To show its usefulness, we apply it to situation interpretation, i.e., the recognition of surgical phases based on surgical activities. Considering best practices in ontology engineering and building on our ontology for laparoscopy, we formalized the workflow of laparoscopic adrenalectomies, cholecystectomies and pancreatic resections in the framework of OntoSPM, a new standard for surgical process models. Furthermore, we provide a rule-based situation interpretation algorithm based on SQWRL to recognize surgical phases using the ontology. The system was evaluated on ground-truth data from 19 manually annotated surgeries. The aim was to show that the phase recognition capabilities are equal to a specialized solution. The recognition rates of the new system were equal to the specialized one. However, the time needed to interpret a situation rose from 0.5 to 1.8 s on average which is still viable for practical application. We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data

Complex adaptive systems ecology

DEFF Research Database (Denmark)

Sommerlund, Julie

2003-01-01

In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies....... They are the result of acooperation between Søren Molin, professor in the group, and his brother, JanMolin, professor at Department of Organization and Industrial Sociology atCopenhagen Business School. The cooperation arises from the recognition that bothmicrobial ecology and sociology/organization theory works...

Designer TGFβ superfamily ligands with diversified functionality.

Directory of Open Access Journals (Sweden)

George P Allendorph

Full Text Available Transforming Growth Factor--beta (TGFβ superfamily ligands, including Activins, Growth and Differentiation Factors (GDFs, and Bone Morphogenetic Proteins (BMPs, are excellent targets for protein-based therapeutics because of their pervasiveness in numerous developmental and cellular processes. We developed a strategy termed RASCH (Random Assembly of Segmental Chimera and Heteromer, to engineer chemically-refoldable TGFβ superfamily ligands with unique signaling properties. One of these engineered ligands, AB208, created from Activin-βA and BMP-2 sequences, exhibits the refolding characteristics of BMP-2 while possessing Activin-like signaling attributes. Further, we find several additional ligands, AB204, AB211, and AB215, which initiate the intracellular Smad1-mediated signaling pathways more strongly than BMP-2 but show no sensitivity to the natural BMP antagonist Noggin unlike natural BMP-2. In another design, incorporation of a short N-terminal segment from BMP-2 was sufficient to enable chemical refolding of BMP-9, without which was never produced nor refolded. Our studies show that the RASCH strategy enables us to expand the functional repertoire of TGFβ superfamily ligands through development of novel chimeric TGFβ ligands with diverse biological and clinical values.

Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms

Directory of Open Access Journals (Sweden)

Sangmin Seo

2018-01-01

Full Text Available We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or similarity of receptors or ligands. The experimental results show that these new features can be effective in predicting GPCR-ligand binding (average area under the curve [AUC] of 0.944, because they are thought to include hidden properties of good ligand-receptor binding. Using the proposed method, we were able to identify novel ligand-GPCR bindings, some of which are supported by several studies.

New pinene-derived pyridines as bidentate chiral ligands

Czech Academy of Sciences Publication Activity Database

Malkov, A. V.; Stewart-Liddon, A.; Teplý, Filip; Kobr, L.; Muir, K. W.; Haigh, D.; Kočovský, P.

2008-01-01

Roč. 64, č. 18 (2008), s. 4011-4025 ISSN 0040-4020 Institutional research plan: CEZ:AV0Z40550506 Keywords : chiral ligands * transition metal catalysis * asymmetric catalysis * pyridine ligands * oxazoline ligands Subject RIV: CC - Organic Chemistry Impact factor: 2.897, year: 2008

Adaptability and selectivity of human peroxisome proliferator-activated receptor (PPAR) pan agonists revealed from crystal structures

International Nuclear Information System (INIS)

Oyama, Takuji; Toyota, Kenji; Waku, Tsuyoshi; Hirakawa, Yuko; Nagasawa, Naoko; Kasuga, Jun-ichi; Hashimoto, Yuichi; Miyachi, Hiroyuki; Morikawa, Kosuke

2009-01-01

The structures of the ligand-binding domains (LBDs) of human peroxisome proliferator-activated receptors (PPARα, PPARγ and PPARδ) in complexes with a pan agonist, an α/δ dual agonist and a PPARδ-specific agonist were determined. The results explain how each ligand is recognized by the PPAR LBDs at an atomic level. Peroxisome proliferator-activated receptors (PPARs) belong to the nuclear hormone receptor family, which is defined as transcriptional factors that are activated by the binding of ligands to their ligand-binding domains (LBDs). Although the three PPAR subtypes display different tissue distribution patterns and distinct pharmacological profiles, they all are essentially related to fatty-acid and glucose metabolism. Since the PPARs share similar three-dimensional structures within the LBDs, synthetic ligands which simultaneously activate two or all of the PPARs could be potent candidates in terms of drugs for the treatment of abnormal metabolic homeostasis. The structures of several PPAR LBDs were determined in complex with synthetic ligands, derivatives of 3-(4-alkoxyphenyl)propanoic acid, which exhibit unique agonistic activities. The PPARα and PPARγ LBDs were complexed with the same pan agonist, TIPP-703, which activates all three PPARs and their crystal structures were determined. The two LBD–ligand complex structures revealed how the pan agonist is adapted to the similar, but significantly different, ligand-binding pockets of the PPARs. The structures of the PPARδ LBD in complex with an α/δ-selective ligand, TIPP-401, and with a related δ-specific ligand, TIPP-204, were also determined. The comparison between the two PPARδ complexes revealed how each ligand exhibits either a ‘dual selective’ or ‘single specific’ binding mode

Re-thinking employee recognition: understanding employee experiences of recognition

OpenAIRE

Smith, Charlotte

2013-01-01

Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...

Molecular Recognition of Corticotropin releasing Factor by Its G protein-coupled Receptor CRFR1

Energy Technology Data Exchange (ETDEWEB)

Pioszak, Augen A.; Parker, Naomi R.; Suino-Powell, Kelly; Xu, H. Eric (Van Andel)

2009-01-15

The bimolecular interaction between corticotropin-releasing factor (CRF), a neuropeptide, and its type 1 receptor (CRFR1), a class B G-protein-coupled receptor (GPCR), is crucial for activation of the hypothalamic-pituitary-adrenal axis in response to stress, and has been a target of intense drug design for the treatment of anxiety, depression, and related disorders. As a class B GPCR, CRFR1 contains an N-terminal extracellular domain (ECD) that provides the primary ligand binding determinants. Here we present three crystal structures of the human CRFR1 ECD, one in a ligand-free form and two in distinct CRF-bound states. The CRFR1 ECD adopts the alpha-beta-betaalpha fold observed for other class B GPCR ECDs, but the N-terminal alpha-helix is significantly shorter and does not contact CRF. CRF adopts a continuous alpha-helix that docks in a hydrophobic surface of the ECD that is distinct from the peptide-binding site of other class B GPCRs, thereby providing a basis for the specificity of ligand recognition between CRFR1 and other class B GPCRs. The binding of CRF is accompanied by clamp-like conformational changes of two loops of the receptor that anchor the CRF C terminus, including the C-terminal amide group. These structural studies provide a molecular framework for understanding peptide binding and specificity by the CRF receptors as well as a template for designing potent and selective CRFR1 antagonists for therapeutic applications.

Recognition of flow in everyday life using sensor agent robot with laser range finder

Science.gov (United States)

Goshima, Misa; Mita, Akira

2011-04-01

In the present paper, we suggest an algorithm for a sensor agent robot with a laser range finder to recognize the flows of residents in the living spaces in order to achieve flow recognition in the living spaces, recognition of the number of people in spaces, and the classification of the flows. House reform is or will be demanded to prolong the lifetime of the home. Adaption for the individuals is needed for our aging society which is growing at a rapid pace. Home autonomous mobile robots will become popular in the future for aged people to assist them in various situations. Therefore we have to collect various type of information of human and living spaces. However, a penetration in personal privacy must be avoided. It is essential to recognize flows in everyday life in order to assist house reforms and aging societies in terms of adaption for the individuals. With background subtraction, extra noise removal, and the clustering based k-means method, we got an average accuracy of more than 90% from the behavior from 1 to 3 persons, and also confirmed the reliability of our system no matter the position of the sensor. Our system can take advantages from autonomous mobile robots and protect the personal privacy. It hints at a generalization of flow recognition methods in the living spaces.

Treatment of autoimmune inflammation by a TLR7 ligand regulating the innate immune system.

Directory of Open Access Journals (Sweden)

Tomoko Hayashi

Full Text Available The Toll-like receptors (TLR have been advocated as attractive therapeutic targets because TLR signaling plays dual roles in initiating adaptive immune responses and perpetuating inflammation. Paradoxically, repeated stimulation of bone marrow mononuclear cells with a synthetic TLR7 ligand 9-benzyl-8-hydroxy-2-(2-methoxyethoxy adenine (called 1V136 leads to subsequent TLR hyporesponsiveness. Further studies on the mechanism of action of this pharmacologic agent demonstrated that the TLR7 ligand treatment depressed dendritic cell activation, but did not directly affect T cell function. To verify this mechanism, we utilized experimental allergic encephalitis (EAE as an in vivo T cell dependent autoimmune model. Drug treated SJL/J mice immunized with proteolipid protein (PLP(139-151 peptide had attenuated disease severity, reduced accumulation of mononuclear cells in the central nervous system (CNS, and limited demyelination, without any apparent systemic toxicity. Splenic T cells from treated mice produced less cytokines upon antigenic rechallenge. In the spinal cords of 1V136-treated EAE mice, the expression of chemoattractants was also reduced, suggesting innate immune cell hyposensitization in the CNS. Indeed, systemic 1V136 did penetrate the CNS. These experiments indicated that repeated doses of a TLR7 ligand may desensitize dendritic cells in lymphoid organs, leading to diminished T cell responses. This treatment strategy might be a new modality to treat T cell mediated autoimmune diseases.

Glucagon-like peptide-1 receptor ligand interactions: structural cross talk between ligands and the extracellular domain.