Detecting Service Chains and Feature Interactions in Sensor-Driven Home Network Services

PubMed Central

Inada, Takuya; Igaki, Hiroshi; Ikegami, Kosuke; Matsumoto, Shinsuke; Nakamura, Masahide; Kusumoto, Shinji

2012-01-01

Sensor-driven services often cause chain reactions, since one service may generate an environmental impact that automatically triggers another service. We first propose a framework that can formalize and detect such service chains based on ECA (event, condition, action) rules. Although the service chain can be a major source of feature interactions, not all service chains lead to harmful interactions. Therefore, we then propose a method that identifies feature interactions within the service chains. Specifically, we characterize the degree of deviation of every service chain by evaluating the gap between expected and actual service states. An experimental evaluation demonstrates that the proposed method successfully detects 11 service chains and 6 feature interactions within 7 practical sensor-driven services. PMID:23012499

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

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

PubMed

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

2014-01-01

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

Eye Tracking and Head Movement Detection: A State-of-Art Survey

PubMed Central

2013-01-01

Eye-gaze detection and tracking have been an active research field in the past years as it adds convenience to a variety of applications. It is considered a significant untraditional method of human computer interaction. Head movement detection has also received researchers' attention and interest as it has been found to be a simple and effective interaction method. Both technologies are considered the easiest alternative interface methods. They serve a wide range of severely disabled people who are left with minimal motor abilities. For both eye tracking and head movement detection, several different approaches have been proposed and used to implement different algorithms for these technologies. Despite the amount of research done on both technologies, researchers are still trying to find robust methods to use effectively in various applications. This paper presents a state-of-art survey for eye tracking and head movement detection methods proposed in the literature. Examples of different fields of applications for both technologies, such as human-computer interaction, driving assistance systems, and assistive technologies are also investigated. PMID:27170851

Interactive-predictive detection of handwritten text blocks

NASA Astrophysics Data System (ADS)

Ramos Terrades, O.; Serrano, N.; Gordó, A.; Valveny, E.; Juan, A.

2010-01-01

A method for text block detection is introduced for old handwritten documents. The proposed method takes advantage of sequential book structure, taking into account layout information from pages previously transcribed. This glance at the past is used to predict the position of text blocks in the current page with the help of conventional layout analysis methods. The method is integrated into the GIDOC prototype: a first attempt to provide integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. Results are given in a transcription task on a 764-page Spanish manuscript from 1891.

Depth detection in interactive projection system based on one-shot black-and-white stripe pattern.

PubMed

Zhou, Qian; Qiao, Xiaorui; Ni, Kai; Li, Xinghui; Wang, Xiaohao

2017-03-06

A novel method enabling estimation of not only the screen surface as the conventional one, but the depth information from two-dimensional coordinates in an interactive projection system was proposed in this research. In this method, a one-shot black-and-white stripe pattern from a projector is projected on a screen plane, where the deformed pattern is captured by a charge-coupled device camera. An algorithm based on object/shadow simultaneous detection is proposed for fulfillment of the correspondence. The depth information of the object is then calculated using the triangulation principle. This technology provides a more direct feeling of virtual interaction in three dimensions without using auxiliary equipment or a special screen as interaction proxies. Simulation and experiments are carried out and the results verified the effectiveness of this method in depth detection.

Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

High throughput detection of antibody self-interaction by bio-layer interferometry.

PubMed

Sun, Tingwan; Reid, Felicia; Liu, Yuqi; Cao, Yuan; Estep, Patricia; Nauman, Claire; Xu, Yingda

2013-01-01

Self-interaction of an antibody may lead to aggregation, low solubility or high viscosity. Rapid identification of highly developable leads remains challenging, even though progress has been made with the introduction of techniques such as self-interaction chromatography (SIC) and cross-interaction chromatography (CIC). Here, we report a high throughput method to detect antibody clone self-interaction (CSI) using bio-layer interferometry (BLI) technology. Antibodies with strong self-interaction responses in the CSI-BLI assay also show delayed retention times in SIC and CIC. This method allows hundreds of candidates to be screened in a matter of hours with minimal material consumption.

Determining dark matter properties with a XENONnT/LZ signal and LHC Run 3 monojet searches

NASA Astrophysics Data System (ADS)

Baum, Sebastian; Catena, Riccardo; Conrad, Jan; Freese, Katherine; Krauss, Martin B.

2018-04-01

We develop a method to forecast the outcome of the LHC Run 3 based on the hypothetical detection of O (100 ) signal events at XENONnT. Our method relies on a systematic classification of renormalizable single-mediator models for dark matter-quark interactions and is valid for dark matter candidates of spin less than or equal to one. Applying our method to simulated data, we find that at the end of the LHC Run 3 only two mutually exclusive scenarios would be compatible with the detection of O (100 ) signal events at XENONnT. In the first scenario, the energy distribution of the signal events is featureless, as for canonical spin-independent interactions. In this case, if a monojet signal is detected at the LHC, dark matter must have spin 1 /2 and interact with nucleons through a unique velocity-dependent operator. If a monojet signal is not detected, dark matter interacts with nucleons through canonical spin-independent interactions. In a second scenario, the spectral distribution of the signal events exhibits a bump at nonzero recoil energies. In this second case, a monojet signal can be detected at the LHC Run 3; dark matter must have spin 1 /2 and interact with nucleons through a unique momentum-dependent operator. We therefore conclude that the observation of O (100 ) signal events at XENONnT combined with the detection, or the lack of detection, of a monojet signal at the LHC Run 3 would significantly narrow the range of possible dark matter-nucleon interactions. As we argued above, it can also provide key information on the dark matter particle spin.

Change Point Detection in Correlation Networks

NASA Astrophysics Data System (ADS)

Barnett, Ian; Onnela, Jukka-Pekka

2016-01-01

Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data.

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

Real-time detection of laser-GaAs interaction process

NASA Astrophysics Data System (ADS)

Jia, Zhichao; Li, Zewen; Lv, Xueming; Ni, Xiaowu

2017-05-01

A real-time method based on laser scattering technology was used to detect the interaction process of GaAs with a 1080 nm laser. The detector collected the scattered laser beam from the GaAs wafer. The main scattering sources were back surface at first, later turn into front surface and vapor, so scattering signal contained much information of the interaction process. The surface morphologies of GaAs with different irradiation times were observed using an optical microscope to confirm occurrence of various phenomena. The proposed method is shown to be effective for the real-time detection of GaAs. By choosing a proper wavelength, the scattering technology can be promoted in detection of thicker GaAs wafer or other materials.

Simple Common Plane contact detection algorithm for FE/FD methods

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

Vorobiev, O

2006-07-19

Common-plane (CP) algorithm is widely used in Discrete Element Method (DEM) to model contact forces between interacting particles or blocks. A new simple contact detection algorithm is proposed to model contacts in FE/FD methods which is similar to the CP algorithm. The CP is defined as a plane separating interacting faces of FE/FD mesh instead of blocks or particles in the original CP method. The method does not require iterations. It is very robust and easy to implement both in 2D and 3D case.

Computational Determination of the Effects of Bacteriophage Bacteriophage Interactions in Human body.

PubMed

Mostafa, Marwa Mostafa; Nassef, Mohammad; Badr, Amr

2017-10-19

Chronic diseases are becoming more serious and widely spreading and this carries a heavy burden on doctors to deal with such patients. Although many of these diseases can be treated by bacteriophages, the situation is significantly dangerous in patients having concomitant more than one chronic disease, where conflicts between phages used in treating these diseases are very closer to happen. This research paper presents a method to detecting the Bacteriophage-Bacteriophage Interaction. This method is implemented based on Domain-Domain Interactions model and it was used to infer Domain-Domain Interactions between the bacteriophages injected in the human body at the same time. By testing the method over bacteriophages that are used to treat tuberculosis, salmonella and virulent E.coli, many interactions have been inferred and detected between these bacteriophages. Several effects were detected for the resulted interactions such as: playing a role in DNA repair such as non-homologous end joining, playing a role in DNA replication, playing a role in the interaction between the immune system and the tumor cells and playing a role in the stiff man syndrome. We revised all patents relating to bacteriophage bacteriophage interactions and phage therapy. The proposed method is developed to help doctors to realize the effect of simultaneously injecting different bacteriophages into the human body to treat different diseases. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

2008-01-01

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969

A Kernel Machine Method for Detecting Effects of Interaction Between Multidimensional Variable Sets: An Imaging Genetics Application

PubMed Central

Ge, Tian; Nichols, Thomas E.; Ghosh, Debashis; Mormino, Elizabeth C.

2015-01-01

Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. PMID:25600633

Current trends in endotoxin detection and analysis of endotoxin-protein interactions.

PubMed

Dullah, Elvina Clarie; Ongkudon, Clarence M

2017-03-01

Endotoxin is a type of pyrogen that can be found in Gram-negative bacteria. Endotoxin can form a stable interaction with other biomolecules thus making its removal difficult especially during the production of biopharmaceutical drugs. The prevention of endotoxins from contaminating biopharmaceutical products is paramount as endotoxin contamination, even in small quantities, can result in fever, inflammation, sepsis, tissue damage and even lead to death. Highly sensitive and accurate detection of endotoxins are keys in the development of biopharmaceutical products derived from Gram-negative bacteria. It will facilitate the study of the intermolecular interaction of an endotoxin with other biomolecules, hence the selection of appropriate endotoxin removal strategies. Currently, most researchers rely on the conventional LAL-based endotoxin detection method. However, new methods have been and are being developed to overcome the problems associated with the LAL-based method. This review paper highlights the current research trends in endotoxin detection from conventional methods to newly developed biosensors. Additionally, it also provides an overview of the use of electron microscopy, dynamic light scattering (DLS), fluorescence resonance energy transfer (FRET) and docking programs in the endotoxin-protein analysis.

Do little interactions get lost in dark random forests?

PubMed

Wright, Marvin N; Ziegler, Andreas; König, Inke R

2016-03-31

Random forests have often been claimed to uncover interaction effects. However, if and how interaction effects can be differentiated from marginal effects remains unclear. In extensive simulation studies, we investigate whether random forest variable importance measures capture or detect gene-gene interactions. With capturing interactions, we define the ability to identify a variable that acts through an interaction with another one, while detection is the ability to identify an interaction effect as such. Of the single importance measures, the Gini importance captured interaction effects in most of the simulated scenarios, however, they were masked by marginal effects in other variables. With the permutation importance, the proportion of captured interactions was lower in all cases. Pairwise importance measures performed about equal, with a slight advantage for the joint variable importance method. However, the overall fraction of detected interactions was low. In almost all scenarios the detection fraction in a model with only marginal effects was larger than in a model with an interaction effect only. Random forests are generally capable of capturing gene-gene interactions, but current variable importance measures are unable to detect them as interactions. In most of the cases, interactions are masked by marginal effects and interactions cannot be differentiated from marginal effects. Consequently, caution is warranted when claiming that random forests uncover interactions.

A kernel machine method for detecting effects of interaction between multidimensional variable sets: an imaging genetics application.

PubMed

Ge, Tian; Nichols, Thomas E; Ghosh, Debashis; Mormino, Elizabeth C; Smoller, Jordan W; Sabuncu, Mert R

2015-04-01

Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of the interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. Copyright © 2015 Elsevier Inc. All rights reserved.

Systems and methods of detecting force and stress using tetrapod nanocrystal

DOEpatents

Choi, Charina L.; Koski, Kristie J.; Sivasankar, Sanjeevi; Alivisatos, A. Paul

2013-08-20

Systems and methods of detecting force on the nanoscale including methods for detecting force using a tetrapod nanocrystal by exposing the tetrapod nanocrystal to light, which produces a luminescent response by the tetrapod nanocrystal. The method continues with detecting a difference in the luminescent response by the tetrapod nanocrystal relative to a base luminescent response that indicates a force between a first and second medium or stresses or strains experienced within a material. Such systems and methods find use with biological systems to measure forces in biological events or interactions.

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Envelope detection using temporal magnetization dynamics of resonantly interacting spin-torque oscillator

NASA Astrophysics Data System (ADS)

Nakamura, Y.; Nishikawa, M.; Osawa, H.; Okamoto, Y.; Kanao, T.; Sato, R.

2018-05-01

In this article, we propose the detection method of the recorded data pattern by the envelope of the temporal magnetization dynamics of resonantly interacting spin-torque oscillator on the microwave assisted magnetic recording for three-dimensional magnetic recording. We simulate the envelope of the waveform from recorded dots with the staggered magnetization configuration, which are calculated by using a micromagnetic simulation. We study the data detection methods for the envelope and propose a soft-output Viterbi algorithm (SOVA) for partial response (PR) system as a signal processing system for three dimensional magnetic recording.

Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.

PubMed

Lee, Jack; Zee, Benny Chung Ying; Li, Qing

2013-01-01

Diabetic retinopathy is a major cause of blindness. Proliferative diabetic retinopathy is a result of severe vascular complication and is visible as neovascularization of the retina. Automatic detection of such new vessels would be useful for the severity grading of diabetic retinopathy, and it is an important part of screening process to identify those who may require immediate treatment for their diabetic retinopathy. We proposed a novel new vessels detection method including statistical texture analysis (STA), high order spectrum analysis (HOS), fractal analysis (FA), and most importantly we have shown that by incorporating their associated interactions the accuracy of new vessels detection can be greatly improved. To assess its performance, the sensitivity, specificity and accuracy (AUC) are obtained. They are 96.3%, 99.1% and 98.5% (99.3%), respectively. It is found that the proposed method can improve the accuracy of new vessels detection significantly over previous methods. The algorithm can be automated and is valuable to detect relatively severe cases of diabetic retinopathy among diabetes patients.

Track-based event recognition in a realistic crowded environment

NASA Astrophysics Data System (ADS)

van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

2014-10-01

Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions.

PubMed

Agarwal, Shashank; Liu, Feifan; Yu, Hong

2011-10-03

Protein-protein interaction (PPI) is an important biomedical phenomenon. Automatically detecting PPI-relevant articles and identifying methods that are used to study PPI are important text mining tasks. In this study, we have explored domain independent features to develop two open source machine learning frameworks. One performs binary classification to determine whether the given article is PPI relevant or not, named "Simple Classifier", and the other one maps the PPI relevant articles with corresponding interaction method nodes in a standardized PSI-MI (Proteomics Standards Initiative-Molecular Interactions) ontology, named "OntoNorm". We evaluated our system in the context of BioCreative challenge competition using the standardized data set. Our systems are amongst the top systems reported by the organizers, attaining 60.8% F1-score for identifying relevant documents, and 52.3% F1-score for mapping articles to interaction method ontology. Our results show that domain-independent machine learning frameworks can perform competitively well at the tasks of detecting PPI relevant articles and identifying the methods that were used to study the interaction in such articles. Simple Classifier is available at http://sourceforge.net/p/simpleclassify/home/ and OntoNorm at http://sourceforge.net/p/ontonorm/home/.

Affinity Pulldown of Biotinylated RNA for Detection of Protein-RNA Complexes.

PubMed

Panda, Amaresh C; Martindale, Jennifer L; Gorospe, Myriam

2016-12-20

RNA-binding proteins (RBPs) have recently emerged as crucial players in the regulation of gene expression. The interactions of RBPs with target mRNAs control the levels of gene products by altering different regulatory steps, including pre-mRNA splicing and maturation, nuclear mRNA export, and mRNA stability and translation (Glisovic et al. , 2008). There are several methodologies available today to identify RNAs bound to specific RBPs; some detect only recombinant molecules in vitro , others detect recombinant and endogenous molecules, while others detect only endogenous molecules. Examples include systematic evolution of ligands by exponential enrichment (SELEX), biotinylated RNA pulldown assay, RNA immunoprecipitation (RIP) assay, electrophoretic mobility shift assay (EMSA), RNA footprinting analysis, and various UV crosslinking and immunoprecipitation (CLIP) methods such as CLIP, PAR-CLIP, and iCLIP (Popova et al. , 2015). Here, we describe a simple and informative method to study and identify the RNA region of interaction between an RBP and its target transcript (Panda et al. , 2014 and 2016). Its reproducibility and ease of use make this protocol a fast and useful method to identify interactions between RBPs and specific RNAs.

rpiCOOL: A tool for In Silico RNA-protein interaction detection using random forest.

PubMed

Akbaripour-Elahabad, Mohammad; Zahiri, Javad; Rafeh, Reza; Eslami, Morteza; Azari, Mahboobeh

2016-08-07

Understanding the principle of RNA-protein interactions (RPIs) is of critical importance to provide insights into post-transcriptional gene regulation and is useful to guide studies about many complex diseases. The limitations and difficulties associated with experimental determination of RPIs, call an urgent need to computational methods for RPI prediction. In this paper, we proposed a machine learning method to detect RNA-protein interactions based on sequence information. We used motif information and repetitive patterns, which have been extracted from experimentally validated RNA-protein interactions, in combination with sequence composition as descriptors to build a model to RPI prediction via a random forest classifier. About 20% of the "sequence motifs" and "nucleotide composition" features have been selected as the informative features with the feature selection methods. These results suggest that these two feature types contribute effectively in RPI detection. Results of 10-fold cross-validation experiments on three non-redundant benchmark datasets show a better performance of the proposed method in comparison with the current state-of-the-art methods in terms of various performance measures. In addition, the results revealed that the accuracy of the RPI prediction methods could vary considerably across different organisms. We have implemented the proposed method, namely rpiCOOL, as a stand-alone tool with a user friendly graphical user interface (GUI) that enables the researchers to predict RNA-protein interaction. The rpiCOOL is freely available at http://biocool.ir/rpicool.html for non-commercial uses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.

PubMed

Huang, Yang; Siwo, Geoffrey; Wuchty, Stefan; Ferdig, Michael T; Przytycka, Teresa M

2012-04-01

It is being increasingly recognized that many important phenotypic traits, including various diseases, are governed by a combination of weak genetic effects and their interactions. While the detection of epistatic interactions that involve a non-additive effect of two loci on a quantitative trait is particularly challenging, this interaction type is fundamental for the understanding of genome organization and gene regulation. However, current methods that detect epistatic interactions typically rely on the existence of a strong primary effect, considerably limiting the sensitivity of the search. To fill this gap, we developed a new method, SEE (Symmetric Epistasis Estimation), allowing the genome-wide detection of epistatic interactions without the need for a strong primary effect. We applied our approach to progeny crosses of the human malaria parasite P. falciparum and S. cerevisiae. We found an abundance of epistatic interactions in the parasite and a much smaller number of such interactions in yeast. The genome of P. falciparum also harboured several epistatic interaction hotspots that putatively play a role in drug resistance mechanisms. The abundance of observed epistatic interactions might suggest a mechanism of compensation for the extremely limited repertoire of transcription factors. Interestingly, epistatic interaction hotspots were associated with elevated levels of linkage disequilibrium, an observation that suggests selection pressure acting on P. falciparum, potentially reflecting host-pathogen interactions or drug-induced selection.

Bimolecular fluorescence complementation: visualization of molecular interactions in living cells.

PubMed

Kerppola, Tom K

2008-01-01

A variety of experimental methods have been developed for the analysis of protein interactions. The majority of these methods either require disruption of the cells to detect molecular interactions or rely on indirect detection of the protein interaction. The bimolecular fluorescence complementation (BiFC) assay provides a direct approach for the visualization of molecular interactions in living cells and organisms. The BiFC approach is based on the facilitated association between two fragments of a fluorescent protein when the fragments are brought together by an interaction between proteins fused to the fragments. The BiFC approach has been used for visualization of interactions among a variety of structurally diverse interaction partners in many different cell types. It enables detection of transient complexes as well as complexes formed by a subpopulation of the interaction partners. It is essential to include negative controls in each experiment in which the interface between the interaction partners has been mutated or deleted. The BiFC assay has been adapted for simultaneous visualization of multiple protein complexes in the same cell and the competition for shared interaction partners. A ubiquitin-mediated fluorescence complementation assay has also been developed for visualization of the covalent modification of proteins by ubiquitin family peptides. These fluorescence complementation assays have a great potential to illuminate a variety of biological interactions in the future.

Electrostatic interaction based approach to thrombin detection by surface-enhanced Raman spectroscopy.

PubMed

Hu, Juan; Zheng, Peng-Cheng; Jiang, Jian-Hui; Shen, Guo-Li; Yu, Ru-Qin; Liu, Guo-Kun

2009-01-01

We have developed an electrostatic interaction based biosensor for thrombin detection using surface-enhanced Raman spectroscopy (SERS). This method utilized the electrostatic interaction between capture (thrombin aptamer) and probe (crystal violet, CV) molecules. The specific interaction between thrombin and aptamer could weaken the electrostatic barrier effect from the negative charged aptamer SAMs to the diffusion process of the positively charged CV from the bulk solution to the Au nanoparticle surface. Therefore, the more the bound thrombin, the more the CV molecules near the Au nanoparticle surface and the stronger the observed Raman signal of CV, provided the Raman detections were set at the same time point for each case. This procedure presented a highly specific selectivity and a linear detection of thrombin in the range from 0.1 nM to 10 nM with a detection limit of about 20 pM and realized the thrombin detection in human blood serum solution directly. The electrostatic interaction based technique provides an easy and fast-responding optical platform for a "signal-on" detection of proteins, which might be applicable for the real time assay of proteins.

[Application of PLA Method for Detection of p53/p63/p73 Complexes in Situ in Tumour Cells and Tumour Tissue].

PubMed

Hrabal, V; Nekulová, M; Nenutil, R; Holčaková, J; Coates, P J; Vojtěšek, B

2017-01-01

PLA (proximity ligation assay) can be used for detection of protein-protein interactions in situ directly in cells and tissues. Due to its high sensitivity and specificity it is useful for detection, localization and quantification of protein complexes with single molecule resolution. One of the mechanisms of mutated p53 gain of function is formation of proten-protein complexes with other members of p53 family - p63 and p73. These interactions influences chemosensitivity and invasivity of cancer cells and this is why these complexes are potential targets of anti-cancer therapy. The aim of this work is to detect p53/p63/p73 interactions in situ in tumour cells and tumour tissue using PLA method. Unique in-house antibodies for specific detection of p63 and p73 isoforms were developed and characterized. Potein complexes were detected using PLA in established cell lines SVK14, HCC1806 and FaDu and in paraffin sections of colorectal carcinoma tissue. Cell lines were also processed to paraffin blocks. p53/T-antigen and ΔNp63/T-antigen protein complexes were detected in SVK14 cells using PLA. Interactions of ΔNp63 and TAp73 isoforms were found in HCC1806 cell line with endogenous expression of these proteins. In FaDu cell line mut-p53/TAp73 complex was localized but not mut-p53/ΔNp63 complex. p53 tetramer was detected directly in colorectal cancer tissue. During development of PLA method for detection of protein complexes between p53 family members we detected interactions of p53 and p63 with T-antigen and mut-p53 and ΔNp63 with TAp73 tumour suppressor in tumour cell lines and p53 tetramers in paraffin sections of colorectal cancer tissue. PLA will be further used for detection of p53/p63, p53/p73 and p63/p73 interactions in tumour tissues and it could be also used for screening of compounds that can block formation of p53/p63/p73 protein complexes.Key words: p53 protein family - protein interaction mapping - immunofluorescence This work was supported by MEYS - NPS I - LO1413. The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 13. 3. 2017Accepted: 26. 3. 2017.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data.

PubMed

Lun, Aaron T L; Smyth, Gordon K

2015-08-19

Chromatin conformation capture with high-throughput sequencing (Hi-C) is a technique that measures the in vivo intensity of interactions between all pairs of loci in the genome. Most conventional analyses of Hi-C data focus on the detection of statistically significant interactions. However, an alternative strategy involves identifying significant changes in the interaction intensity (i.e., differential interactions) between two or more biological conditions. This is more statistically rigorous and may provide more biologically relevant results. Here, we present the diffHic software package for the detection of differential interactions from Hi-C data. diffHic provides methods for read pair alignment and processing, counting into bin pairs, filtering out low-abundance events and normalization of trended or CNV-driven biases. It uses the statistical framework of the edgeR package to model biological variability and to test for significant differences between conditions. Several options for the visualization of results are also included. The use of diffHic is demonstrated with real Hi-C data sets. Performance against existing methods is also evaluated with simulated data. On real data, diffHic is able to successfully detect interactions with significant differences in intensity between biological conditions. It also compares favourably to existing software tools on simulated data sets. These results suggest that diffHic is a viable approach for differential analyses of Hi-C data.

Precisely detecting atomic position of atomic intensity images.

PubMed

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

2015-03-01

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

Surface Plasmon Resonance Label-Free Monitoring of Antibody Antigen Interactions in Real Time

ERIC Educational Resources Information Center

Kausaite, Asta; van Dijk, Martijn; Castrop, Jan; Ramanaviciene, Almira; Baltrus, John P.; Acaite, Juzefa; Ramanavicius, Arunas

2007-01-01

Detection of biologically active compounds is one of the most important topics in molecular biology and biochemistry. One of the most promising detection methods is based on the application of surface plasmon resonance for label-free detection of biologically active compounds. This method allows one to monitor binding events in real time without…

Nanoribbon field-effect transistors as direct and label-free sensors of enzyme-substrate interactions

NASA Astrophysics Data System (ADS)

Mu, Luye; Droujinine, Ilia; Rajan, Nitin; Sawtelle, Sonya; Reed, Mark

2015-03-01

The ability to measure enzyme-substrate interactions is essential in areas such as diagnostics, treatment, and biochemical screens. Many enzymatic reactions alter the pH of its environment, suggesting of a simple and direct method for detection. We show the ability of Al2O3-coated Si nanoribbon field-effect transistor biosensors to sensitively measure various aspects of enzyme-substrate interactions through measuring the pH. Urea in phosphate buffered saline (PBS) and penicillinase in PBS and urine were measured to limits of <200 μM and 0.02 units/mL, respectively. We also show the ability to extract accurate kinetics from the interaction of acetylcholine and its esterase. Prior work on FET sensors has been limited by the use of surface functionalization, which not only alters enzyme-substrate affinity, but also makes enzyme activity quantification difficult. Our method involves direct detection of reactions in solution without requiring alteration to the reactants, allowing us to obtain repeatable results and sensitive limits of detection. This method is a simple, inexpensive, and effective platform for detection of enzymatic reactions, and can be readily generalized to many unrelated classes of reactants. This work was supported in part by U.S. Army Research Office and Air Force Research Laboratory.

An incremental community detection method for social tagging systems using locality-sensitive hashing.

PubMed

Wu, Zhenyu; Zou, Ming

2014-10-01

An increasing number of users interact, collaborate, and share information through social networks. Unprecedented growth in social networks is generating a significant amount of unstructured social data. From such data, distilling communities where users have common interests and tracking variations of users' interests over time are important research tracks in fields such as opinion mining, trend prediction, and personalized services. However, these tasks are extremely difficult considering the highly dynamic characteristics of the data. Existing community detection methods are time consuming, making it difficult to process data in real time. In this paper, dynamic unstructured data is modeled as a stream. Tag assignments stream clustering (TASC), an incremental scalable community detection method, is proposed based on locality-sensitive hashing. Both tags and latent interactions among users are incorporated in the method. In our experiments, the social dynamic behaviors of users are first analyzed. The proposed TASC method is then compared with state-of-the-art clustering methods such as StreamKmeans and incremental k-clique; results indicate that TASC can detect communities more efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gamma-ray tracking method for pet systems

DOEpatents

Mihailescu, Lucian; Vetter, Kai M.

2010-06-08

Gamma-ray tracking methods for use with granular, position sensitive detectors identify the sequence of the interactions taking place in the detector and, hence, the position of the first interaction. The improved position resolution in finding the first interaction in the detection system determines a better definition of the direction of the gamma-ray photon, and hence, a superior source image resolution. A PET system using such a method will have increased efficiency and position resolution.

Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

NASA Technical Reports Server (NTRS)

Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

2010-01-01

This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

Exploration of the metal coordination region of concanavalin A for its interaction with human norovirus.

PubMed

Kim, Duwoon; Lee, Hee-Min; Oh, Kyung-Seo; Ki, Ah Young; Protzman, Rachael A; Kim, Dongkyun; Choi, Jong-Soon; Kim, Min Ji; Kim, Sung Hyun; Vaidya, Bipin; Lee, Seung Jae; Kwon, Joseph

2017-06-01

Rapid methods for the detection and clinical treatment of human norovirus (HuNoV) are needed to control foodborne disease outbreaks, but reliable techniques that are fast and sensitive enough to detect small amounts of HuNoV in food and aquatic environments are not yet available. We explore the interactions between HuNoV and concanavalin A (Con A), which could facilitate the development of a sensitive detection tool for HuNoV. Biophysical studies including hydrogen/deuterium exchange (HDX) mass spectrometry and surface plasmon resonance (SPR) revealed that when the metal coordinated region of Con A, which spans Asp16 to His24, is converted to nine alanine residues (mCon A MCR ), the affinity for HuNoV (GII.4) diminishes, demonstrating that this Ca 2+ and Mn 2+ coordinated region is responsible for the observed virus-protein interaction. The mutated carbohydrate binding region of Con A (mCon A CBR ) does not affect binding affinity significantly, indicating that MCR of Con A is a major region of interaction to HuNoV (GII.4). The results further contribute to the development of a HuNoV concentration tool, Con A-immobilized polyacrylate beads (Con A-PAB), for rapid detection of genotypes from genogroups I and II (GI and GII). This method offers many advantages over currently available methods, including a short concentration time. HuNov (GI and GII) can be detected in just 15 min with 90% recovery through Con A-PAB application. In addition, this method can be used over a wide range of pH values (pH 3.0 - 10.0). Overall, this rapid and sensitive detection of HuNoV (GI and GII) will aid in the prevention of virus transmission pathways, and the method developed here may have applicability for other foodborne viral infections. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid detection and identification of energetic materials with surface enhanced raman spectrometry (SERS)

DOEpatents

Han, Thomas Yong-Jin; Valdez, Carlos A; Olson, Tammy Y; Kim, Sung Ho; Satcher, Jr., Joe H

2015-04-21

In one embodiment, a system includes a plurality of metal nanoparticles functionalized with a plurality of organic molecules tethered thereto, wherein the plurality of organic molecules preferentially interact with one or more analytes when placed in proximity therewith. According to another embodiment, a method for detecting analytes includes contacting a fluid having one or more analytes of interest therein with a plurality of metal nanoparticles, each metal nanoparticle having a plurality of organic molecules tethered thereto, and detecting Raman scattering from an analyte of interest from the fluid, the analyte interacting with one or more of the plurality of organic molecules. In another embodiment, a method includes chemically modifying a plurality of cyclodextrin molecules at a primary hydroxyl moiety to create a chemical handle, and tethering the plurality of cyclodextrin molecules to a metal nanoparticle using the chemical handle. Other systems and methods for detecting analytes are also described.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

Surface plasmon resonance label-free monitoring of antibody antigen interactions in real time

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

Kausaite, A.; van Dijk, M.; Castrop, J.

2007-01-01

Detection of biologically active compounds is one of the most important topics in molecular biology and biochemistry. One of the most promising detection methods is based on the application of surface plasmon resonance for label-free detection of biologically active compounds. This method allows one to monitor binding events in real time without labeling. The system can therefore be used to determine both affinity and rate constants for interactions between various types of molecules. Here, we describe the application of a surface plasmon resonance biosensor for label-free investigation of the interaction between an immobilized antigen bovine serum albumin (BSA) and antibodymore » rabbit anti-cow albumin IgG1 (anti-BSA). The formation of a self-assembled monolayer (SAM) over a gold surface is introduced into this laboratory training protocol as an effective immobilization method, which is very promising in biosensing systems based on detection of affinity interactions. In the next step, covalent attachment via artificially formed amide bonds is applied for the immobilization of proteins on the formed SAM surface. These experiments provide suitable experience for postgraduate students to help them understand immobilization of biologically active materials via SAMs, fundamentals of surface plasmon resonance biosensor applications, and determination of non-covalent biomolecular interactions. The experiment is designed for master and/or Ph.D. students. In some particular cases, this protocol might be adoptable for bachelor students that already have completed an extended biochemistry program that included a background in immunology.« less

Detection and localisation of protein-protein interactions in Saccharomyces cerevisiae using a split-GFP method.

PubMed

Barnard, Emma; McFerran, Neil V; Trudgett, Alan; Nelson, John; Timson, David J

2008-05-01

An alternative method for monitoring protein-protein interactions in Saccharomyces cerevisiae has been developed. It relies on the ability of two fragments of enhanced green fluorescent protein (EGFP) to reassemble and fluoresce when fused to interacting proteins. Since this fluorescence can be detected in living cells, simultaneous detection and localisation of interacting pairs is possible. DNA sequences encoding N- and C-terminal EGFP fragments flanked by sequences from the genes of interest were transformed into S. cerevisiae JPY5 cells and homologous recombination into the genome verified by PCR. The system was evaluated by testing known interacting proteins: labelling of the phosphofructokinase subunits, Pfk1p and Pfk2p, with N- and C-terminal EGFP fragments, respectively, resulted in green fluorescence in the cytoplasm. The system works in other cellular compartments: labelling of Idh1p and Idh2p (mitochondrial matrix), Sdh3p and Sdh4p (mitochondrial membrane) and Pap2p and Mtr4p (nucleus) all resulted in fluorescence in the appropriate cellular compartment.

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

Electrokinetic detection for X-ray spectra of weakly interacting liquids: n-decane and n-nonane.

PubMed

Lam, Royce K; Shih, Orion; Smith, Jacob W; Sheardy, Alex T; Rizzuto, Anthony M; Prendergast, David; Saykally, Richard J

2014-06-21

The introduction of liquid microjets into soft X-ray absorption spectroscopy enabled the windowless study of liquids by this powerful atom-selective high vacuum methodology. However, weakly interacting liquids produce large vapor backgrounds that strongly perturb the liquid signal. Consequently, solvents (e.g., hydrocarbons, ethers, ketones, etc.) and solutions of central importance in chemistry and biology have been inaccessible by this technology. Here we describe a new detection method, upstream detection, which greatly reduces the vapor phase contribution to the X-ray absorption signal while retaining important advantages of liquid microjet sample introduction (e.g., minimal radiation damage). The effectiveness of the upstream detection method is demonstrated in this first study of room temperature liquid hydrocarbons: n-nonane and n-decane. Good agreement with first principles' calculations indicates that the eXcited electron and Core Hole theory adequately describes the subtle interactions in these liquids that perturb the electronic structure of the unoccupied states probed in core-level experiments.

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

PubMed

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

2015-01-01

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

A water-soluble conjugated polymer for protein identification and denaturation detection.

PubMed

Xu, Qingling; Wu, Chunxian; Zhu, Chunlei; Duan, Xinrui; Liu, Libing; Han, Yuchun; Wang, Yilin; Wang, Shu

2010-12-03

Rapid and sensitive methods to detect proteins and protein denaturation have become increasingly needful in the field of proteomics, medical diagnostics, and biology. In this paper, we have reported the synthesis of a new cationic water-soluble conjugated polymer that contains fluorene and diene moieties in the backbone (PFDE) for protein identification by sensing an array of PFDE solutions in different ionic strengths using the linear discriminant analysis technique (LDA). The PFDE can form complexes with proteins by electrostatic and/or hydrophobic interactions and exhibits different fluorescence response. Three main factors contribute to the fluorescence response of PFDE, namely, the net charge density on the protein surface, the hydrophobic nature of the protein, and the metalloprotein characteristics. The denaturation of proteins can also be detected using PFDE as a fluorescent probe. The interactions between PFDE and proteins were also studied by dynamic light scattering (DLS) and isothermal titration microcalorimetry (ITC) techniques. In contrast to other methods based on conjugated polymers, the synthesis of a series of quencher or dye-labeled acceptors or protein substrates has been avoided in our method, which significantly reduces the cost and the synthetic complexity. Our method provides promising applications on protein identification and denaturation detection in a simple, fast, and label-free manner based on non-specific interaction-induced perturbation of PFDE fluorescence response.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

A facile fluorescent "turn-off" method for sensing paraquat based on pyranine-paraquat interaction

NASA Astrophysics Data System (ADS)

Zhao, Zuzhi; Zhang, Fengwei; Zhang, Zipin

2018-06-01

Development of a technically simple yet effective method for paraquat (PQ) detection is of great importance due to its high clinical and environmental relevance. In this study, we developed a pyranine-based fluorescent "turn-off" method for PQ sensing based on pyranine-PQ interaction. We investigated the dependence of analytical performance of this method on the experimental conditions, such as the ion strength, medium pH, and so on. Under the optimized conditions, the method is sensitive and selective, and could be used for PQ detection in real-world sample. This study essentially provides a readily accessible fluorescent system for PQ sensing which is cheap, robust, and technically simple, and it is envisaged to find more interesting clinical and environmental applications.

A General Method for Discovering Inhibitors of Protein–DNA Interactions Using Photonic Crystal Biosensors

PubMed Central

Chan, Leo L.; Pineda, Maria; Heeres, James T.; Hergenrother, Paul J.; Cunningham, Brian T.

2009-01-01

Protein–DNA interactions are essential for fundamental cellular processes such as transcription, DNA damage repair, and apoptosis. As such, small molecule disruptors of these interactions could be powerful tools for investigation of these biological processes, and such compounds would have great potential as therapeutics. Unfortunately, there are few methods available for the rapid identification of compounds that disrupt protein–DNA interactions. Here we show that photonic crystal (PC) technology can be utilized to detect protein–DNA interactions, and can be used in a high-throughput screening mode to identify compounds that prevent protein–DNA binding. The PC technology is used to detect binding between protein–DNA interactions that are DNA-sequence-dependent (the bacterial toxin–antitoxin system MazEF) and those that are DNA-sequence-independent (the human apoptosis inducing factor (AIF)). The PC technology was further utilized in a screen for inhibitors of the AIF–DNA interaction, and through this screen aurin tricarboxylic acid was identified as the first in vitro inhibitor of AIF. The generality and simplicity of the photonic crystal method should enable this technology to find broad utility for identification of compounds that inhibit protein–DNA binding. PMID:18582039

Multilevel depth and image fusion for human activity detection.

PubMed

Ni, Bingbing; Pei, Yong; Moulin, Pierre; Yan, Shuicheng

2013-10-01

Recognizing complex human activities usually requires the detection and modeling of individual visual features and the interactions between them. Current methods only rely on the visual features extracted from 2-D images, and therefore often lead to unreliable salient visual feature detection and inaccurate modeling of the interaction context between individual features. In this paper, we show that these problems can be addressed by combining data from a conventional camera and a depth sensor (e.g., Microsoft Kinect). We propose a novel complex activity recognition and localization framework that effectively fuses information from both grayscale and depth image channels at multiple levels of the video processing pipeline. In the individual visual feature detection level, depth-based filters are applied to the detected human/object rectangles to remove false detections. In the next level of interaction modeling, 3-D spatial and temporal contexts among human subjects or objects are extracted by integrating information from both grayscale and depth images. Depth information is also utilized to distinguish different types of indoor scenes. Finally, a latent structural model is developed to integrate the information from multiple levels of video processing for an activity detection. Extensive experiments on two activity recognition benchmarks (one with depth information) and a challenging grayscale + depth human activity database that contains complex interactions between human-human, human-object, and human-surroundings demonstrate the effectiveness of the proposed multilevel grayscale + depth fusion scheme. Higher recognition and localization accuracies are obtained relative to the previous methods.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores.

PubMed

Ghosh, Sourav K; Ostanin, Victor P; Johnson, Christian L; Lowe, Christopher R; Seshia, Ashwin A

2011-11-15

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks. Copyright © 2011 Elsevier B.V. All rights reserved.

Method for detection of nuclear-plasma interactions in a 134Xe-doped exploding pusher at the National Ignition Facility

DOE PAGES

Bleuel, Daniel L.; Bernstein, Lee A.; Brand, Christopher A.; ...

2016-06-10

Angular momentum changes due to nuclear-plasma interactions on highly-excited nuclei in high energy density plasmas created at the National Ignition Facility can be measured through a change in isomer feeding following gamma emission. Here, we propose an experiment to detect these effects in 133Xe* in exploding pusher capsules.

Method for detection of nuclear-plasma interactions in a 134Xe-doped exploding pusher at the National Ignition Facility

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

Bleuel, Daniel L.; Bernstein, Lee A.; Brand, Christopher A.

Angular momentum changes due to nuclear-plasma interactions on highly-excited nuclei in high energy density plasmas created at the National Ignition Facility can be measured through a change in isomer feeding following gamma emission. Here, we propose an experiment to detect these effects in 133Xe* in exploding pusher capsules.

Spectral study of interaction between chondroitin sulfate and nanoparticles and its application in quantitative analysis

NASA Astrophysics Data System (ADS)

Ma, Yi; Wei, Maojie; Zhang, Xiao; Zhao, Ting; Liu, Xiumei; Zhou, Guanglian

2016-01-01

In this work, the interaction between chondroitin sulfate (CS) and gold nanoparticles (GNPs) and silver nanoparticles (SNPs) was characterized for the first time. Plasma resonance scattering (PRS) and plasma resonance absorption (PRA) were used to investigate the characteristics of their spectrum. The results suggested that the CS with negative charge could interact with metal nanoparticles with negative charge and the adsorption of CS on the surface of SNPs was more regular than that of GNPs. The resonance scattering spectra also further confirmed the interaction between CS and SNPs. A new method for detection of CS based on the interaction was developed. CS concentrations in the range of 0.02-3.5 μg/mL were proportional to the decreases of absorbance of SNPs. Compared with other reported methods, the proposed method is simple and workable without complex process, high consumption and expensive equipments. The developed method was applied to the determination of the CS contents from different biological origins and the results were compared with those obtained by the method of Chinese Pharmacopeia. The effects of matrix in plasma and other glycosaminoglycans on the determination of CS were also investigated. The results showed that a small quantity of blood plasma had no effect on the determination of CS and when the concentration ratio of CS to heparin was more than 10:1, the influence of heparin on the detection of CS could be ignored. This work gave a specific research direction for the detection of CS in the presence of metal nanoparticles.

EINVis: a visualization tool for analyzing and exploring genetic interactions in large-scale association studies.

PubMed

Wu, Yubao; Zhu, Xiaofeng; Chen, Jian; Zhang, Xiang

2013-11-01

Epistasis (gene-gene interaction) detection in large-scale genetic association studies has recently drawn extensive research interests as many complex traits are likely caused by the joint effect of multiple genetic factors. The large number of possible interactions poses both statistical and computational challenges. A variety of approaches have been developed to address the analytical challenges in epistatic interaction detection. These methods usually output the identified genetic interactions and store them in flat file formats. It is highly desirable to develop an effective visualization tool to further investigate the detected interactions and unravel hidden interaction patterns. We have developed EINVis, a novel visualization tool that is specifically designed to analyze and explore genetic interactions. EINVis displays interactions among genetic markers as a network. It utilizes a circular layout (specially, a tree ring view) to simultaneously visualize the hierarchical interactions between single nucleotide polymorphisms (SNPs), genes, and chromosomes, and the network structure formed by these interactions. Using EINVis, the user can distinguish marginal effects from interactions, track interactions involving more than two markers, visualize interactions at different levels, and detect proxy SNPs based on linkage disequilibrium. EINVis is an effective and user-friendly free visualization tool for analyzing and exploring genetic interactions. It is publicly available with detailed documentation and online tutorial on the web at http://filer.case.edu/yxw407/einvis/. © 2013 WILEY PERIODICALS, INC.

AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.

PubMed

Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y

2018-06-07

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.

Detecting signals of drug–drug interactions in a spontaneous reports database

PubMed Central

Thakrar, Bharat T; Grundschober, Sabine Borel; Doessegger, Lucette

2007-01-01

Aims The spontaneous reports database is widely used for detecting signals of ADRs. We have extended the methodology to include the detection of signals of ADRs that are associated with drug–drug interactions (DDI). In particular, we have investigated two different statistical assumptions for detecting signals of DDI. Methods Using the FDA's spontaneous reports database, we investigated two models, a multiplicative and an additive model, to detect signals of DDI. We applied the models to four known DDIs (methotrexate-diclofenac and bone marrow depression, simvastatin-ciclosporin and myopathy, ketoconazole-terfenadine and torsades de pointes, and cisapride-erythromycin and torsades de pointes) and to four drug-event combinations where there is currently no evidence of a DDI (fexofenadine-ketoconazole and torsades de pointes, methotrexade-rofecoxib and bone marrow depression, fluvastatin-ciclosporin and myopathy, and cisapride-azithromycine and torsade de pointes) and estimated the measure of interaction on the two scales. Results The additive model correctly identified all four known DDIs by giving a statistically significant (P< 0.05) positive measure of interaction. The multiplicative model identified the first two of the known DDIs as having a statistically significant or borderline significant (P< 0.1) positive measure of interaction term, gave a nonsignificant positive trend for the third interaction (P= 0.27), and a negative trend for the last interaction. Both models correctly identified the four known non interactions by estimating a negative measure of interaction. Conclusions The spontaneous reports database is a valuable resource for detecting signals of DDIs. In particular, the additive model is more sensitive in detecting such signals. The multiplicative model may further help qualify the strength of the signal detected by the additive model. PMID:17506784

Summarizing techniques that combine three non-parametric scores to detect disease-associated 2-way SNP-SNP interactions.

PubMed

Sengupta Chattopadhyay, Amrita; Hsiao, Ching-Lin; Chang, Chien Ching; Lian, Ie-Bin; Fann, Cathy S J

2014-01-01

Identifying susceptibility genes that influence complex diseases is extremely difficult because loci often influence the disease state through genetic interactions. Numerous approaches to detect disease-associated SNP-SNP interactions have been developed, but none consistently generates high-quality results under different disease scenarios. Using summarizing techniques to combine a number of existing methods may provide a solution to this problem. Here we used three popular non-parametric methods-Gini, absolute probability difference (APD), and entropy-to develop two novel summary scores, namely principle component score (PCS) and Z-sum score (ZSS), with which to predict disease-associated genetic interactions. We used a simulation study to compare performance of the non-parametric scores, the summary scores, the scaled-sum score (SSS; used in polymorphism interaction analysis (PIA)), and the multifactor dimensionality reduction (MDR). The non-parametric methods achieved high power, but no non-parametric method outperformed all others under a variety of epistatic scenarios. PCS and ZSS, however, outperformed MDR. PCS, ZSS and SSS displayed controlled type-I-errors (<0.05) compared to GS, APDS, ES (>0.05). A real data study using the genetic-analysis-workshop 16 (GAW 16) rheumatoid arthritis dataset identified a number of interesting SNP-SNP interactions. © 2013 Elsevier B.V. All rights reserved.

Method and apparatus for detecting neutrons

DOEpatents

Perkins, R.W.; Reeder, P.L.; Wogman, N.A.; Warner, R.A.; Brite, D.W.; Richey, W.C.; Goldman, D.S.

1997-10-21

The instant invention is a method for making and using an apparatus for detecting neutrons. Scintillating optical fibers are fabricated by melting SiO{sub 2} with a thermal neutron capturing substance and a scintillating material in a reducing atmosphere. The melt is then drawn into fibers in an anoxic atmosphere. The fibers may then be coated and used directly in a neutron detection apparatus, or assembled into a geometrical array in a second, hydrogen-rich, scintillating material such as a polymer. Photons generated by interaction with thermal neutrons are trapped within the coated fibers and are directed to photoelectric converters. A measurable electronic signal is generated for each thermal neutron interaction within the fiber. These electronic signals are then manipulated, stored, and interpreted by normal methods to infer the quality and quantity of incident radiation. When the fibers are arranged in an array within a second scintillating material, photons generated by kinetic neutrons interacting with the second scintillating material and photons generated by thermal neutron capture within the fiber can both be directed to photoelectric converters. These electronic signals are then manipulated, stored, and interpreted by normal methods to infer the quality and quantity of incident radiation. 5 figs.

Method and apparatus for detecting neutrons

DOEpatents

Perkins, Richard W.; Reeder, Paul L.; Wogman, Ned A.; Warner, Ray A.; Brite, Daniel W.; Richey, Wayne C.; Goldman, Don S.

1997-01-01

The instant invention is a method for making and using an apparatus for detecting neutrons. Scintillating optical fibers are fabricated by melting SiO.sub.2 with a thermal neutron capturing substance and a scintillating material in a reducing atmosphere. The melt is then drawn into fibers in an anoxic atmosphere. The fibers may then be coated and used directly in a neutron detection apparatus, or assembled into a geometrical array in a second, hydrogen-rich, scintillating material such as a polymer. Photons generated by interaction with thermal neutrons are trapped within the coated fibers and are directed to photoelectric converters. A measurable electronic signal is generated for each thermal neutron interaction within the fiber. These electronic signals are then manipulated, stored, and interpreted by normal methods to infer the quality and quantity of incident radiation. When the fibers are arranged in an array within a second scintillating material, photons generated by kinetic neutrons interacting with the second scintillating material and photons generated by thermal neutron capture within the fiber can both be directed to photoelectric converters. These electronic signals are then manipulated, stored, and interpreted by normal methods to infer the quality and quantity of incident radiation.

EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units

PubMed Central

Kam-Thong, Tony; Czamara, Darina; Tsuda, Koji; Borgwardt, Karsten; Lewis, Cathryn M; Erhardt-Lehmann, Angelika; Hemmer, Bernhard; Rieckmann, Peter; Daake, Markus; Weber, Frank; Wolf, Christiane; Ziegler, Andreas; Pütz, Benno; Holsboer, Florian; Schölkopf, Bernhard; Müller-Myhsok, Bertram

2011-01-01

Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case–control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair. PMID:21150885

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Studying generalised dark matter interactions with extended halo-independent methods

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

Kahlhoefer, Felix; Wild, Sebastian

2016-10-20

The interpretation of dark matter direct detection experiments is complicated by the fact that neither the astrophysical distribution of dark matter nor the properties of its particle physics interactions with nuclei are known in detail. To address both of these issues in a very general way we develop a new framework that combines the full formalism of non-relativistic effective interactions with state-of-the-art halo-independent methods. This approach makes it possible to analyse direct detection experiments for arbitrary dark matter interactions and quantify the goodness-of-fit independent of astrophysical uncertainties. We employ this method in order to demonstrate that the degeneracy between astrophysicalmore » uncertainties and particle physics unknowns is not complete. Certain models can be distinguished in a halo-independent way using a single ton-scale experiment based on liquid xenon, while other models are indistinguishable with a single experiment but can be separated using combined information from several target elements.« less

A novel method to calibrate DOI function of a PET detector with a dual-ended-scintillator readout.

PubMed

Shao, Yiping; Yao, Rutao; Ma, Tianyu

2008-12-01

The detection of depth-of-interaction (DOI) is a critical detector capability to improve the PET spatial resolution uniformity across the field-of-view and will significantly enhance, in particular, small bore system performance for brain, breast, and small animal imaging. One promising technique of DOI detection is to use dual-ended-scintillator readout that uses two photon sensors to detect scintillation light from both ends of a scintillator array and estimate DOI based on the ratio of signals (similar to Anger logic). This approach needs a careful DOI function calibration to establish accurate relationship between DOI and signal ratios, and to recalibrate if the detection condition is shifted due to the drift of sensor gain, bias variations, or degraded optical coupling, etc. However, the current calibration method that uses coincident events to locate interaction positions inside a single scintillator crystal has severe drawbacks, such as complicated setup, long and repetitive measurements, and being prone to errors from various possible misalignments among the source and detector components. This method is also not practically suitable to calibrate multiple DOI functions of a crystal array. To solve these problems, a new method has been developed that requires only a uniform flood source to irradiate a crystal array without the need to locate the interaction positions, and calculates DOI functions based solely on the uniform probability distribution of interactions over DOI positions without knowledge or assumption of detector responses. Simulation and experiment have been studied to validate the new method, and the results show that the new method, with a simple setup and one single measurement, can provide consistent and accurate DOI functions for the entire array of multiple scintillator crystals. This will enable an accurate, simple, and practical DOI function calibration for the PET detectors based on the design of dual-ended-scintillator readout. In addition, the new method can be generally applied to calibrating other types of detectors that use the similar dual-ended readout to acquire the radiation interaction position.

An automated method for finding molecular complexes in large protein interaction networks

PubMed Central

Bader, Gary D; Hogue, Christopher WV

2003-01-01

Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from . PMID:12525261

Detecting population-environmental interactions with mismatched time series data.

PubMed

Ferguson, Jake M; Reichert, Brian E; Fletcher, Robert J; Jager, Henriëtte I

2017-11-01

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has been little work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida's southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population-environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates. © 2017 by the Ecological Society of America.

Detecting population–environmental interactions with mismatched time series data

PubMed Central

Ferguson, Jake M.; Reichert, Brian E.; Fletcher, Robert J.; Jager, Henriëtte I.

2017-01-01

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has been little work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida’s southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population–environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates. PMID:28759123

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664

Detecting protein-protein interactions using Renilla luciferase fusion proteins.

PubMed

Burbelo, Peter D; Kisailus, Adam E; Peck, Jeremy W

2002-11-01

We have developed a novel system designated the luciferase assay for protein detection (LAPD) to study protein-protein interactions. This method involves two protein fusions, a soluble reporter fusion and a fusion for immobilizing the target protein. The soluble reporter is an N-terminal Renilla luciferase fusion protein that exhibits high Renilla luciferase activity. Crude cleared lysates from transfected Cos1 cells that express the Renilla luciferase fusion protein can be used in binding assays with immobilized target proteins. Following incubation and washing, target-bound Renilla luciferase fusion proteins produce light from the coelenterazine substrate, indicating an interaction between the two proteins of interest. As proof of the principle, we reproduced known, transient protein-protein interactions between the Cdc42 GTPase and its effector proteins. GTPase Renilla fusion proteins produced in Cos1 cells were tested with immobilized recombinant GST-N-WASP and CEP5 effector proteins. Using this assay, we could detect specific interactions of Cdc42 with these effector proteins in approximately 50 min. The specificity of these interactions was demonstrated by showing that they were GTPase-specific and GTP-dependent and not seen with other unrelated target proteins. These results suggest that the LAPD method, which is both rapid and sensitive, may have research and practical applications.

Detecting drug-drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and non-steroidal anti-inflammatory drugs.

PubMed

van Puijenbroek, E P; Egberts, A C; Heerdink, E R; Leufkens, H G

2000-12-01

Drug-drug interactions are relatively rarely reported to spontaneous reporting systems (SRSs) for adverse drug reactions. For this reason, the traditional approach for analysing SRS has major limitations for the detection of drug-drug interactions. We developed a method that may enable signalling of these possible interactions, which are often not explicitly reported, utilising reports of adverse drug reactions in data sets of SRS. As an example, the influence of concomitant use of diuretics and non-steroidal anti-inflammatory drugs (NSAIDs) on symptoms indicating a decreased efficacy of diuretics was examined using reports received by the Netherlands Pharmacovigilance Foundation Lareb. Reports received between 1 January 1990 and 1 January 1999 of patients older than 50 years were included in the study. Cases were defined as reports with symptoms indicating a decreased efficacy of diuretics, non-cases as all other reports. Exposure categories were the use of NSAIDs or diuretics versus the use of neither of these drugs. The influence of the combined use of both drugs was examined using logistic regression analysis. The odds ratio of the statistical interaction term of the combined use of both drugs was increased [adjusted odds ratio 2.0, 95% confidence interval (CI) 1.1-3.7], which may indicate an enhanced effect of concomitant drug use. The findings illustrate that spontaneous reporting systems have a potential for signal detection and the analysis of possible drug-drug interactions. The method described may enable a more active approach in the detection of drug-drug interactions after marketing.

Adaptation of Tri-molecular fluorescence complementation allows assaying of regulatory Csr RNA-protein interactions in bacteria.

PubMed

Gelderman, Grant; Sivakumar, Anusha; Lipp, Sarah; Contreras, Lydia

2015-02-01

sRNAs play a significant role in controlling and regulating cellular metabolism. One of the more interesting aspects of certain sRNAs is their ability to make global changes in the cell by interacting with regulatory proteins. In this work, we demonstrate the use of an in vivo Tri-molecular Fluorescence Complementation assay to detect and visualize the central regulatory sRNA-protein interaction of the Carbon Storage Regulatory system in E. coli. The Carbon Storage Regulator consists primarily of an RNA binding protein, CsrA, that alters the activity of mRNA targets and of an sRNA, CsrB, that modulates the activity of CsrA. We describe the construction of a fluorescence complementation system that detects the interactions between CsrB and CsrA. Additionally, we demonstrate that the intensity of the fluorescence of this system is able to detect changes in the affinity of the CsrB-CsrA interaction, as caused by mutations in the protein sequence of CsrA. While previous methods have adopted this technique to study mRNA or RNA localization, this is the first attempt to use this technique to study the sRNA-protein interaction directly in bacteria. This method presents a potentially powerful tool to study complex bacterial RNA protein interactions in vivo. © 2014 Wiley Periodicals, Inc.

Detection of plum pox potyviral protein-protein interactions in planta using an optimized mRFP-based bimolecular fluorescence complementation system.

PubMed

Zilian, Eva; Maiss, Edgar

2011-12-01

In previous studies, protein interaction maps of different potyviruses have been generated using yeast two-hybrid (YTH) systems, and these maps have demonstrated a high diversity of interactions of potyviral proteins. Using an optimized bimolecular fluorescence complementation (BiFC) system, a complete interaction matrix for proteins of a potyvirus was developed for the first time under in planta conditions with ten proteins from plum pox virus (PPV). In total, 52 of 100 possible interactions were detected, including the self-interactions of CI, 6K2, VPg, NIa-Pro, NIb and CP, which is more interactions than have ever been detected for any other potyvirus in a YTH approach. Moreover, the BiFC system was shown to be able to localize the protein interactions, which was typified for the protein self-interactions indicated above. Additionally, experiments were carried out with the P3N-PIPO protein, revealing an interaction with CI but not with CP and supporting the involvement of P3N-PIPO in the cell-to-cell movement of potyviruses. No self-interaction of the PPV helper component-proteinase (HC-Pro) was detected using BiFC in planta. Therefore, additional experiments with turnip mosaic virus (TuMV) HC-Pro, PPV_HC-Pro and their mutants were conducted. The self-interaction of TuMV_HCpro, as recently demonstrated, and the self-interaction of the TuMV_ and PPV_HC-Pro mutants were shown by BiFC in planta, indicating that HC-Pro self-interactions may be species-specific. BiFC is a very useful and reliable method for the detection and localization of protein interactions in planta, thus enabling investigations under more natural conditions than studies in yeast cells.

DNase I enzyme-aided fluorescence signal amplification based on graphene oxide-DNA aptamer interactions for colorectal cancer exosome detection.

PubMed

Wang, Hui; Chen, Hui; Huang, Zhipeng; Li, Tengda; Deng, Anmei; Kong, Jilie

2018-07-01

Exosomes have proved to be an effective cancer biomarker with significant potential, and several cell-specific molecules have been found in colorectal cancer (CRC) exosomes. Nevertheless, it is challenging to use exosomes in clinical lab diagnostics due to their nanoscale and the lack of a convenient and effective detection platform. Here, we developed a DNase I enzyme-aided fluorescence amplification method for CRC exosome detection, based on graphene oxide (GO)-DNA aptamer (CD63 and EpCAM aptamers) interactions. The fluorescence of fluorophore-labeled aptamers quenched by GO, recovered after incubation with samples containing CRC exosomes. The DNase I enzyme digested the single-stranded DNA aptamers on the exosome surface and the exosomes were able to interact with more fluorescent aptamer probes, resulting in an increase of signal amplification. The limit of detection for CRC exosomes is 2.1 × 10 4 particles/μl. Consequently, a rapid and effective method with high sensitivity was established. The method was verified in 19 clinical blood serum samples to distinguish healthy and CRC patients, showing significant diagnostic power. Moreover, it can be expanded to other kinds of cancer exosomes, in addition to CRC. Copyright © 2018 Elsevier B.V. All rights reserved.

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Quantum dot-fluorescence in situ hybridisation for Ectromelia virus detection based on biotin-streptavidin interactions.

PubMed

Wang, Ting; Zheng, Zhenhua; Zhang, Xian-En; Wang, Hanzhong

2016-09-01

Ectromelia virus (ECTV) is an pathogen that can lead to a lethal, acute toxic disease known as mousepox in mice. Prevention and control of ECTV infection requires the establishment of a rapid and sensitive diagnostic system for detecting the virus. In the present study, we developed a method of quantum-dot-fluorescence based in situ hybridisation for detecting ECTV genome DNA. Using biotin-dUTP to replace dTTP, biotin was incorporated into a DNA probe during polymerase chain reaction. High sensitivity and specificity of ECTV DNA detection were displayed by fluorescent quantum dots based on biotin-streptavidin interactions. ECTV DNA was then detected by streptavidin-conjugated quantum dots that bound the biotin-labelled probe. Results indicated that the established method can visualise ECTV genomic DNA in both infected cells and mouse tissues. To our knowledge, this is the first study reporting quantum-dot-fluorescence based in situ hybridisation for the detection of viral nucleic acids, providing a reference for the identification and detection of other viruses. Copyright © 2016. Published by Elsevier B.V.

Nuclear technologies for explosives detection

NASA Astrophysics Data System (ADS)

Bell, Curtis J.

1992-12-01

This paper presents an exploration of several techniques for detection of Improvised Explosive Devices (IED) using interactions of specific nuclei with gammarays or fast neutrons. Techniques considered use these interactions to identify the device by measuring the densities and/or relative concentrations of the elemental constituents of explosives. These techniques are to be compared with selected other nuclear and non-nuclear methods. Combining of nuclear and non-nuclear techniques will also be briefly discussed.

Evaluation of Pseudo-Haptic Interactions with Soft Objects in Virtual Environments.

PubMed

Li, Min; Sareh, Sina; Xu, Guanghua; Ridzuan, Maisarah Binti; Luo, Shan; Xie, Jun; Wurdemann, Helge; Althoefer, Kaspar

2016-01-01

This paper proposes a pseudo-haptic feedback method conveying simulated soft surface stiffness information through a visual interface. The method exploits a combination of two feedback techniques, namely visual feedback of soft surface deformation and control of the indenter avatar speed, to convey stiffness information of a simulated surface of a soft object in virtual environments. The proposed method was effective in distinguishing different sizes of virtual hard nodules integrated into the simulated soft bodies. To further improve the interactive experience, the approach was extended creating a multi-point pseudo-haptic feedback system. A comparison with regards to (a) nodule detection sensitivity and (b) elapsed time as performance indicators in hard nodule detection experiments to a tablet computer incorporating vibration feedback was conducted. The multi-point pseudo-haptic interaction is shown to be more time-efficient than the single-point pseudo-haptic interaction. It is noted that multi-point pseudo-haptic feedback performs similarly well when compared to a vibration-based feedback method based on both performance measures elapsed time and nodule detection sensitivity. This proves that the proposed method can be used to convey detailed haptic information for virtual environmental tasks, even subtle ones, using either a computer mouse or a pressure sensitive device as an input device. This pseudo-haptic feedback method provides an opportunity for low-cost simulation of objects with soft surfaces and hard inclusions, as, for example, occurring in ever more realistic video games with increasing emphasis on interaction with the physical environment and minimally invasive surgery in the form of soft tissue organs with embedded cancer nodules. Hence, the method can be used in many low-budget applications where haptic sensation is required, such as surgeon training or video games, either using desktop computers or portable devices, showing reasonably high fidelity in conveying stiffness perception to the user.

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

PubMed

Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid

2014-01-01

Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

PubMed Central

Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang

2017-01-01

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338

Magnetic force microscopy method and apparatus to detect and image currents in integrated circuits

DOEpatents

Campbell, Ann. N.; Anderson, Richard E.; Cole, Jr., Edward I.

1995-01-01

A magnetic force microscopy method and improved magnetic tip for detecting and quantifying internal magnetic fields resulting from current of integrated circuits. Detection of the current is used for failure analysis, design verification, and model validation. The interaction of the current on the integrated chip with a magnetic field can be detected using a cantilevered magnetic tip. Enhanced sensitivity for both ac and dc current and voltage detection is achieved with voltage by an ac coupling or a heterodyne technique. The techniques can be used to extract information from analog circuits.

Magnetic force microscopy method and apparatus to detect and image currents in integrated circuits

DOEpatents

Campbell, A.N.; Anderson, R.E.; Cole, E.I. Jr.

1995-11-07

A magnetic force microscopy method and improved magnetic tip for detecting and quantifying internal magnetic fields resulting from current of integrated circuits are disclosed. Detection of the current is used for failure analysis, design verification, and model validation. The interaction of the current on the integrated chip with a magnetic field can be detected using a cantilevered magnetic tip. Enhanced sensitivity for both ac and dc current and voltage detection is achieved with voltage by an ac coupling or a heterodyne technique. The techniques can be used to extract information from analog circuits. 17 figs.

Evaluation of a Bead-Free Coimmunoprecipitation Technique for Identification of Virus-Host Protein Interactions Using High-Resolution Mass Spectrometry.

PubMed

DeBlasio, Stacy L; Bereman, Michael S; Mahoney, Jaclyn; Thannhauser, Theodore W; Gray, Stewart M; MacCoss, Michael J; Cilia Heck, Michelle

2017-09-01

Protein interactions between virus and host are essential for viral propagation and movement, as viruses lack most of the proteins required to thrive on their own. Precision methods aimed at disrupting virus-host interactions represent new approaches to disease management but require in-depth knowledge of the identity and binding specificity of host proteins within these interaction networks. Protein coimmunoprecipitation (co-IP) coupled with mass spectrometry (MS) provides a high-throughput way to characterize virus-host interactomes in a single experiment. Common co-IP methods use antibodies immobilized on agarose or magnetic beads to isolate virus-host complexes in solutions of host tissue homogenate. Although these workflows are well established, they can be fairly laborious and expensive. Therefore, we evaluated the feasibility of using antibody-coated microtiter plates coupled with MS analysis as an easy, less expensive way to identify host proteins that interact with Potato leafroll virus (PLRV), an insect-borne RNA virus that infects potatoes. With the use of the bead-free platform, we were able to detect 36 plant and 1 nonstructural viral protein significantly coimmunoprecipitating with PLRV. Two of these proteins, a 14-3-3 signal transduction protein and malate dehydrogenase 2 (mMDH2), were detected as having a weakened or lost association with a structural mutant of the virus, demonstrating that the bead-free method is sensitive enough to detect quantitative differences that can be used to pin-point domains of interaction. Collectively, our analysis shows that the bead-free platform is a low-cost alternative that can be used by core facilities and other investigators to identify plant and viral proteins interacting with virions and/or the viral structural proteins.

A Novel Tactile Sensor with Electromagnetic Induction and Its Application on Stick-Slip Interaction Detection

PubMed Central

Liu, Yanjie; Han, Haijun; Liu, Tao; Yi, Jingang; Li, Qingguo; Inoue, Yoshio

2016-01-01

Real-time detection of contact states, such as stick-slip interaction between a robot and an object on its end effector, is crucial for the robot to grasp and manipulate the object steadily. This paper presents a novel tactile sensor based on electromagnetic induction and its application on stick-slip interaction. An equivalent cantilever-beam model of the tactile sensor was built and capable of constructing the relationship between the sensor output and the friction applied on the sensor. With the tactile sensor, a new method to detect stick-slip interaction on the contact surface between the object and the sensor is proposed based on the characteristics of friction change. Furthermore, a prototype was developed for a typical application, stable wafer transferring on a wafer transfer robot, by considering the spatial magnetic field distribution and the sensor size according to the requirements of wafer transfer. The experimental results validate the sensing mechanism of the tactile sensor and verify its feasibility of detecting stick-slip on the contact surface between the wafer and the sensor. The sensing mechanism also provides a new approach to detect the contact state on the soft-rigid surface in other robot-environment interaction systems. PMID:27023545

Optical sensing: recognition elements and devices

NASA Astrophysics Data System (ADS)

Gauglitz, Guenter G.

2012-09-01

The requirements in chemical and biochemical sensing with respect to recognition elements, avoiding non-specific interactions, and high loading of the surface for detection of low concentrations as well as optimized detection systems are discussed. Among the many detection principles the optical techniques are classified. Methods using labeled compounds like Total Internal Reflection Fluorescence (TIRF) and direct optical methods like micro reflectometry or refractometry are discussed in comparison. Reflectometric Interference Spectroscopy (RIfS) is presented as a robust simple method for biosensing. As applications, trace analysis of endocrine disruptors in water, hormones in food, detection of viruses and bacteria in food and clinical diagnostics are discussed.

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

NASA Astrophysics Data System (ADS)

Chen, Huabo; Tu, Yaqing; Luo, Ting

1998-08-01

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

Prediction of physical protein protein interactions

NASA Astrophysics Data System (ADS)

Szilágyi, András; Grimm, Vera; Arakaki, Adrián K.; Skolnick, Jeffrey

2005-06-01

Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.

Optimization of o-phtaldialdehyde/2-mercaptoethanol postcolumn reaction for the hydrophilic interaction liquid chromatography determination of memantine utilizing a silica hydride stationary phase.

PubMed

Douša, Michal; Pivoňková, Veronika; Sýkora, David

2016-08-01

A rapid procedure for the determination of memantine based on hydrophilic interaction chromatography with fluorescence detection was developed. Fluorescence detection after postcolumn derivatization with o-phtaldialdehyde/2-mercaptoethanol was performed at excitation and emission wavelengths of 345 and 450 nm, respectively. The postcolumn reaction conditions such as reaction temperature, derivatization reagent flow rate, and reagents concentration were studied due to steric hindrance of amino group of memantine. The derivatization reaction was applied for the hydrophilic interaction liquid chromatography method which was based on Cogent Silica-C stationary phase with a mobile phase consisting of a mixture of 10 mmol/L citric acid and 10 mmol/L o-phosphoric acid (pH 6.0) with acetonitrile using an isocratic composition of 2:8 v/v. The benefit of the reported approach consists in a simple sample pretreatment and a quick and sensitive hydrophilic interaction chromatography method. The developed method was validated in terms of linearity, accuracy, precision, and selectivity according to the International Conference on Harmonisation guidelines. The developed method was successfully applied for the analysis of commercial memantine tablets. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bioluminescence Resonance Energy Transfer System for Measuring Dynamic Protein-Protein Interactions in Bacteria

PubMed Central

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong

2014-01-01

ABSTRACT Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. PMID:24846380

Quantitative real-time PCR as a sensitive protein-protein interaction quantification method and a partial solution for non-accessible autoactivator and false-negative molecule analysis in the yeast two-hybrid system.

PubMed

Maier, Richard H; Maier, Christina J; Hintner, Helmut; Bauer, Johann W; Onder, Kamil

2012-12-01

Many functional proteomic experiments make use of high-throughput technologies such as mass spectrometry combined with two-dimensional polyacrylamide gel electrophoresis and the yeast two-hybrid (Y2H) system. Currently there are even automated versions of the Y2H system available that can be used for proteome-wide research. The Y2H system has the capacity to deliver a profusion of Y2H positive colonies from a single library screen. However, subsequent analysis of these numerous primary candidates with complementary methods can be overwhelming. Therefore, a method to select the most promising candidates with strong interaction properties might be useful to reduce the number of candidates requiring further analysis. The method described here offers a new way of quantifying and rating the performance of positive Y2H candidates. The novelty lies in the detection and measurement of mRNA expression instead of proteins or conventional Y2H genetic reporters. This method correlates well with the direct genetic reporter readouts usually used in the Y2H system, and has greater sensitivity for detecting and quantifying protein-protein interactions (PPIs) than the conventional Y2H system, as demonstrated by detection of the Y2H false-negative PPI of RXR/PPARG. Approximately 20% of all proteins are not suitable for the Y2H system, the so-called autoactivators. A further advantage of this method is the possibility to evaluate molecules that usually cannot be analyzed in the Y2H system, exemplified by a VDR-LXXLL motif peptide interaction. Copyright © 2012 Elsevier Inc. All rights reserved.

Impact of Missing Data on the Detection of Differential Item Functioning: The Case of Mantel-Haenszel and Logistic Regression Analysis

ERIC Educational Resources Information Center

Robitzsch, Alexander; Rupp, Andre A.

2009-01-01

This article describes the results of a simulation study to investigate the impact of missing data on the detection of differential item functioning (DIF). Specifically, it investigates how four methods for dealing with missing data (listwise deletion, zero imputation, two-way imputation, response function imputation) interact with two methods of…

Multi-Harmony: detecting functional specificity from sequence alignment

PubMed Central

Brandt, Bernd W.; Feenstra, K. Anton; Heringa, Jaap

2010-01-01

Many protein families contain sub-families with functional specialization, such as binding different ligands or being involved in different protein–protein interactions. A small number of amino acids generally determine functional specificity. The identification of these residues can aid the understanding of protein function and help finding targets for experimental analysis. Here, we present multi-Harmony, an interactive web sever for detecting sub-type-specific sites in proteins starting from a multiple sequence alignment. Combining our Sequence Harmony (SH) and multi-Relief (mR) methods in one web server allows simultaneous analysis and comparison of specificity residues; furthermore, both methods have been significantly improved and extended. SH has been extended to cope with more than two sub-groups. mR has been changed from a sampling implementation to a deterministic one, making it more consistent and user friendly. For both methods Z-scores are reported. The multi-Harmony web server produces a dynamic output page, which includes interactive connections to the Jalview and Jmol applets, thereby allowing interactive analysis of the results. Multi-Harmony is available at http://www.ibi.vu.nl/ programs/shmrwww. PMID:20525785

An in vivo imaging-based assay for detecting protein interactions over a wide range of binding affinities

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

Fowlkes, Jason Davidson; Owens, Elizabeth T; Standaert, Robert F

2009-01-01

Identifying and characterizing protein interactions are fundamental steps towards understanding and modeling biological networks. Methods that detect protein interactions in intact cells rather than buffered solutions are likely more relevant to natural systems since molecular crowding events in the cytosol can influence the diffusion and reactivity of individual proteins. One in vivo, imaging-based method relies on the co-localization of two proteins of interest fused to DivIVA, a cell division protein from Bacillus subtilis, and green fluorescent protein (GFP). We have modified this imaging-based assay to facilitate rapid cloning by constructing new vectors encoding N- and C-terminal DivIVA or GFP molecularmore » tag fusions based on site-specific recombination technology. The sensitivity of the assay was defined using a well-characterized protein interaction system involving the eukaryotic nuclear import receptor subunit, Importin (Imp ) and variant nuclear localization signals (NLS) representing a range of binding affinities. These data demonstrate that the modified co-localization assay is sensitive enough to detect protein interactions with Kd values that span over four orders of magnitude (1nM to 15 M). Lastly, this assay was used to confirm numerous protein interactions identified from mass spectrometry-based analyses of affinity isolates as part of an interactome mapping project in Rhodopseudomonas palustris« less

Detecting Coevolution in Mammalian Sperm–Egg Fusion Proteins

PubMed Central

CLAW, KATRINA G.; GEORGE, RENEE D.; SWANSON, WILLIE J.

2018-01-01

SUMMARY Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm–egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm–egg proteins; interacting sperm–egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm–egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm–egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm–egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm–egg protein pairs. PMID:24644026

Detecting coevolution in mammalian sperm-egg fusion proteins.

PubMed

Claw, Katrina G; George, Renee D; Swanson, Willie J

2014-06-01

Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm-egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm-egg proteins; interacting sperm-egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm-egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm-egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm-egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm-egg protein pairs. © 2014 Wiley Periodicals, Inc.

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

PubMed

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

2016-10-17

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

A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.

PubMed

Moore, Jason H; Gilbert, Joshua C; Tsai, Chia-Ti; Chiang, Fu-Tien; Holden, Todd; Barney, Nate; White, Bill C

2006-07-21

Detecting, characterizing, and interpreting gene-gene interactions or epistasis in studies of human disease susceptibility is both a mathematical and a computational challenge. To address this problem, we have previously developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension (i.e. constructive induction) thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe a comprehensive and flexible framework for detecting and interpreting gene-gene interactions that utilizes advances in information theory for selecting interesting single-nucleotide polymorphisms (SNPs), MDR for constructive induction, machine learning methods for classification, and finally graphical models for interpretation. We illustrate the usefulness of this strategy using artificial datasets simulated from several different two-locus and three-locus epistasis models. We show that the accuracy, sensitivity, specificity, and precision of a naïve Bayes classifier are significantly improved when SNPs are selected based on their information gain (i.e. class entropy removed) and reduced to a single attribute using MDR. We then apply this strategy to detecting, characterizing, and interpreting epistatic models in a genetic study (n = 500) of atrial fibrillation and show that both classification and model interpretation are significantly improved.

Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Nanometer-Sized Diamond Particle as a Probe for Biolabeling

PubMed Central

Chao, Jui-I.; Perevedentseva, Elena; Chung, Pei-Hua; Liu, Kuang-Kai; Cheng, Chih-Yuan; Chang, Chia-Ching; Cheng, Chia-Liang

2007-01-01

A novel method is proposed using nanometer-sized diamond particles as detection probes for biolabeling. The advantages of nanodiamond's unique properties were demonstrated in its biocompatibility, nontoxicity, easily detected Raman signal, and intrinsic fluorescence from its natural defects without complicated pretreatments. Carboxylated nanodiamond's (cND's) penetration ability, noncytotoxicity, and visualization of cND-cell interactions are demonstrated on A549 human lung epithelial cells. Protein-targeted cell interaction visualization was demonstrated with cND-lysozyme complex interaction with bacteria Escherichia coli. It is shown that the developed biomolecule-cND complex preserves the original functions of the test protein. The easily detected natural fluorescent and Raman intrinsic signals, penetration ability, and low cytotoxicity of cNDs render them promising agents in multiple medical applications. PMID:17513352

An autonomous surface discontinuity detection and quantification method by digital image correlation and phase congruency

NASA Astrophysics Data System (ADS)

Cinar, A. F.; Barhli, S. M.; Hollis, D.; Flansbjer, M.; Tomlinson, R. A.; Marrow, T. J.; Mostafavi, M.

2017-09-01

Digital image correlation has been routinely used to measure full-field displacements in many areas of solid mechanics, including fracture mechanics. Accurate segmentation of the crack path is needed to study its interaction with the microstructure and stress fields, and studies of crack behaviour, such as the effect of closure or residual stress in fatigue, require data on its opening displacement. Such information can be obtained from any digital image correlation analysis of cracked components, but it collection by manual methods is quite onerous, particularly for massive amounts of data. We introduce the novel application of Phase Congruency to detect and quantify cracks and their opening. Unlike other crack detection techniques, Phase Congruency does not rely on adjustable threshold values that require user interaction, and so allows large datasets to be treated autonomously. The accuracy of the Phase Congruency based algorithm in detecting cracks is evaluated and compared with conventional methods such as Heaviside function fitting. As Phase Congruency is a displacement-based method, it does not suffer from the noise intensification to which gradient-based methods (e.g. strain thresholding) are susceptible. Its application is demonstrated to experimental data for cracks in quasi-brittle (Granitic rock) and ductile (Aluminium alloy) materials.

Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

PubMed

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

2014-05-20

Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells, thus allowing the detection of protein-protein interactions in live bacterial cells. This BRET system added another useful tool to address important questions in microbiological studies. Copyright © 2014 Cui et al.

Methods of detecting and controlling mucoid Pseudomonas biofilm production

NASA Technical Reports Server (NTRS)

Qiu, Dongru (Inventor); Yu, Hongwei D. (Inventor)

2013-01-01

Compositions and methods for detecting and controlling the conversion to mucoidy in Pseudomonas aeruginosa are disclosed. The present invention provides for detecting the switch from nonmucoid to mucoid state of P. aeruginosa by measuring mucE expression or MucE protein levels. The interaction between MucE and AlgW controls the switch to mucoidy in wild type P. aeruginosa. Also disclosed is an alginate biosynthesis heterologous expression system for use in screening candidate substances that inhibit conversion to mucoidy.

Methods of detecting and controlling mucoid pseudomonas biofilm production

NASA Technical Reports Server (NTRS)

Qiu, Dongru (Inventor); Yu, Hongwei D. (Inventor)

2010-01-01

Compositions and methods for detecting and controlling the conversion to mucoidy in Pseudomonas aeruginosa are disclosed. The present invention provides for detecting the switch from nonmucoid to mucoid state of P. aeruginosa by measuring mucE expression or MucE protein levels. The interaction between MucE and AlgW controls the switch to mucoidy in wild type P. aeruginosa. Also disclosed is an alginate biosynthesis heterologous expression system for use in screening candidate substances that inhibit conversion to mucoidy.

ReliefSeq: A Gene-Wise Adaptive-K Nearest-Neighbor Feature Selection Tool for Finding Gene-Gene Interactions and Main Effects in mRNA-Seq Gene Expression Data

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php. PMID:24339943

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

PubMed

Mifsud, Borbala; Martincorena, Inigo; Darbo, Elodie; Sugar, Robert; Schoenfelder, Stefan; Fraser, Peter; Luscombe, Nicholas M

2017-01-01

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; van Riel, Piet L C M; Coenen, Marieke J H; Scorza, Raffaella

2010-08-06

Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. http://sourceforge.net/projects/sdrproject/.

Dual-model automatic detection of nerve-fibres in corneal confocal microscopy images.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I; Tavakoli, M; Malik, R A

2010-01-01

Corneal Confocal Microscopy (CCM) imaging is a non-invasive surrogate of detecting, quantifying and monitoring diabetic peripheral neuropathy. This paper presents an automated method for detecting nerve-fibres from CCM images using a dual-model detection algorithm and compares the performance to well-established texture and feature detection methods. The algorithm comprises two separate models, one for the background and another for the foreground (nerve-fibres), which work interactively. Our evaluation shows significant improvement (p approximately 0) in both error rate and signal-to-noise ratio of this model over the competitor methods. The automatic method is also evaluated in comparison with manual ground truth analysis in assessing diabetic neuropathy on the basis of nerve-fibre length, and shows a strong correlation (r = 0.92). Both analyses significantly separate diabetic patients from control subjects (p approximately 0).

Face Detection Technique as Interactive Audio/Video Controller for a Mother-Tongue-Based Instructional Material

NASA Astrophysics Data System (ADS)

Guidang, Excel Philip B.; Llanda, Christopher John R.; Palaoag, Thelma D.

2018-03-01

Face Detection Technique as a strategy in controlling a multimedia instructional material was implemented in this study. Specifically, it achieved the following objectives: 1) developed a face detection application that controls an embedded mother-tongue-based instructional material for face-recognition configuration using Python; 2) determined the perceptions of the students using the Mutt Susan’s student app review rubric. The study concludes that face detection technique is effective in controlling an electronic instructional material. It can be used to change the method of interaction of the student with an instructional material. 90% of the students perceived the application to be a great app and 10% rated the application to be good.

Label-free glucose detection using cantilever sensor technology based on gravimetric detection principles.

PubMed

Hsieh, Shuchen; Hsieh, Shu-Ling; Hsieh, Chiung-Wen; Lin, Po-Chiao; Wu, Chun-Hsin

2013-01-01

Efficient maintenance of glucose homeostasis is a major challenge in diabetes therapy, where accurate and reliable glucose level detection is required. Though several methods are currently used, these suffer from impaired response and often unpredictable drift, making them unsuitable for long-term therapeutic practice. In this study, we demonstrate a method that uses a functionalized atomic force microscope (AFM) cantilever as the sensor for reliable glucose detection with sufficient sensitivity and selectivity for clinical use. We first modified the AFM tip with aminopropylsilatrane (APS) and then adsorbed glucose-specific lectin concanavalin A (Con A) onto the surface. The Con A/APS-modified probes were then used to detect glucose by monitoring shifts in the cantilever resonance frequency. To confirm the molecule-specific interaction, AFM topographical images were acquired of identically treated silicon substrates which indicated a specific attachment for glucose-Con A and not for galactose-Con A. These results demonstrate that by monitoring the frequency shift of the AFM cantilever, this sensing system can detect the interaction between Con A and glucose, one of the biomolecule recognition processes, and may assist in the detection and mass quantification of glucose for clinical applications with very high sensitivity.

Information-theoretical noninvasive damage detection in bridge structures

NASA Astrophysics Data System (ADS)

Sudu Ambegedara, Amila; Sun, Jie; Janoyan, Kerop; Bollt, Erik

2016-11-01

Damage detection of mechanical structures such as bridges is an important research problem in civil engineering. Using spatially distributed sensor time series data collected from a recent experiment on a local bridge in Upper State New York, we study noninvasive damage detection using information-theoretical methods. Several findings are in order. First, the time series data, which represent accelerations measured at the sensors, more closely follow Laplace distribution than normal distribution, allowing us to develop parameter estimators for various information-theoretic measures such as entropy and mutual information. Second, as damage is introduced by the removal of bolts of the first diaphragm connection, the interaction between spatially nearby sensors as measured by mutual information becomes weaker, suggesting that the bridge is "loosened." Finally, using a proposed optimal mutual information interaction procedure to prune away indirect interactions, we found that the primary direction of interaction or influence aligns with the traffic direction on the bridge even after damaging the bridge.

[Simple method for precognition of drug interaction between oral iron and phenolic hydroxyl group-containing drugs].

PubMed

Sunagane, Nobuyoshi; Yoshinobu, Etsuko; Murayama, Nobuko; Terawaki, Yasufumi; Kamimura, Naoki; Uruno, Tsutomu

2005-02-01

In the present study, we devised a simple method for detecting the drug interaction between oral iron preparations and phenolic hydroxyl group-containing drugs, using the coloring reaction as indicator, due to the formation of complexes or chelates. In the method, oral iron preparations and test drugs in amounts as much as single dose for adults were added to 10 ml of purified water to make sample suspensions for testing. Thirty minutes after mixing an oral iron suspension and a test drug suspension, the change of color in the mixture was observed macroscopically and graded as 0 to 3, with a marked color change judged as grade 3 and no color change as grade 0. Screening of 14 test drugs commonly used orally was carried out. When using sodium ferrous citrate preparations as oral iron, 5 were classified as grade 3, 2 as grade 2, 4 as grade 1, and 3 as grade 0, respectively. To verify usefulness of the method, the interactions suggested by screening were pharmacokinetically assessed by measuring serum concentrations of the drug in mice. When a levodopa or droxidopa preparation, judged as grade 3 in screening, was concomitantly administered with an iron preparation, a significant reduction in bioavailability of the test drug was observed, indicating possible drug interaction between the test drug and oral iron. Combined administration of an acetaminophen preparation, judged as grade 1, and oral iron preparation showed no influence on the bioavailability of the test drug, implying no detectable interactions between them. In conclusion, the simple method devised in the present study is useful for precognition of drug interactions between oral iron preparations and phenolic hydroxyl group-containing drugs, and the drugs with a higher grade in screening may induce drug interactions with oral iron.

Detection of regional DNA methylation using DNA-graphene affinity interactions.

PubMed

Haque, Md Hakimul; Gopalan, Vinod; Yadav, Sharda; Islam, Md Nazmul; Eftekhari, Ehsan; Li, Qin; Carrascosa, Laura G; Nguyen, Nam-Trung; Lam, Alfred K; Shiddiky, Muhammad J A

2017-01-15

We report a new method for the detection of regional DNA methylation using base-dependent affinity interaction (i.e., adsorption) of DNA with graphene. Due to the strongest adsorption affinity of guanine bases towards graphene, bisulfite-treated guanine-enriched methylated DNA leads to a larger amount of the adsorbed DNA on the graphene-modified electrodes in comparison to the adenine-enriched unmethylated DNA. The level of the methylation is quantified by monitoring the differential pulse voltammetric current as a function of the adsorbed DNA. The assay is sensitive to distinguish methylated and unmethylated DNA sequences at single CpG resolution by differentiating changes in DNA methylation as low as 5%. Furthermore, this method has been used to detect methylation levels in a collection of DNA samples taken from oesophageal cancer tissues. Copyright © 2016 Elsevier B.V. All rights reserved.

Extended maximum likelihood halo-independent analysis of dark matter direct detection data

DOE PAGES

Gelmini, Graciela B.; Georgescu, Andreea; Gondolo, Paolo; ...

2015-11-24

We extend and correct a recently proposed maximum-likelihood halo-independent method to analyze unbinned direct dark matter detection data. Instead of the recoil energy as independent variable we use the minimum speed a dark matter particle must have to impart a given recoil energy to a nucleus. This has the advantage of allowing us to apply the method to any type of target composition and interaction, e.g. with general momentum and velocity dependence, and with elastic or inelastic scattering. We prove the method and provide a rigorous statistical interpretation of the results. As first applications, we find that for dark mattermore » particles with elastic spin-independent interactions and neutron to proton coupling ratio f n/f p=-0.7, the WIMP interpretation of the signal observed by CDMS-II-Si is compatible with the constraints imposed by all other experiments with null results. We also find a similar compatibility for exothermic inelastic spin-independent interactions with f n/f p=-0.8.« less

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

A Simple and Sensitive Method for Auramine O Detection Based on the Binding Interaction with Bovin Serum Albumin.

PubMed

Yan, Jingjing; Huang, Xin; Liu, Shaopu; Yang, Jidong; Yuan, Yusheng; Duan, Ruilin; Zhang, Hui; Hu, Xiaoli

2016-01-01

A simple, rapid and effective method for auramine O (AO) detection was proposed by fluorescence and UV-Vis absorption spectroscopy. In the BR buffer system (pH 7.0), AO had a strong quenching ability to the fluorescence of bovin serum albumin (BSA) by dynamic quenching. In terms of the thermodynamic parameters calculated as ΔH > 0 and ΔS > 0, the resulting binding of BSA and AO was mainly attributed to the hydrophobic interaction forces. The linearity of this method was in the concentration range from 0.16 to 50 μmol L(-1) with a detection limit of 0.05 μmol L(-1). Based on fluorescence resonance energy transfer (FRET), the distance r (1.36 nm) between donor (BSA) and acceptor (AO) was obtained. Furthermore, the effects of foreign substances and ionic strength were evaluated under the optimum reaction conditions. BSA as a selective probe could be applied to the analysis of AO in medicines with satisfactory results.

Development of a nucleotide sugar purification method using a mixed mode column & mass spectrometry detection.

PubMed

Eastwood, Heather; Xia, Fang; Lo, Mei-Chu; Zhou, Jing; Jordan, John B; McCarter, John; Barnhart, Wesley W; Gahm, Kyung-Hyun

2015-11-10

Analysis of nucleotide sugars, nucleoside di- and triphosphates and sugar-phosphates is an essential step in the process of understanding enzymatic pathways. A facile and rapid separation method was developed to analyze these compounds present in an enzymatic reaction mixture utilized to produce nucleotide sugars. The Primesep SB column explored in this study utilizes hydrophobic interactions as well as electrostatic interactions with the phosphoric portion of the nucleotide sugars. Ammonium formate buffer was selected due to its compatibility with mass spectrometry. Negative ion mode mass spectrometry was adopted for detection of the sugar phosphate (fucose-1-phophate), as the compound is not amenable to UV detection. Various mobile phase conditions such as pH, buffer concentration and organic modifier were explored. The semi-preparative separation method was developed to prepare 30mg of the nucleotide sugar. (19)F NMR was utilized to determine purity of the purified fluorinated nucleotide sugar. The collected nucleotide sugar was found to be 99% pure. Published by Elsevier B.V.

Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection

DTIC Science & Technology

2009-06-05

the interaction data sets we determined, via comparisons with strict randomized simulations , the propensity for essential proteins to selectively...and analysis of high- quality PPI data sets. Materials and Methods We analyzed protein interaction networks for yeast and E. coli determined from Y2H...we reinvestigated the centrality-lethality rule, which implies that proteins having more interactions are more likely to be essential. From analysis

Monitoring Ligand-Activated Protein-Protein Interactions Using Bioluminescent Resonance Energy Transfer (BRET) Assay.

PubMed

Coriano, Carlos; Powell, Emily; Xu, Wei

2016-01-01

The bioluminescent resonance energy transfer (BRET) assay has been extensively used in cell-based and in vivo imaging systems for detecting protein-protein interactions in the native environment of living cells. These protein-protein interactions are essential for the functional response of many signaling pathways to environmental chemicals. BRET has been used as a toxicological tool for identifying chemicals that either induce or inhibit these protein-protein interactions. This chapter focuses on describing the toxicological applications of BRET and its optimization as a high-throughput detection system in live cells. Here we review the construction of BRET fusion proteins, describe the BRET methodology, and outline strategies to overcome obstacles that may arise. Furthermore, we describe the advantage of BRET over other resonance energy transfer methods for monitoring protein-protein interactions.

Surface plasmon resonance-based molecular detection of Hb S [beta6(A3)Glu-->Val, GAG-->GTG] at the gene level.

PubMed

Atalay, Erol O; Ustel, Emre; Yildiz, Sanem; Atalay, Ayfer

2006-01-01

The surface plasmon resonance (SPR) approach, being a relatively novel biophysical method, is used to detect many different targets by biomolecular interaction. The SPR system uses optical and evanescent wave phenomenon. This approach does not need any labels, such as enzymes or isotopes, and the monitored interactions are in real time. In DNA-DNA interaction, the SPR approach is Tm-independent. Here we report our preliminary results for the molecular detection of the Hb S (GAG -->GTG) mutation at codon 6 of the human beta-globin gene. Our preliminary results show that the SPR approach could be applied as an inexpensive and fast routine test system for the molecular diagnosis of abnormal hemoglobins (Hbs), especially in premarital screening programs.

Detection of epistatic effects with logic regression and a classical linear regression model.

PubMed

Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

2014-02-01

To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

PubMed Central

Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.

PubMed

Ibrahim, Heba; Saad, Amr; Abdo, Amany; Sharaf Eldin, A

2016-04-01

Pharmacovigilance (PhV) is an important clinical activity with strong implications for population health and clinical research. The main goal of PhV is the timely detection of adverse drug events (ADEs) that are novel in their clinical nature, severity and/or frequency. Drug interactions (DI) pose an important problem in the development of new drugs and post marketing PhV that contribute to 6-30% of all unexpected ADEs. Therefore, the early detection of DI is vital. Spontaneous reporting systems (SRS) have served as the core data collection system for post marketing PhV since the 1960s. The main objective of our study was to particularly identify signals of DI from SRS. In addition, we are presenting an optimized tailored mining algorithm called "hybrid Apriori". The proposed algorithm is based on an optimized and modified association rule mining (ARM) approach. A hybrid Apriori algorithm has been applied to the SRS of the United States Food and Drug Administration's (U.S. FDA) adverse events reporting system (FAERS) in order to extract significant association patterns of drug interaction-adverse event (DIAE). We have assessed the resulting DIAEs qualitatively and quantitatively using two different triage features: a three-element taxonomy and three performance metrics. These features were applied on two random samples of 100 interacting and 100 non-interacting DIAE patterns. Additionally, we have employed logistic regression (LR) statistic method to quantify the magnitude and direction of interactions in order to test for confounding by co-medication in unknown interacting DIAE patterns. Hybrid Apriori extracted 2933 interacting DIAE patterns (including 1256 serious ones) and 530 non-interacting DIAE patterns. Referring to the current knowledge using four different reliable resources of DI, the results showed that the proposed method can extract signals of serious interacting DIAEs. Various association patterns could be identified based on the relationships among the elements which composed a pattern. The average performance of the method showed 85% precision, 80% negative predictive value, 81% sensitivity and 84% specificity. The LR modeling could provide the statistical context to guard against spurious DIAEs. The proposed method could efficiently detect DIAE signals from SRS data as well as, identifying rare adverse drug reactions (ADRs). Copyright © 2016 Elsevier Inc. All rights reserved.

eMethylsorb: electrochemical quantification of DNA methylation at CpG resolution using DNA-gold affinity interactions.

PubMed

Sina, Abu Ali Ibn; Howell, Sidney; Carrascosa, Laura G; Rauf, Sakandar; Shiddiky, Muhammad J A; Trau, Matt

2014-11-07

We report a simple electrochemical method referred to as "eMethylsorb" for the detection of DNA methylation. The method relies on the base dependent affinity interaction of DNA with gold. The methylation status of DNA is quantified by monitoring the electrochemical current as a function of the relative adsorption level of bisulphite treated DNA samples onto a bare gold electrode. This method can successfully distinguish methylated and unmethylated epigenotypes at single CpG resolution.

Quantitation of five organophosphorus nerve agent metabolites in serum using hydrophilic interaction liquid chromatography and tandem mass spectrometry

PubMed Central

Hamelin, Elizabeth I.; Schulze, Nicholas D.; Shaner, Rebecca L.; Coleman, Rebecca M.; Lawrence, Richard J.; Crow, Brian S.; Jakubowski, E. M.; Johnson, Rudolph C.

2015-01-01

Although nerve agent use is prohibited, concerns remain for human exposure to nerve agents during decommissioning, research, and warfare. Exposure can be detected through the analysis of the hydrolysis products in urine as well as blood. An analytical method to detect exposure to five nerve agents, including VX, VR (Russian VX), GB (sarin), GD (soman) and GF (cyclosarin), through the analysis of the hydrolysis products, which are the primary metabolites, in serum has been developed and characterized. This method uses solid phase extraction coupled with high performance liquid chromatography for separation and isotopic dilution tandem mass spectrometry for detection. An uncommon buffer of ammonium fluoride was used to enhance ionization and improve sensitivity when coupled with hydrophilic interaction liquid chromatography resulting in detection limits from 0.3–0.5 ng/mL. The assessment of two quality control samples demonstrated high accuracy (101–105%) and high precision (5–8%) for the detection of these five nerve agent hydrolysis products in serum. PMID:24633507

Microsomal metabolism of calycosin, formononetin and drug-drug interactions by dynamic microdialysis sampling and HPLC-DAD-MS analysis.

PubMed

Wen, Xiao-Dong; Qi, Lian-Wen; Li, Bin; Li, Ping; Yi, Ling; Wang, Ya-Qiong; Liu, E-Hu; Yang, Xiao-Lin

2009-08-15

A dynamic microdialysis sampling method with liquid chromatography-diode array detection and time-of-flight mass spectrometry (LC-DAD-TOF/MS) analysis was developed to investigate rat microsomal metabolisms of calycosin and formononetin, and their drug-drug interactions. Two hydroxylated metabolites from calycosin, and three hydroxylated or 4'-O-demethylated derivatives from formononetin were detected and identified after co-incubation with microsomes. Calibration curves offered linear ranges of two orders of magnitude with r(2)>0.999 for calycosin, formononetin and daidzein. The quantitative LC method provides a range of 0.028-0.034microg/mL for limits of detection, overall precision less than 5% and accuracy less than 3% by RSD. Besides, calycosin and formononetin were found to produce the depressive effect on the CYP450 enzyme reaction, and inhibit phase I enzyme reaction of each other when they are concurrent. Dynamic microdialysis sampling with LC-DAD-TOF/MS analysis developed in this work is a powerful tool for in vitro metabolism studies of drugs and metabolic interactions.

A facile method to screen inhibitors of protein-protein interactions including MDM2-p53 displayed on T7 phage.

PubMed

Ishi, Kazutomo; Sugawara, Fumio

2008-05-01

Protein-protein interactions are essential in many biological processes including cell cycle and apoptosis. It is currently of great medical interest to inhibit specific protein-protein interactions in order to treat a variety of disease states. Here, we describe a facile multiwell plate assay method using T7 phage display to screen for candidate inhibitors of protein-protein interactions. Because T7 phage display is an effective method for detecting protein-protein interactions, we aimed to utilize this technique to screen for small-molecule inhibitors that disrupt these types of interaction. We used the well-characterized interaction between p53 and MDM2 and an inhibitor of this interaction, nutlin 3, as a model system to establish a new screening method. Phage particles displaying p53 interacted with GST-MDM2 immobilized on 96-well plates, and the interaction was inhibited by nutlin 3. Multiwell plate assay was then performed using a natural product library, which identified dehydroaltenusin as a candidate inhibitor of the p53-MDM2 interaction. We discuss the potential applications of this novel T7 phage display methodology, which we propose to call 'reverse phage display'.

A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data.

PubMed

Lee, MinJae; Rahbar, Mohammad H; Talebi, Hooshang

2018-01-01

We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates.

Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs

PubMed Central

White, Cynthia; Mao, Zhiyuan; Savage, Van M.

2016-01-01

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions—ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions. PMID:27278366

A novel method to calibrate DOI function of a PET detector with a dual-ended-scintillator readout

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

Shao Yiping; Yao Rutao; Ma Tianyu

The detection of depth-of-interaction (DOI) is a critical detector capability to improve the PET spatial resolution uniformity across the field-of-view and will significantly enhance, in particular, small bore system performance for brain, breast, and small animal imaging. One promising technique of DOI detection is to use dual-ended-scintillator readout that uses two photon sensors to detect scintillation light from both ends of a scintillator array and estimate DOI based on the ratio of signals (similar to Anger logic). This approach needs a careful DOI function calibration to establish accurate relationship between DOI and signal ratios, and to recalibrate if the detectionmore » condition is shifted due to the drift of sensor gain, bias variations, or degraded optical coupling, etc. However, the current calibration method that uses coincident events to locate interaction positions inside a single scintillator crystal has severe drawbacks, such as complicated setup, long and repetitive measurements, and being prone to errors from various possible misalignments among the source and detector components. This method is also not practically suitable to calibrate multiple DOI functions of a crystal array. To solve these problems, a new method has been developed that requires only a uniform flood source to irradiate a crystal array without the need to locate the interaction positions, and calculates DOI functions based solely on the uniform probability distribution of interactions over DOI positions without knowledge or assumption of detector responses. Simulation and experiment have been studied to validate the new method, and the results show that the new method, with a simple setup and one single measurement, can provide consistent and accurate DOI functions for the entire array of multiple scintillator crystals. This will enable an accurate, simple, and practical DOI function calibration for the PET detectors based on the design of dual-ended-scintillator readout. In addition, the new method can be generally applied to calibrating other types of detectors that use the similar dual-ended readout to acquire the radiation interaction position.« less

Single Molecule Approaches in RNA-Protein Interactions.

PubMed

Serebrov, Victor; Moore, Melissa J

RNA-protein interactions govern every aspect of RNA metabolism, and aberrant RNA-binding proteins are the cause of hundreds of genetic diseases. Quantitative measurements of these interactions are necessary in order to understand mechanisms leading to diseases and to develop efficient therapies. Existing methods of RNA-protein interactome capture can afford a comprehensive snapshot of RNA-protein interaction networks but lack the ability to characterize the dynamics of these interactions. As all ensemble methods, their resolution is also limited by statistical averaging. Here we discuss recent advances in single molecule techniques that have the potential to tackle these challenges. We also provide a thorough overview of single molecule colocalization microscopy and the essential protein and RNA tagging and detection techniques.

A Novel Test for Gene-Ancestry Interactions in Genome-Wide Association Data

PubMed Central

Dunlop, Malcolm G.; Houlston, Richard S.; Tomlinson, Ian P.; Holmes, Chris C.

2012-01-01

Genome-wide association study (GWAS) data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into “ancestry groups” and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions. PMID:23236349

Genome-wide gene–gene interaction analysis for next-generation sequencing

PubMed Central

Zhao, Jinying; Zhu, Yun; Xiong, Momiao

2016-01-01

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study. PMID:26173972

Detection of myo-inositol trispyrophosphate in equine urine and plasma by hydrophillic interaction chromatography-tandem mass spectrometry.

PubMed

Wong, April S Y; Ho, Emmie N M; Wan, Terence S M

2012-05-01

Myo-inositol trispyrophosphate (ITPP) is a new drug capable of increasing the amount of oxygen in hypoxic tissues. Studies have shown that administration of ITPP increases the maximal exercise capacity in normal mice as well as mice with severe heart failure. The properties of ITPP make it an ideal candidate as a doping agent to enhance performance in racehorses. While there have been speculations in the horseracing industry that the covert use of ITPP is already widespread, no reported method exists for the detection of ITPP in equine biological samples. ITPP is a difficult-to-detect drug due to its hydrophilic nature; the complexity of equine biological matrices also adds to the problem. This paper describes for the first time a method for the detection and confirmation of ITPP in equine urine and plasma. ITPP was isolated from the sample matrices by solid-phase extraction and the extract was analyzed by hydrophilic interaction chromatography-tandem mass spectrometry. ITPP could be detected at low ppb levels in both fortified equine plasma and urine with good precision, fast instrumental turnaround time, and negligible matrix interferences. To our knowledge, this is the first report of a validated method for the detection and unequivocal confirmation of low levels of ITPP in any biological fluid. Copyright © 2012 John Wiley & Sons, Ltd.

A novel non-contact radar sensor for affective and interactive analysis.

PubMed

Lin, Hong-Dun; Lee, Yen-Shien; Shih, Hsiang-Lan; Chuang, Bor-Nian

2013-01-01

Currently, many physiological signal sensing techniques have been applied for affective analysis in Human-Computer Interaction applications. Most known maturely developed sensing methods (EEG/ECG/EMG/Temperature/BP etc. al.) replied on contact way to obtain desired physiological information for further data analysis. However, those methods might cause some inconvenient and uncomfortable problems, and not easy to be used for affective analysis in interactive performing. To improve this issue, a novel technology based on low power radar technology (Nanosecond Pulse Near-field Sensing, NPNS) with 300 MHz radio-frequency was proposed to detect humans' pulse signal by the non-contact way for heartbeat signal extraction. In this paper, a modified nonlinear HRV calculated algorithm was also developed and applied on analyzing affective status using extracted Peak-to-Peak Interval (PPI) information from detected pulse signal. The proposed new affective analysis method is designed to continuously collect the humans' physiological signal, and validated in a preliminary experiment with sound, light and motion interactive performance. As a result, the mean bias between PPI (from NPNS) and RRI (from ECG) shows less than 1ms, and the correlation is over than 0.88, respectively.

Detection of Electrophilic and Nucleophilic Chemical Agents

DOEpatents

McElhanon, James R.; Shepodd, Timothy J.

2008-11-11

A "real time" method for detecting electrophilic and nucleophilic species generally by employing tunable, precursor sensor materials that mimic the physiological interaction of these agents to form highly florescent berberine-type alkaloids that can be easily and rapidly detected. These novel precursor sensor materials can be tuned for reaction with both electrophilic (chemical species, toxins) and nucleophilic (proteins and other biological molecules) species.

Offline Impedance Measurements for Detection and Mitigation of Dangerous Implant Interactions: An RF Safety Prescreen

PubMed Central

Ellenor, Christopher W; Stang, Pascal P; Etezadi-Amoli, Maryam; Pauly, John M; Scott, Greig C

2015-01-01

Purpose The concept of a “radiofrequency safety prescreen” is investigated, wherein dangerous interactions between radiofrequency fields used in MRI, and conductive implants in patients are detected through impedance changes in the radiofrequency coil. Theory The behavior of coupled oscillators is reviewed, and the resulting, observable impedance changes are discussed. Methods A birdcage coil is loaded with a static head phantom and a wire phantom with a wire close to its resonant length, the shape, position, and orientation of which can be changed. Interactions are probed with a current sensor and network analyzer. Results Impedance spectra show dramatic, unmistakable splitting in cases of strong coupling, and strong correlation is observed between induced current and scattering parameters. Conclusions The feasibility of a new, low-power prescreening technique has been demonstrated in a simple phantom experiment, which can unambiguously detect resonant interactions between an implanted wire and an imaging coil. A new technique has also been presented which can detect parallel transmit null modes for the wire. Magn Reson Med 73:1328–1339, 2015. © 2014 Wiley Periodicals, Inc. PMID:24623586

An automatic method for detecting sliding railway wheels and hot bearings using thermal imagery.

DOT National Transportation Integrated Search

2016-05-03

One of the most important safety-related tasks in the rail industry is early detection of defective rolling : stock components. Railway wheels and wheel bearings are two components prone to damage due to : their interactions with brakes and railway t...

Procedure for short-lived particle detection in the OPERA experiment and its application to charm decays

NASA Astrophysics Data System (ADS)

Agafonova, N.; Aleksandrov, A.; Anokhina, A.; Aoki, S.; Ariga, A.; Ariga, T.; Bender, D.; Bertolin, A.; Bozza, C.; Brugnera, R.; Buonaura, A.; Buontempo, S.; Büttner, B.; Chernyavsky, M.; Chukanov, A.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; De Serio, M.; Del Amo Sanchez, P.; Di Crescenzo, A.; Di Ferdinando, D.; Di Marco, N.; Dmitrievski, S.; Dracos, M.; Duchesneau, D.; Dusini, S.; Dzhatdoev, T.; Ebert, J.; Ereditato, A.; Fini, R. A.; Fukuda, T.; Galati, G.; Garfagnini, A.; Giacomelli, G.; Göllnitz, C.; Goldberg, J.; Gornushkin, Y.; Grella, G.; Guler, M.; Gustavino, C.; Hagner, C.; Hara, T.; Hollnagel, A.; Hosseini, B.; Ishida, H.; Ishiguro, K.; Jakovcic, K.; Jollet, C.; Kamiscioglu, C.; Kamiscioglu, M.; Kawada, J.; Kim, J. H.; Kim, S. H.; Kitagawa, N.; Klicek, B.; Kodama, K.; Komatsu, M.; Kose, U.; Kreslo, I.; Lauria, A.; Lenkeit, J.; Ljubicic, A.; Longhin, A.; Loverre, P.; Malgin, A.; Malenica, M.; Mandrioli, G.; Matsuo, T.; Matveev, V.; Mauri, N.; Medinaceli, E.; Meregaglia, A.; Mikado, S.; Monacelli, P.; Montesi, M. C.; Morishima, K.; Muciaccia, M. T.; Naganawa, N.; Naka, T.; Nakamura, M.; Nakano, T.; Nakatsuka, Y.; Niwa, K.; Ogawa, S.; Okateva, N.; Olshevsky, A.; Omura, T.; Ozaki, K.; Paoloni, A.; Park, B. D.; Park, I. G.; Pasqualini, L.; Pastore, A.; Patrizii, L.; Pessard, H.; Pistillo, C.; Podgrudkov, D.; Polukhina, N.; Pozzato, M.; Pupilli, F.; Roda, M.; Rokujo, H.; Roganova, T.; Rosa, G.; Ryazhskaya, O.; Sato, O.; Schembri, A.; Shakiryanova, I.; Shchedrina, T.; Sheshukov, A.; Shibuya, H.; Shiraishi, T.; Shoziyoev, G.; Simone, S.; Sioli, M.; Sirignano, C.; Sirri, G.; Spinetti, M.; Stanco, L.; Starkov, N.; Stellacci, S. M.; Stipcevic, M.; Strauss, T.; Strolin, P.; Takahashi, S.; Tenti, M.; Terranova, F.; Tioukov, V.; Tufanli, S.; Vilain, P.; Vladimirov, M.; Votano, L.; Vuilleumier, J. L.; Wilquet, G.; Wonsak, B.; Yoon, C. S.; Zemskova, S.; Zghiche, A.

2014-08-01

The OPERA experiment, designed to perform the first observation of oscillations in appearance mode through the detection of the leptons produced in charged current interactions, has collected data from 2008 to 2012. In the present paper, the procedure developed to detect particle decays, occurring over distances of the order of from the neutrino interaction point, is described in detail and applied to the search for charmed hadrons, showing similar decay topologies as the lepton. In the analysed sample, 50 charm decay candidate events are observed while are expected, proving that the detector performance and the analysis chain applied to neutrino events are well reproduced by the OPERA simulation and thus validating the methods for appearance detection.

Effective Identification of Akt Interacting Proteins by Two-Step Chemical Crosslinking, Co-Immunoprecipitation and Mass Spectrometry

PubMed Central

Huang, Bill X.; Kim, Hee-Yong

2013-01-01

Akt is a critical protein for cell survival and known to interact with various proteins. However, Akt binding partners that modulate or regulate Akt activation have not been fully elucidated. Identification of Akt-interacting proteins has been customarily achieved by co-immunoprecipitation combined with western blot and/or MS analysis. An intrinsic problem of the method is loss of interacting proteins during procedures to remove non-specific proteins. Moreover, antibody contamination often interferes with the detection of less abundant proteins. Here, we developed a novel two-step chemical crosslinking strategy to overcome these problems which resulted in a dramatic improvement in identifying Akt interacting partners. Akt antibody was first immobilized on protein A/G beads using disuccinimidyl suberate and allowed to bind to cellular Akt along with its interacting proteins. Subsequently, dithiobis[succinimidylpropionate], a cleavable crosslinker, was introduced to produce stable complexes between Akt and binding partners prior to the SDS-PAGE and nanoLC-MS/MS analysis. This approach enabled identification of ten Akt partners from cell lysates containing as low as 1.5 mg proteins, including two new potential Akt interacting partners. None of these but one protein was detectable without crosslinking procedures. The present method provides a sensitive and effective tool to probe Akt-interacting proteins. This strategy should also prove useful for other protein interactions, particularly those involving less abundant or weakly associating partners. PMID:23613850

Experimental Methods for Protein Interaction Identification and Characterization

NASA Astrophysics Data System (ADS)

Uetz, Peter; Titz, Björn; Cagney, Gerard

There are dozens of methods for the detection of protein-protein interactions but they fall into a few broad categories. Fragment complementation assays such as the yeast two-hybrid (Y2H) system are based on split proteins that are functionally reconstituted by fusions of interacting proteins. Biophysical methods include structure determination and mass spectrometric (MS) identification of proteins in complexes. Biochemical methods include methods such as far western blotting and peptide arrays. Only the Y2H and protein complex purification combined with MS have been used on a larger scale. Due to the lack of data it is still difficult to compare these methods with respect to their efficiency and error rates. Current data does not favor any particular method and thus multiple experimental approaches are necessary to maximally cover the interactome of any target cell or organism.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

PubMed

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case-Control Study

PubMed Central

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-01-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (GxE) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying GxE interactions which may be partly due to limited statistical power and inaccurately measured exposures. While existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes which may modify this association. PMID:25219575

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.

PubMed

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-11-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (G × E) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying G × E interactions, which may be partly due to limited statistical power and inaccurately measured exposures. Although existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here, we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes that may modify this association. © 2014 Wiley Periodicals, Inc.

To Control False Positives in Gene-Gene Interaction Analysis: Two Novel Conditional Entropy-Based Approaches

PubMed Central

Lin, Meihua; Li, Haoli; Zhao, Xiaolei; Qin, Jiheng

2013-01-01

Genome-wide analysis of gene-gene interactions has been recognized as a powerful avenue to identify the missing genetic components that can not be detected by using current single-point association analysis. Recently, several model-free methods (e.g. the commonly used information based metrics and several logistic regression-based metrics) were developed for detecting non-linear dependence between genetic loci, but they are potentially at the risk of inflated false positive error, in particular when the main effects at one or both loci are salient. In this study, we proposed two conditional entropy-based metrics to challenge this limitation. Extensive simulations demonstrated that the two proposed metrics, provided the disease is rare, could maintain consistently correct false positive rate. In the scenarios for a common disease, our proposed metrics achieved better or comparable control of false positive error, compared to four previously proposed model-free metrics. In terms of power, our methods outperformed several competing metrics in a range of common disease models. Furthermore, in real data analyses, both metrics succeeded in detecting interactions and were competitive with the originally reported results or the logistic regression approaches. In conclusion, the proposed conditional entropy-based metrics are promising as alternatives to current model-based approaches for detecting genuine epistatic effects. PMID:24339984

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

PubMed Central

2010-01-01

Background Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. Results The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the FcγRIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Conclusions Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/ PMID:20691091

An effective system for detecting protein-protein interaction based on in vivo cleavage by PPV NIa protease.

PubMed

Zheng, Nuoyan; Huang, Xiahe; Yin, Bojiao; Wang, Dan; Xie, Qi

2012-12-01

Detection of protein-protein interaction can provide valuable information for investigating the biological function of proteins. The current methods that applied in protein-protein interaction, such as co-immunoprecipitation and pull down etc., often cause plenty of working time due to the burdensome cloning and purification procedures. Here we established a system that characterization of protein-protein interaction was accomplished by co-expression and simply purification of target proteins from one expression cassette within E. coli system. We modified pET vector into co-expression vector pInvivo which encoded PPV NIa protease, two cleavage site F and two multiple cloning sites that flanking cleavage sites. The target proteins (for example: protein A and protein B) were inserted at multiple cloning sites and translated into polyprotein in the order of MBP tag-protein A-site F-PPV NIa protease-site F-protein B-His(6) tag. PPV NIa protease carried out intracellular cleavage along expression, then led to the separation of polyprotein components, therefore, the interaction between protein A-protein B can be detected through one-step purification and analysis. Negative control for protein B was brought into this system for monitoring interaction specificity. We successfully employed this system to prove two cases of reported protien-protein interaction: RHA2a/ANAC and FTA/FTB. In conclusion, a convenient and efficient system has been successfully developed for detecting protein-protein interaction.

Identifying significant gene‐environment interactions using a combination of screening testing and hierarchical false discovery rate control

PubMed Central

Shen, Li; Saykin, Andrew J.; Williams, Scott M.; Moore, Jason H.

2016-01-01

ABSTRACT Although gene‐environment (G× E) interactions play an important role in many biological systems, detecting these interactions within genome‐wide data can be challenging due to the loss in statistical power incurred by multiple hypothesis correction. To address the challenge of poor power and the limitations of existing multistage methods, we recently developed a screening‐testing approach for G× E interaction detection that combines elastic net penalized regression with joint estimation to support a single omnibus test for the presence of G× E interactions. In our original work on this technique, however, we did not assess type I error control or power and evaluated the method using just a single, small bladder cancer data set. In this paper, we extend the original method in two important directions and provide a more rigorous performance evaluation. First, we introduce a hierarchical false discovery rate approach to formally assess the significance of individual G× E interactions. Second, to support the analysis of truly genome‐wide data sets, we incorporate a score statistic‐based prescreening step to reduce the number of single nucleotide polymorphisms prior to fitting the first stage penalized regression model. To assess the statistical properties of our method, we compare the type I error rate and statistical power of our approach with competing techniques using both simple simulation designs as well as designs based on real disease architectures. Finally, we demonstrate the ability of our approach to identify biologically plausible SNP‐education interactions relative to Alzheimer's disease status using genome‐wide association study data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). PMID:27578615

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

Alignment and integration of complex networks by hypergraph-based spectral clustering

NASA Astrophysics Data System (ADS)

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Alignment and integration of complex networks by hypergraph-based spectral clustering.

PubMed

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

PubMed

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information.

PubMed

An, Ji-Yong; Zhang, Lei; Zhou, Yong; Zhao, Yu-Jun; Wang, Da-Fu

2017-08-18

Self-interactions Proteins (SIPs) is important for their biological activity owing to the inherent interaction amongst their secondary structures or domains. However, due to the limitations of experimental Self-interactions detection, one major challenge in the study of prediction SIPs is how to exploit computational approaches for SIPs detection based on evolutionary information contained protein sequence. In the work, we presented a novel computational approach named WELM-LAG, which combined the Weighed-Extreme Learning Machine (WELM) classifier with Local Average Group (LAG) to predict SIPs based on protein sequence. The major improvement of our method lies in presenting an effective feature extraction method used to represent candidate Self-interactions proteins by exploring the evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix (PSSM); and then employing a reliable and robust WELM classifier to carry out classification. In addition, the Principal Component Analysis (PCA) approach is used to reduce the impact of noise. The WELM-LAG method gave very high average accuracies of 92.94 and 96.74% on yeast and human datasets, respectively. Meanwhile, we compared it with the state-of-the-art support vector machine (SVM) classifier and other existing methods on human and yeast datasets, respectively. Comparative results indicated that our approach is very promising and may provide a cost-effective alternative for predicting SIPs. In addition, we developed a freely available web server called WELM-LAG-SIPs to predict SIPs. The web server is available at http://219.219.62.123:8888/WELMLAG/ .

THz frequency spectrum of protein-solvent interaction energy using a recurrence plot-based Wiener-Khinchin method.

PubMed

Karain, Wael

2016-10-01

The dynamics of a protein and the water surrounding it are coupled via nonbonded energy interactions. This coupling can exhibit a complex, nonlinear, and nonstationary nature. The THz frequency spectrum for this interaction energy characterizes both the vibration spectrum of the water hydrogen bond network, and the frequency range of large amplitude modes of proteins. We use a Recurrence Plot based Wiener-Khinchin method RPWK to calculate this spectrum, and the results are compared to those determined using the classical auto-covariance-based Wiener-Khinchin method WK. The frequency spectra for the total nonbonded interaction energy extracted from molecular dynamics simulations between the β-Lactamase Inhibitory Protein BLIP, and water molecules within a 10 Å distance from the protein surface, are calculated at 150, 200, 250, and 310 K, respectively. Similar calculations are also performed for the nonbonded interaction energy between the residues 49ASP, 53TYR, and 142PHE in BLIP, with water molecules within 10 Å from each residue respectively at 150, 200, 250, and 310 K. A comparison of the results shows that RPWK performs better than WK, and is able to detect some frequency data points that WK fails to detect. This points to the importance of using methods capable of taking the complex nature of the protein-solvent energy landscape into consideration, and not to rely on standard linear methods. In general, RPWK can be a valuable addition to the analysis tools for protein molecular dynamics simulations. Proteins 2016; 84:1549-1557. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Quantitative analysis of small molecule-nucleic acid interactions with a biosensor surface and surface plasmon resonance detection.

PubMed

Liu, Yang; Wilson, W David

2010-01-01

Surface plasmon resonance (SPR) technology with biosensor surfaces has become a widely-used tool for the study of nucleic acid interactions without any labeling requirements. The method provides simultaneous kinetic and equilibrium characterization of the interactions of biomolecules as well as small molecule-biopolymer binding. SPR monitors molecular interactions in real time and provides significant advantages over optical or calorimetic methods for systems with strong binding coupled to small spectroscopic signals and/or reaction heats. A detailed and practical guide for nucleic acid interaction analysis using SPR-biosensor methods is presented. Details of the SPR technology and basic fundamentals are described with recommendations on the preparation of the SPR instrument, sensor chips, and samples, as well as extensive information on experimental design, quantitative and qualitative data analysis and presentation. A specific example of the interaction of a minor-groove-binding agent with DNA is evaluated by both kinetic and steady-state SPR methods to illustrate the technique. Since the molecules that bind cooperatively to specific DNA sequences are attractive for many applications, a cooperative small molecule-DNA interaction is also presented.

Detection of J-coupling using atomic magnetometer

DOEpatents

Ledbetter, Micah P.; Crawford, Charles W.; Wemmer, David E.; Pines, Alexander; Knappe, Svenja; Kitching, John; Budker, Dmitry

2015-09-22

An embodiment of a method of detecting a J-coupling includes providing a polarized analyte adjacent to a vapor cell of an atomic magnetometer; and measuring one or more J-coupling parameters using the atomic magnetometer. According to an embodiment, measuring the one or more J-coupling parameters includes detecting a magnetic field created by the polarized analyte as the magnetic field evolves under a J-coupling interaction.

Reversible interactions with para-hydrogen enhance NMR sensitivity by polarization transfer.

PubMed

Adams, Ralph W; Aguilar, Juan A; Atkinson, Kevin D; Cowley, Michael J; Elliott, Paul I P; Duckett, Simon B; Green, Gary G R; Khazal, Iman G; López-Serrano, Joaquín; Williamson, David C

2009-03-27

The sensitivity of both nuclear magnetic resonance spectroscopy and magnetic resonance imaging is very low because the detected signal strength depends on the small population difference between spin states even in high magnetic fields. Hyperpolarization methods can be used to increase this difference and thereby enhance signal strength. This has been achieved previously by incorporating the molecular spin singlet para-hydrogen into hydrogenation reaction products. We show here that a metal complex can facilitate the reversible interaction of para-hydrogen with a suitable organic substrate such that up to an 800-fold increase in proton, carbon, and nitrogen signal strengths are seen for the substrate without its hydrogenation. These polarized signals can be selectively detected when combined with methods that suppress background signals.

New diagnostic methods for laser plasma- and microwave-enhanced combustion

PubMed Central

Miles, Richard B; Michael, James B; Limbach, Christopher M; McGuire, Sean D; Chng, Tat Loon; Edwards, Matthew R; DeLuca, Nicholas J; Shneider, Mikhail N; Dogariu, Arthur

2015-01-01

The study of pulsed laser- and microwave-induced plasma interactions with atmospheric and higher pressure combusting gases requires rapid diagnostic methods that are capable of determining the mechanisms by which these interactions are taking place. New rapid diagnostics are presented here extending the capabilities of Rayleigh and Thomson scattering and resonance-enhanced multi-photon ionization (REMPI) detection and introducing femtosecond laser-induced velocity and temperature profile imaging. Spectrally filtered Rayleigh scattering provides a method for the planar imaging of temperature fields for constant pressure interactions and line imaging of velocity, temperature and density profiles. Depolarization of Rayleigh scattering provides a measure of the dissociation fraction, and multi-wavelength line imaging enables the separation of Thomson scattering from Rayleigh scattering. Radar REMPI takes advantage of high-frequency microwave scattering from the region of laser-selected species ionization to extend REMPI to atmospheric pressures and implement it as a stand-off detection method for atomic and molecular species in combusting environments. Femtosecond laser electronic excitation tagging (FLEET) generates highly excited molecular species and dissociation through the focal zone of the laser. The prompt fluorescence from excited molecular species yields temperature profiles, and the delayed fluorescence from recombining atomic fragments yields velocity profiles. PMID:26170432

Development, validation and application of a hydrophilic interaction liquid chromatography-evaporative light scattering detection based method for process control of hydrolysis of xylans obtained from different agricultural wastes.

PubMed

Li, Fangbing; Wang, Hui; Xin, Huaxia; Cai, Jianfeng; Fu, Qing; Jin, Yu

2016-12-01

Purified standards of xylooligosaccharides (XOSs) (DP2-6) were first prepared from a mixture of XOSs using solid phase extraction (SPE), followed by semi-preparative liquid chromatography both under hydrophilic interaction liquid chromatography (HILIC) modes. Then, an accurate quantitative analysis method based on hydrophilic interaction liquid chromatography-evaporative light scattering detection (HILIC-ELSD) was developed and validated for simultaneous determination of xylose (X1), xylobiose (X2), xylotriose (X3), xylotetraose (X4), xylopentaose (X5), and xylohexaose (X6). This developed HILIC-ELSD method was applied to the comparison of different hydrolysis methods for xylans and assessment of XOSs contents from different agricultural wastes. The result indicated that enzymatic hydrolysis was preferable with fewer by-products and high XOSs yield. The XOSs yield (48.40%) from sugarcane bagasse xylan was the highest, showing conversions of 11.21g X2, 12.75g X3, 4.54g X4, 13.31g X5, and 6.78g X6 from 100g xylan. Copyright © 2016 Elsevier Ltd. All rights reserved.

Semi-automated segmentation of neuroblastoma nuclei using the gradient energy tensor: a user driven approach

NASA Astrophysics Data System (ADS)

Kromp, Florian; Taschner-Mandl, Sabine; Schwarz, Magdalena; Blaha, Johanna; Weiss, Tamara; Ambros, Peter F.; Reiter, Michael

2015-02-01

We propose a user-driven method for the segmentation of neuroblastoma nuclei in microscopic fluorescence images involving the gradient energy tensor. Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization (FISH) signals and nucleus morphology. The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections. Accurate segmentation is difficult due to varying staining intensities and aggregated cells. It requires several (meta-) parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample (or group of similar samples) by user interactions. Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values. With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction. The strategy was validated on handsegmented datasets of three neuroblastoma cell lines.

Bio-nano interactions detected by nanochannel electrophoresis.

PubMed

Luan, Binquan

2016-08-01

Engineered nanoparticles have been widely used in industry and are present in many consumer products. However, their bio-safeties especially in a long term are largely unknown. Here, a nanochannel-electrophoresis-based method is proposed for detecting the potential bio-nano interactions that may further lead to damages to human health and/or biological environment. Through proof-of-concept molecular dynamics simulations, it was demonstrated that the transport of a protein-nanoparticle complex is very different from that of a protein along. By monitoring the change of ionic currents induced by a transported analyte as well as the transport velocities of the analyte, the complex (with bio-nano interaction) can be clearly distinguished from the protein alone (with no interaction with tested nanoparticles). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Immuno-PCR: Achievements and Perspectives.

PubMed

Ryazantsev, D Y; Voronina, D V; Zavriev, S K

2016-12-01

The immuno-PCR (iPCR) method combines advantages of enzyme-linked immunosorbent assay and polymerase chain reaction, which is used in iPCR as a method of "visualization" of antigen-antibody interaction. The use of iPCR provides classical PCR sensitivity to objects traditionally detected by ELISA. This method could be very sensitive and allow for detection of quantities of femtograms/ml order. However, iPCR is still not widely used. The aim of this review is to highlight the special features of the iPCR method and to show the main aspects of its development and application in recent years.

Cross-correlation spin noise spectroscopy of heterogeneous interacting spin systems

DOE PAGES

Roy, Dibyendu; Yang, Luyi; Crooker, Scott A.; ...

2015-04-30

Interacting multi-component spin systems are ubiquitous in nature and in the laboratory. As such, investigations of inter-species spin interactions are of vital importance. Traditionally, they are studied by experimental methods that are necessarily perturbative: e.g., by intentionally polarizing or depolarizing one spin species while detecting the response of the other(s). Here, we describe and demonstrate an alternative approach based on multi-probe spin noise spectroscopy, which can reveal inter-species spin interactions - under conditions of strict thermal equilibrium - by detecting and cross-correlating the stochastic fluctuation signals exhibited by each of the constituent spin species. Specifically, we consider a two-component spinmore » ensemble that interacts via exchange coupling, and we determine cross-correlations between their intrinsic spin fluctuations. The model is experimentally confirmed using “two-color” optical spin noise spectroscopy on a mixture of interacting Rb and Cs vapors. Noise correlations directly reveal the presence of inter-species spin exchange, without ever perturbing the system away from thermal equilibrium. These non-invasive and noise-based techniques should be generally applicable to any heterogeneous spin system in which the fluctuations of the constituent components are detectable.« less

Colorimetric determination of Timolol concentration based on localized surface plasmon resonance of silver nanoparticles

NASA Astrophysics Data System (ADS)

Amirjani, Amirmostafa; Bagheri, Mozhgan; Heydari, Mojgan; Hesaraki, Saeed

2016-09-01

In this work, a rapid and simple colorimetric method based on the surface plasmon resonance of silver nanoparticles (AgNPs) was developed for the detection of the drug Timolol. The method used is based on the interaction of Timolol with the surface of the as-synthesized AgNPs, which promotes aggregation of the nanoparticles. This aggregation exploits the surface plasmon resonance through the electric dipole-dipole interaction and coupling among the agglomerated particles, hence bringing forth distinctive changes in the spectra as well as the color of colloidal silver. UV-vis spectrophotometery was used to monitor the changes of the localized surface plasmon resonance of AgNPs at wavelengths of 400 and 550 nm. The developed colorimetric sensor has a wide dynamic range of 1.0 × 10-7 M-1.0 × 10-3 M for detection of Timolol with a low detection limit of 1.2 × 10-6 M. The proposed method was successfully applied for the determination of Timolol concentration in ophthalmic eye-drop solution with a response time lower than 40 s.

Optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate.

PubMed

Song, Qi; Wu, Xiaodong; Liu, Yunlong; Smith, Mark; Buatti, John; Sonka, Milan

2009-01-01

We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic approach. Hard surface interacting constraints are enforced in the interacting regions, preserving the geometric relationship of those partially interacting surfaces. The soft smoothness a priori shape compliance is introduced into the energy functional to provide shape guidance. The globally optimal surfaces can be simultaneously achieved by solving a maximum flow problem based on an arc-weighted graph representation. Representing the segmentation problem in an arc-weighted graph, one can incorporate a wider spectrum of constraints into the formulation, thus increasing segmentation accuracy and robustness in volumetric image data. To the best of our knowledge, our method is the first attempt to introduce the arc-weighted graph representation into the graph-searching approach for simultaneous segmentation of multiple partially interacting objects, which admits a globally optimal solution in a low-order polynomial time. Our new approach was applied to the simultaneous surface detection of bladder and prostate. The result was quite encouraging in spite of the low saliency of the bladder and prostate in CT images.

A sensitive and selective resonance Rayleigh scattering method for quick detection of avidin using affinity labeling Au nanoparticles

NASA Astrophysics Data System (ADS)

Wang, Qi; Huang, Xi; Fu, Xuan; Deng, Huan; Ma, Meihu; Cai, Zhaoxia

2016-06-01

Avidin is a glycoprotein with antinutritional property, which should be limited in daily food. We developed an affinity biosensor system based on resonance Rayleigh scattering (RRS) and using affinity biotin labeling Au nanoparticles (AuNPs). This method was selective and sensitive for quick avidin detection due to the avidin-biotin affinitive interaction. Under optimal conditions, RRS intensity of biotin-AuNPs increase linearly with an increasing concentration of avidin from 5 to 160 ng/mL. The lower limit of detection was 0.59 ng/mL. This rapid and selective avidin detection method was used in synthetic samples and egg products with recoveries of between 102.97 and 107.92%, thereby demonstrating the feasible and practical application of this assay.

Epistasis-list.org: A Curated Database of Gene-Gene and Gene-Environment Interactions in Human Epidemiology

EPA Science Inventory

The field of human genetics has experienced a paradigm shift in that common diseases are now thought to be due to the complex interactions among numerous genetic and environmental factors. This paradigm shift has prompted the development of myriad novel methods to detect such int...

DiffSLc: A graph centrality method to detect essential proteins of a protein-protein interaction network

USDA-ARS?s Scientific Manuscript database

Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures have been helpful in identifying critical genes and proteins in biomolecular networks. The proposed centrality measure DiffSLc uses the number of interactions of a protein and gen...

Using CdTe/ZnSe core/shell quantum dots to detect DNA and damage to DNA

PubMed Central

Moulick, Amitava; Milosavljevic, Vedran; Vlachova, Jana; Podgajny, Robert; Hynek, David; Kopel, Pavel; Adam, Vojtech

2017-01-01

CdTe/ZnSe core/shell quantum dot (QD), one of the strongest and most highly luminescent nanoparticles, was directly synthesized in an aqueous medium to study its individual interactions with important nucleobases (adenine, guanine, cytosine, and thymine) in detail. The results obtained from the optical analyses indicated that the interactions of the QDs with different nucleobases were different, which reflected in different fluorescent emission maxima and intensities. The difference in the interaction was found due to the different chemical behavior and different sizes of the formed nanoconjugates. An electrochemical study also confirmed that the purines and pyrimidines show different interactions with the core/shell QDs. Based on these phenomena, a novel QD-based method is developed to detect the presence of the DNA, damage to DNA, and mutation. The QDs were successfully applied very easily to detect any change in the sequence (mutation) of DNA. The QDs also showed their ability to detect DNAs directly from the extracts of human cancer (PC3) and normal (PNT1A) cells (detection limit of 500 pM of DNA), which indicates the possibilities to use this easy assay technique to confirm the presence of living organisms in extreme environments. PMID:28243089

Extended GTST-MLD for aerospace system safety analysis.

PubMed

Guo, Chiming; Gong, Shiyu; Tan, Lin; Guo, Bo

2012-06-01

The hazards caused by complex interactions in the aerospace system have become a problem that urgently needs to be settled. This article introduces a method for aerospace system hazard interaction identification based on extended GTST-MLD (goal tree-success tree-master logic diagram) during the design stage. GTST-MLD is a functional modeling framework with a simple architecture. Ontology is used to extend the ability of system interaction description in GTST-MLD by adding the system design knowledge and the past accident experience. From the level of functionality and equipment, respectively, this approach can help the technician detect potential hazard interactions. Finally, a case is used to show the method. © 2011 Society for Risk Analysis.

A novel microfluidics-based method for probing weak protein-protein interactions.

PubMed

Tan, Darren Cherng-wen; Wijaya, I Putu Mahendra; Andreasson-Ochsner, Mirjam; Vasina, Elena Nikolaevna; Nallani, Madhavan; Hunziker, Walter; Sinner, Eva-Kathrin

2012-08-07

We report the use of a novel microfluidics-based method to detect weak protein-protein interactions between membrane proteins. The tight junction protein, claudin-2, synthesised in vitro using a cell-free expression system in the presence of polymer vesicles as membrane scaffolds, was used as a model membrane protein. Individual claudin-2 molecules interact weakly, although the cumulative effect of these interactions is significant. This effect results in a transient decrease of average vesicle dispersivity and reduction in transport speed of claudin-2-functionalised vesicles. Polymer vesicles functionalised with claudin-2 were perfused through a microfluidic channel and the time taken to traverse a defined distance within the channel was measured. Functionalised vesicles took 1.19 to 1.69 times longer to traverse this distance than unfunctionalised ones. Coating the channel walls with protein A and incubating the vesicles with anti-claudin-2 antibodies prior to perfusion resulted in the functionalised vesicles taking 1.75 to 2.5 times longer to traverse this distance compared to the controls. The data show that our system is able to detect weak as well as strong protein-protein interactions. This system offers researchers a portable, easily operated and customizable platform for the study of weak protein-protein interactions, particularly between membrane proteins.

Study of the interaction of 6-mercaptopurine with protein by microdialysis coupled with LC and electrochemical detection based on functionalized multi-wall carbon nanotubes modified electrode.

PubMed

Cao, Xu-Ni; Lin, Li; Zhou, Yu-Yan; Zhang, Wen; Shi, Guo-Yue; Yamamoto, Katsunobu; Jin, Li-Tong

2003-07-14

Microdialysis sampling coupled with liquid chromatography and electrochemical detection (LC-ECD) was developed and applied to study the interaction of 6-Mercaptopurine (6-MP) with bovine serum albumin (BSA). In the LC-ECD, the multi-wall carbon nanotubes fuctionalized with carboxylic groups modified electrode (MWNT-COOH CME) was used as the working electrode for the determination of 6-MP. The results indicated that this chemically modified electrode (CME) exhibited efficiently electrocatalytic oxidation for 6-MP with relatively high sensitivity, stability and long-life. The peak currents of 6-MP were linear to its concentrations ranging from 4.0 x 10(-7) to 1.0 x 10(-4) mol l(-1) with the calculated detection limit (S/N = 3) of 2.0 x 10(-7) mol l(-1). The method had been successfully applied to assess the association constant (K) and the number of the binding sites (n) on a BSA molecular, which calculated by Scatchard equation, were 3.97 x 10(3) mol(-1) l and 1.51, respectively. This method provided a fast, sensible and simple technique for the study of drug-protein interactions.

Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils.

PubMed

Brandes, Susanne; Mokhtari, Zeinab; Essig, Fabian; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-02-01

Time-lapse microscopy is an important technique to study the dynamics of various biological processes. The labor-intensive manual analysis of microscopy videos is increasingly replaced by automated segmentation and tracking methods. These methods are often limited to certain cell morphologies and/or cell stainings. In this paper, we present an automated segmentation and tracking framework that does not have these restrictions. In particular, our framework handles highly variable cell shapes and does not rely on any cell stainings. Our segmentation approach is based on a combination of spatial and temporal image variations to detect moving cells in microscopy videos. This method yields a sensitivity of 99% and a precision of 95% in object detection. The tracking of cells consists of different steps, starting from single-cell tracking based on a nearest-neighbor-approach, detection of cell-cell interactions and splitting of cell clusters, and finally combining tracklets using methods from graph theory. The segmentation and tracking framework was applied to synthetic as well as experimental datasets with varying cell densities implying different numbers of cell-cell interactions. We established a validation framework to measure the performance of our tracking technique. The cell tracking accuracy was found to be >99% for all datasets indicating a high accuracy for connecting the detected cells between different time points. Copyright © 2014 Elsevier B.V. All rights reserved.

Simultaneous determination of several antalgic drugs based on their interactions with beta-cyclodextrin by capillary zone electrophoresis.

PubMed

Wei, Wei; Yu, Xiaodong; Ju, Huangxin

2004-03-01

The binding constants of beta-cyclodextrin (beta-CD) with antalgic drugs such as naproxen, ketoprofen, ibuprofen, acemetacin, and aspirin are determined by affinity capillary electrophoresis. Based on these interactions, a reliable method for the separation and simultaneous determinations of these compounds in the presence of 5.0 mM beta-CD in phosphate buffer solution is presented by capillary zone electrophoresis with UV detection at 214 nm for naproxen and 200 nm for the others. The linear ranges for naproxen, ketoprofen, ibuprofen, acemetacin, aspirin, and caffeine detections are from 2.0 to 800, 2.5 to 1000, 2.5 to 700, 2.5 to 700, 2.0 to 800, and 1.5 to 800 microg/mL, respectively. Their detection limits are 1.0, 0.5, 0.5, 1.5, 1.5, and 1.0 microg/mL at a signal to noise ratio of 3, respectively. This method has been successfully applied to the detections of these drugs in the pharmaceutical formulations (tablets or capsules) and urine samples.

An impedance spectroscopy method for the detection and evaluation of Babesia bovis antibodies in cattle

USDA-ARS?s Scientific Manuscript database

An immunosensor method for diagnosis of Babesia bovis in cattle based on impedance measurement is presented in this study. The method probes the interaction between serum antibodies against B. bovis infected cattle and recombinant protein, RAP-1, with C-terminal obtained from a Portuguese B. bovis s...

On-line solid-phase microextraction of triclosan, bisphenol A, chlorophenols, and selected pharmaceuticals in environmental water samples by high-performance liquid chromatography-ultraviolet detection.

PubMed

Kim, Dalho; Han, Jungho; Choi, Yongwook

2013-01-01

A method using on-line solid-phase microextraction (SPME) on a carbowax-templated fiber followed by liquid chromatography (LC) with ultraviolet (UV) detection was developed for the determination of triclosan in environmental water samples. Along with triclosan, other selected phenolic compounds, bisphenol A, and acidic pharmaceuticals were studied. Previous SPME/LC or stir-bar sorptive extraction/LC-UV for polar analytes showed lack of sensitivity. In this study, the calculated octanol-water distribution coefficient (log D) values of the target analytes at different pH values were used to estimate polarity of the analytes. The lack of sensitivity observed in earlier studies is identified as a lack of desorption by strong polar-polar interactions between analyte and solid-phase. Calculated log D values were useful to understand or predict the interaction between analyte and solid phase. Under the optimized conditions, the method detection limit of selected analytes by using on-line SPME-LC-UV method ranged from 5 to 33 ng L(-1), except for very polar 3-chlorophenol and 2,4-dichlorophenol which was obscured in wastewater samples by an interfering substance. This level of detection represented a remarkable improvement over the conventional existing methods. The on-line SPME-LC-UV method, which did not require derivatization of analytes, was applied to the determination of TCS including phenolic compounds and acidic pharmaceuticals in tap water and river water and municipal wastewater samples.

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

PubMed Central

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-01-01

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.

PubMed

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-02-17

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes.

Dyes as bifunctional markers of DNA hybridization on surfaces and mutation detection.

PubMed

García-Mendiola, Tania; Cerro, María Ramos; López-Moreno, José María; Pariente, Félix; Lorenzo, Encarnación

2016-10-01

The interaction of small molecules with DNA has found diagnostic and therapeutic applications. In this work, we propose the use of two different dyes, in particular Azure A and Safranine, as bifunctional markers of on-surface DNA hybridization and potent tools for screening of specific gene mutations directly in real DNA PCR amplicons extracted from blood cells. By combining spectroscopic and electrochemical methods we demonstrate that both dyes can interact with single and double stranded DNA to a different extent, allowing reliable hybridization detection. From these data, we have also elucidated the nature of the interaction. We conclude that the binding mode is fundamentally intercalative with an electrostatic component. The dye fluorescence allows their use as nucleic acid stains for the detection of on-surfaces DNA hybridization. Its redox activity is exploited in the development of selective electrochemical DNA biosensors. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of the interaction between membrane proteins and soluble binding partners by surface plasmon resonance.

PubMed

Wu, Zht Cheng; de Keyzer, Jeanine; Kusters, Ilja; Driessen, Arnold J M

2013-01-01

The interaction between membrane proteins and their (protein) ligands is conventionally investigated by nonequilibrium methods such as co-sedimentation or pull-down assays. Surface Plasmon Resonance can be used to monitor such binding events in real-time using isolated membranes immobilized to a surface providing insights in the kinetics of binding under equilibrium conditions. This application provides a fast, automated way to detect interacting species and to determine the kinetics and affinity (Kd) of the interaction.

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

PubMed

Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be obtained from git.io/diffslcpy. The R implementation and code to reproduce the analysis is available via git.io/diffslc.

Nanoparticle light scattering on interferometric surfaces

NASA Astrophysics Data System (ADS)

Hayrapetyan, K.; Arif, K. M.; Savran, C. A.; Nolte, D. D.

2011-03-01

We present a model based on Mie Surface Double Interaction (MSDI) to explore bead-based detection mechanisms using imaging and scanning. The application goal of this work is to explore the trade-offs between the sensitivity and throughput among various detection methods. Experimentally we use thermal oxide on silicon to establish and control surface interferometric conditions. Surface-captured gold beads are detected using Molecular Interferometric Imaging (MI2) and Spinning-Disc Interferometry (SDI).

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation.

PubMed

Taylor, Dane; Shai, Saray; Stanley, Natalie; Mucha, Peter J

2016-06-03

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common-but not well understood-practice of thresholding pairwise-interaction data to obtain sparse network representations.

Detection of anions by normal Raman spectroscopy and surface-enhanced Raman spectroscopy of cationic-coated substrates.

PubMed

Mosier-Boss, P A; Lieberman, S H

2003-09-01

The use of normal Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) of cationic-coated silver and gold substrates to detect polyatomic anions in aqueous environments is examined. For normal Raman spectroscopy, using near-infrared excitation, linear concentration responses were observed. Detection limits varied from 84 ppm for perchlorate to 2600 ppm for phosphate. In general, detection limits in the ppb to ppm concentration range for the polyatomic anions were achieved using cationic-coated SERS substrates. Adsorption of the polyatomic anions on the cationic-coated SERS substrates was described by a Frumkin isotherm. The SERS technique could not be used to detect dichromate, as this anion reacted with the coatings to form thiol esters. A competitive complexation method was used to evaluate the interaction of chloride ion with the cationic coatings. Hydrogen bonding and pi-pi interactions play significant roles in the selectivity of the cationic coatings.

Single-molecule detection of proteins with antigen-antibody interaction using resistive-pulse sensing of submicron latex particles

NASA Astrophysics Data System (ADS)

Takakura, T.; Yanagi, I.; Goto, Y.; Ishige, Y.; Kohara, Y.

2016-03-01

We developed a resistive-pulse sensor with a solid-state pore and measured the latex agglutination of submicron particles induced by antigen-antibody interaction for single-molecule detection of proteins. We fabricated the pore based on numerical simulation to clearly distinguish between monomer and dimer latex particles. By measuring single dimers agglutinated in the single-molecule regime, we detected single human alpha-fetoprotein molecules. Adjusting the initial particle concentration improves the limit of detection (LOD) to 95 fmol/l. We established a theoretical model of the LOD by combining the reaction kinetics and the counting statistics to explain the effect of initial particle concentration on the LOD. The theoretical model shows how to improve the LOD quantitatively. The single-molecule detection studied here indicates the feasibility of implementing a highly sensitive immunoassay by a simple measurement method using resistive-pulse sensing.

Finger tips detection for two handed gesture recognition

NASA Astrophysics Data System (ADS)

Bhuyan, M. K.; Kar, Mithun Kumar; Neog, Debanga Raj

2011-10-01

In this paper, a novel algorithm is proposed for fingertips detection in view of two-handed static hand pose recognition. In our method, finger tips of both hands are detected after detecting hand regions by skin color-based segmentation. At first, the face is removed in the image by using Haar classifier and subsequently, the regions corresponding to the gesturing hands are isolated by a region labeling technique. Next, the key geometric features characterizing gesturing hands are extracted for two hands. Finally, for all possible/allowable finger movements, a probabilistic model is developed for pose recognition. Proposed method can be employed in a variety of applications like sign language recognition and human-robot-interactions etc.

Observing real-time social interaction via telecommunication methods in budgerigars (Melopsittacus undulatus).

PubMed

Ikkatai, Yuko; Okanoya, Kazuo; Seki, Yoshimasa

2016-07-01

Humans communicate with one another not only face-to-face but also via modern telecommunication methods such as television and video conferencing. We readily detect the difference between people actively communicating with us and people merely acting via a broadcasting system. We developed an animal model of this novel communication method seen in humans to determine whether animals also make this distinction. We built a system for two animals to interact via audio-visual equipment in real-time, to compare behavioral differences between two conditions, an "interactive two-way condition" and a "non-interactive (one-way) condition." We measured birds' responses to stimuli which appeared in these two conditions. We used budgerigars, which are small, gregarious birds, and found that the frequency of vocal interaction with other individuals did not differ between the two conditions. However, body synchrony between the two birds was observed more often in the interactive condition, suggesting budgerigars recognized the difference between these interactive and non-interactive conditions on some level. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistical models for detecting differential chromatin interactions mediated by a protein.

PubMed

Niu, Liang; Li, Guoliang; Lin, Shili

2014-01-01

Chromatin interactions mediated by a protein of interest are of great scientific interest. Recent studies show that protein-mediated chromatin interactions can have different intensities in different types of cells or in different developmental stages of a cell. Such differences can be associated with a disease or with the development of a cell. Thus, it is of great importance to detect protein-mediated chromatin interactions with different intensities in different cells. A recent molecular technique, Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET), which uses formaldehyde cross-linking and paired-end sequencing, is able to detect genome-wide chromatin interactions mediated by a protein of interest. Here we proposed two models (One-Step Model and Two-Step Model) for two sample ChIA-PET count data (one biological replicate in each sample) to identify differential chromatin interactions mediated by a protein of interest. Both models incorporate the data dependency and the extent to which a fragment pair is related to a pair of DNA loci of interest to make accurate identifications. The One-Step Model makes use of the data more efficiently but is more computationally intensive. An extensive simulation study showed that the models can detect those differentially interacted chromatins and there is a good agreement between each classification result and the truth. Application of the method to a two-sample ChIA-PET data set illustrates its utility. The two models are implemented as an R package MDM (available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM).

Statistical Models for Detecting Differential Chromatin Interactions Mediated by a Protein

PubMed Central

Niu, Liang; Li, Guoliang; Lin, Shili

2014-01-01

Chromatin interactions mediated by a protein of interest are of great scientific interest. Recent studies show that protein-mediated chromatin interactions can have different intensities in different types of cells or in different developmental stages of a cell. Such differences can be associated with a disease or with the development of a cell. Thus, it is of great importance to detect protein-mediated chromatin interactions with different intensities in different cells. A recent molecular technique, Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET), which uses formaldehyde cross-linking and paired-end sequencing, is able to detect genome-wide chromatin interactions mediated by a protein of interest. Here we proposed two models (One-Step Model and Two-Step Model) for two sample ChIA-PET count data (one biological replicate in each sample) to identify differential chromatin interactions mediated by a protein of interest. Both models incorporate the data dependency and the extent to which a fragment pair is related to a pair of DNA loci of interest to make accurate identifications. The One-Step Model makes use of the data more efficiently but is more computationally intensive. An extensive simulation study showed that the models can detect those differentially interacted chromatins and there is a good agreement between each classification result and the truth. Application of the method to a two-sample ChIA-PET data set illustrates its utility. The two models are implemented as an R package MDM (available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM). PMID:24835279

Local cell metrics: a novel method for analysis of cell-cell interactions.

PubMed

Su, Jing; Zapata, Pedro J; Chen, Chien-Chiang; Meredith, J Carson

2009-10-23

The regulation of many cell functions is inherently linked to cell-cell contact interactions. However, effects of contact interactions among adherent cells can be difficult to detect with global summary statistics due to the localized nature and noise inherent to cell-cell interactions. The lack of informatics approaches specific for detecting cell-cell interactions is a limitation in the analysis of large sets of cell image data, including traditional and combinatorial or high-throughput studies. Here we introduce a novel histogram-based data analysis strategy, termed local cell metrics (LCMs), which addresses this shortcoming. The new LCM method is demonstrated via a study of contact inhibition of proliferation of MC3T3-E1 osteoblasts. We describe how LCMs can be used to quantify the local environment of cells and how LCMs are decomposed mathematically into metrics specific to each cell type in a culture, e.g., differently-labelled cells in fluorescence imaging. Using this approach, a quantitative, probabilistic description of the contact inhibition effects in MC3T3-E1 cultures has been achieved. We also show how LCMs are related to the naïve Bayes model. Namely, LCMs are Bayes class-conditional probability functions, suggesting their use for data mining and classification. LCMs are successful in robust detection of cell contact inhibition in situations where conventional global statistics fail to do so. The noise due to the random features of cell behavior was suppressed significantly as a result of the focus on local distances, providing sensitive detection of cell-cell contact effects. The methodology can be extended to any quantifiable feature that can be obtained from imaging of cell cultures or tissue samples, including optical, fluorescent, and confocal microscopy. This approach may prove useful in interpreting culture and histological data in fields where cell-cell interactions play a critical role in determining cell fate, e.g., cancer, developmental biology, and tissue regeneration.

Dynamical inference: where phase synchronization and generalized synchronization meet.

PubMed

Stankovski, Tomislav; McClintock, Peter V E; Stefanovska, Aneta

2014-06-01

Synchronization is a widespread phenomenon that occurs among interacting oscillatory systems. It facilitates their temporal coordination and can lead to the emergence of spontaneous order. The detection of synchronization from the time series of such systems is of great importance for the understanding and prediction of their dynamics, and several methods for doing so have been introduced. However, the common case where the interacting systems have time-variable characteristic frequencies and coupling parameters, and may also be subject to continuous external perturbation and noise, still presents a major challenge. Here we apply recent developments in dynamical Bayesian inference to tackle these problems. In particular, we discuss how to detect phase slips and the existence of deterministic coupling from measured data, and we unify the concepts of phase synchronization and general synchronization. Starting from phase or state observables, we present methods for the detection of both phase and generalized synchronization. The consistency and equivalence of phase and generalized synchronization are further demonstrated, by the analysis of time series from analog electronic simulations of coupled nonautonomous van der Pol oscillators. We demonstrate that the detection methods work equally well on numerically simulated chaotic systems. In all the cases considered, we show that dynamical Bayesian inference can clearly identify noise-induced phase slips and distinguish coherence from intrinsic coupling-induced synchronization.

Application of scanning laser Doppler vibrometry for delamination detection in composite structures

NASA Astrophysics Data System (ADS)

Kudela, Pawel; Wandowski, Tomasz; Malinowski, Pawel; Ostachowicz, Wieslaw

2017-12-01

In this paper application of scanning laser Doppler vibrometry for delamination detection in composite structures was presented. Delamination detection was based on a guided wave propagation method. In this papers results from numerical and experimental research were presented. In the case of numerical research, the Spectral Element Method (SEM) was utilized, in which a mesh was composed of 3D spectral elements. SEM model included also a piezoelectric transducer. In the experimental research guided waves were excited using the piezoelectric transducer whereas the sensing process was conducted using scanning laser Doppler vibrometer (SLDV). Analysis of guided wave propagation and its interaction with delamination was based on a full wavefield approach. Attention was focused on interactions of guided waves with delamination manifested by A0 mode reflection, A0 mode entrapment, and S0/A0 mode conversion. Delamination was simulated by a teflon insert located between plies of composite material. Results of interaction with symmetrically and nonsymmetrical placed delamination (in respect to the composite sample thickness) were presented. Moreover, the authors investigated different size of delaminations. Damage detection was based on a new signal processing algorithm proposed by the authors. In this approach the weighted RMS was utilized selectively. It means that the summation in RMS formula was performed only for a specially selected time instances. Results for simple composite panels, panel with honeycomb core, and real stiffened composite panel from the aircraft were presented.

Monitoring molecular interactions using photon arrival-time interval distribution analysis

DOEpatents

Laurence, Ted A [Livermore, CA; Weiss, Shimon [Los Angels, CA

2009-10-06

A method for analyzing/monitoring the properties of species that are labeled with fluorophores. A detector is used to detect photons emitted from species that are labeled with one or more fluorophores and located in a confocal detection volume. The arrival time of each of the photons is determined. The interval of time between various photon pairs is then determined to provide photon pair intervals. The number of photons that have arrival times within the photon pair intervals is also determined. The photon pair intervals are then used in combination with the corresponding counts of intervening photons to analyze properties and interactions of the molecules including brightness, concentration, coincidence and transit time. The method can be used for analyzing single photon streams and multiple photon streams.

Techniques of EMG signal analysis: detection, processing, classification and applications

PubMed Central

Hussain, M.S.; Mohd-Yasin, F.

2006-01-01

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

Robust detection of chromosomal interactions from small numbers of cells using low-input Capture-C

PubMed Central

Oudelaar, A. Marieke; Davies, James O.J.; Downes, Damien J.; Higgs, Douglas R.

2017-01-01

Abstract Chromosome conformation capture (3C) techniques are crucial to understanding tissue-specific regulation of gene expression, but current methods generally require large numbers of cells. This hampers the investigation of chromatin architecture in rare cell populations. We present a new low-input Capture-C approach that can generate high-quality 3C interaction profiles from 10 000–20 000 cells, depending on the resolution used for analysis. We also present a PCR-free, sequencing-free 3C technique based on NanoString technology called C-String. By comparing C-String and Capture-C interaction profiles we show that the latter are not skewed by PCR amplification. Furthermore, we demonstrate that chromatin interactions detected by Capture-C do not depend on the degree of cross-linking by performing experiments with varying formaldehyde concentrations. PMID:29186505

Left ventricular volume estimation in cardiac three-dimensional ultrasound: a semiautomatic border detection approach.

PubMed

van Stralen, Marijn; Bosch, Johan G; Voormolen, Marco M; van Burken, Gerard; Krenning, Boudewijn J; van Geuns, Robert-Jan M; Lancée, Charles T; de Jong, Nico; Reiber, Johan H C

2005-10-01

We propose a semiautomatic endocardial border detection method for three-dimensional (3D) time series of cardiac ultrasound (US) data based on pattern matching and dynamic programming, operating on two-dimensional (2D) slices of the 3D plus time data, for the estimation of full cycle left ventricular volume, with minimal user interaction. The presented method is generally applicable to 3D US data and evaluated on data acquired with the Fast Rotating Ultrasound (FRU-) Transducer, developed by Erasmus Medical Center (Rotterdam, the Netherlands), a conventional phased-array transducer, rotating at very high speed around its image axis. The detection is based on endocardial edge pattern matching using dynamic programming, which is constrained by a 3D plus time shape model. It is applied to an automatically selected subset of 2D images of the original data set, for typically 10 equidistant rotation angles and 16 cardiac phases (160 images). Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastole and end-systole volumes. Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastolic (ED) and end-systolic (ES) volumes. The semiautomatic border detection approach shows good correlations with MRI ED/ES volumes (r = 0.938) and low interobserver variability (y = 1.005x - 16.7, r = 0.943) over full-cycle volume estimations. It shows a high consistency in tracking the user-defined initial borders over space and time. We show that the ease of the acquisition using the FRU-transducer and the semiautomatic endocardial border detection method together can provide a way to quickly estimate the left ventricular volume over the full cardiac cycle using little user interaction.

A survey about methods dedicated to epistasis detection.

PubMed

Niel, Clément; Sinoquet, Christine; Dina, Christian; Rocheleau, Ghislain

2015-01-01

During the past decade, findings of genome-wide association studies (GWAS) improved our knowledge and understanding of disease genetics. To date, thousands of SNPs have been associated with diseases and other complex traits. Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests. However, geneticists admit this is an oversimplified approach to tackle the complexity of underlying biological mechanisms. Interaction between SNPs, namely epistasis, must be considered. Unfortunately, epistasis detection gives rise to analytic challenges since analyzing every SNP combination is at present impractical at a genome-wide scale. In this review, we will present the main strategies recently proposed to detect epistatic interactions, along with their operating principle. Some of these methods are exhaustive, such as multifactor dimensionality reduction, likelihood ratio-based tests or receiver operating characteristic curve analysis; some are non-exhaustive, such as machine learning techniques (random forests, Bayesian networks) or combinatorial optimization approaches (ant colony optimization, computational evolution system).

Luminescent detection of hydrazine and hydrazine derivatives

DOEpatents

Swager, Timothy M [Newton, MA; Thomas, III, Samuel W.

2012-04-17

The present invention generally relates to methods for modulating the optical properties of a luminescent polymer via interaction with a species (e.g., an analyte). In some cases, the present invention provides methods for determination of an analyte by monitoring a change in an optical signal of a luminescent polymer upon exposure to an analyte. Methods of the present invention may be useful for the vapor phase detection of analytes such as explosives and toxins. The present invention also provides methods for increasing the luminescence intensity of a polymer, such as a polymer that has been photobleached, by exposing the luminescent polymer to a species such as a reducing agent.

Predicting Physical Interactions between Protein Complexes*

PubMed Central

Clancy, Trevor; Rødland, Einar Andreas; Nygard, Ståle; Hovig, Eivind

2013-01-01

Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships. PMID:23438732

Recognition and defect detection of dot-matrix text via variation-model based learning

NASA Astrophysics Data System (ADS)

Ohyama, Wataru; Suzuki, Koushi; Wakabayashi, Tetsushi

2017-03-01

An algorithm for recognition and defect detection of dot-matrix text printed on products is proposed. Extraction and recognition of dot-matrix text contains several difficulties, which are not involved in standard camera-based OCR, that the appearance of dot-matrix characters is corrupted and broken by illumination, complex texture in the background and other standard characters printed on product packages. We propose a dot-matrix text extraction and recognition method which does not require any user interaction. The method employs detected location of corner points and classification score. The result of evaluation experiment using 250 images shows that recall and precision of extraction are 78.60% and 76.03%, respectively. Recognition accuracy of correctly extracted characters is 94.43%. Detecting printing defect of dot-matrix text is also important in the production scene to avoid illegal productions. We also propose a detection method for printing defect of dot-matrix characters. The method constructs a feature vector of which elements are classification scores of each character class and employs support vector machine to classify four types of printing defect. The detection accuracy of the proposed method is 96.68 %.

Oil Spill AISA+ Hyperspectral Data Detection Based on Different Sea Surface Glint Suppression Methods

NASA Astrophysics Data System (ADS)

Yang, J.; Ren, G.; Ma, Y.; Dong, L.; Wan, J.

2018-04-01

The marine oil spill is a sudden event, and the airborne hyperspectral means to detect the oil spill is an important part of the rapid response. Sun glint, the specular reflection of sun light from water surface to sensor, is inevitable due to the limitation of observation geometry, which makes so much bright glint in image that it is difficult to extract oil spill feature information from the remote sensing data. This paper takes AISA+ airborne hyperspectral oil spill image as data source, using multi-scale wavelet transform, enhanced Lee filter, enhanced Frost filter and mean filter method for sea surface glint suppression of images. And then the classical SVM method is used for the oil spill information detection, and oil spill information distribution map obtained by human-computer interactive interpretation is used to verify the accuracy of oil spill detection. The results show that the above methods can effectively suppress the sea surface glints and improve the accuracy of oil spill detection. The enhanced Lee filter method has the highest detection accuracy of 88.28 %, which is 12.2 % higher than that of the original image.

Compensatable muon collider calorimeter with manageable backgrounds

DOEpatents

Raja, Rajendran

2015-02-17

A method and system for reducing background noise in a particle collider, comprises identifying an interaction point among a plurality of particles within a particle collider associated with a detector element, defining a trigger start time for each of the pixels as the time taken for light to travel from the interaction point to the pixel and a trigger stop time as a selected time after the trigger start time, and collecting only detections that occur between the start trigger time and the stop trigger time in order to thereafter compensate the result from the particle collider to reduce unwanted background detection.

A new method for detection of distant supernova neutrino bursts

NASA Astrophysics Data System (ADS)

Cline, D.; Fenyves, E.; Foshe, T.; Fuller, G.; Meyer, B.; Wilson, J.

1990-03-01

The feasibility of astrophysical neutrino detectors is studied, which is based on the detection of neutrons produced in neutrino-nucleus inelastic scattering events. Collective nuclear effects greatly enhancing the relevant interaction cross sections over those of single particle interactions are discussed. These effects can help to reduce the mass required for neutrino detectors. An example of a simple detector based on CaCO3 neutrino targets and BF3 neutron counters is presented. Neutron background limitations are discussed and the possibility of forming a coincidence between neutrino detectors and future gravity wave detectors is also considered.

Measuring information interactions on the ordinal pattern of stock time series

NASA Astrophysics Data System (ADS)

Zhao, Xiaojun; Shang, Pengjian; Wang, Jing

2013-02-01

The interactions among time series as individual components of complex systems can be quantified by measuring to what extent they exchange information among each other. In many applications, one focuses not on the original series but on its ordinal pattern. In such cases, trivial noises appear more likely to be filtered and the abrupt influence of extreme values can be weakened. Cross-sample entropy and inner composition alignment have been introduced as prominent methods to estimate the information interactions of complex systems. In this paper, we modify both methods to detect the interactions among the ordinal pattern of stock return and volatility series, and we try to uncover the information exchanges across sectors in Chinese stock markets.

On the use of sibling recurrence risks to select environmental factors liable to interact with genetic risk factors.

PubMed

Kazma, Rémi; Bonaïti-Pellié, Catherine; Norris, Jill M; Génin, Emmanuelle

2010-01-01

Gene-environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene-environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene-environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype.

Using an innovative multiple regression procedure in a cancer population (Part 1): detecting and probing relationships of common interacting symptoms (pain, fatigue/weakness, sleep problems) as a strategy to discover influential symptom pairs and clusters

PubMed Central

Francoeur, Richard B

2015-01-01

Background The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Materials and methods Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Results Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain–fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain–fatigue/weakness–sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. Conclusion By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial. PMID:25565865

A proximity-based graph clustering method for the identification and application of transcription factor clusters.

PubMed

Spadafore, Maxwell; Najarian, Kayvan; Boyle, Alan P

2017-11-29

Transcription factors (TFs) form a complex regulatory network within the cell that is crucial to cell functioning and human health. While methods to establish where a TF binds to DNA are well established, these methods provide no information describing how TFs interact with one another when they do bind. TFs tend to bind the genome in clusters, and current methods to identify these clusters are either limited in scope, unable to detect relationships beyond motif similarity, or not applied to TF-TF interactions. Here, we present a proximity-based graph clustering approach to identify TF clusters using either ChIP-seq or motif search data. We use TF co-occurrence to construct a filtered, normalized adjacency matrix and use the Markov Clustering Algorithm to partition the graph while maintaining TF-cluster and cluster-cluster interactions. We then apply our graph structure beyond clustering, using it to increase the accuracy of motif-based TFBS searching for an example TF. We show that our method produces small, manageable clusters that encapsulate many known, experimentally validated transcription factor interactions and that our method is capable of capturing interactions that motif similarity methods might miss. Our graph structure is able to significantly increase the accuracy of motif TFBS searching, demonstrating that the TF-TF connections within the graph correlate with biological TF-TF interactions. The interactions identified by our method correspond to biological reality and allow for fast exploration of TF clustering and regulatory dynamics.

Methods of preparing and using single chain anti-tumor antibodies

DOEpatents

Cheung, Nai-Kong; Guo, Hong-Fen

2010-02-23

This invention provides a method for identifying cells expressing a target single chain antibody (scFv) directed against a target antigen from a collection of cells that includes cells that do not express the target scFv, comprising the step of combining the collection of cells with an anti-idiotype directed to an antibody specific for the target antigen and detecting interaction, if any, of the anti-idiotype with the cells, wherein the occurrence of an interaction identifies the cell as one which expresses the target scFv. This invention also provides a method for making a single chain antibody (scFv) directed against an antigen, wherein the selection of clones is made based upon interaction of those clones with an appropriate anti-idiotype, and heretofore inaccessible scFv so made. This invention provides the above methods or any combination thereof. Finally, this invention provides various uses of these methods.

Method for preparation of single chain antibodies

DOEpatents

Cheung, Nai-Kong V [New York, NY; Guo, Hong-fen [New York, NY

2012-04-03

This invention provides a method for identifying cells expressing a target single chain antibody (scFv) directed against a target antigen from a collection of cells that includes cells that do not express the target scFv, comprising the step of combining the collection of cells with an anti-idiotype directed to an antibody specific for the target antigen and detecting interaction, if any, of the anti-idiotype with the cells, wherein the occurrence of an interaction identifies the cell as one which expresses the target scFv. This invention also provides a method for making a single chain antibody (scFv) directed against an antigen, wherein the selection of clones is made based upon interaction of those clones with an appropriate anti-idiotype, and heretofore inaccessible scFv so made. This invention provides the above methods or any combination thereof. Finally, this invention provides various uses of these methods.

Time-varying coupling functions: Dynamical inference and cause of synchronization transitions

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav

2017-02-01

Interactions in nature can be described by their coupling strength, direction of coupling, and coupling function. The coupling strength and directionality are relatively well understood and studied, at least for two interacting systems; however, there can be a complexity in the interactions uniquely dependent on the coupling functions. Such a special case is studied here: synchronization transition occurs only due to the time variability of the coupling functions, while the net coupling strength is constant throughout the observation time. To motivate the investigation, an example is used to present an analysis of cross-frequency coupling functions between delta and alpha brain waves extracted from the electroencephalography recording of a healthy human subject in a free-running resting state. The results indicate that time-varying coupling functions are a reality for biological interactions. A model of phase oscillators is used to demonstrate and detect the synchronization transition caused by the varying coupling functions during an invariant coupling strength. The ability to detect this phenomenon is discussed with the method of dynamical Bayesian inference, which was able to infer the time-varying coupling functions. The form of the coupling function acts as an additional dimension for the interactions, and it should be taken into account when detecting biological or other interactions from data.

Dense module enumeration in biological networks

NASA Astrophysics Data System (ADS)

Tsuda, Koji; Georgii, Elisabeth

2009-12-01

Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

Dynamical Bayesian inference of time-evolving interactions: from a pair of coupled oscillators to networks of oscillators.

PubMed

Duggento, Andrea; Stankovski, Tomislav; McClintock, Peter V E; Stefanovska, Aneta

2012-12-01

Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski et al. [Phys. Rev. Lett. 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

Analysis of Biological Interactions by Affinity Chromatography: Clinical and Pharmaceutical Applications

PubMed Central

Hage, David S.

2017-01-01

BACKGROUND The interactions between biochemical and chemical agents in the body are important in many clinical processes. Affinity chromatography and high-performance affinity chromatography (HPAC), in which a column contains an immobilized biologically-related binding agent, are two methods that can be used to study these interactions. CONTENT This review looks at various approaches that can be used in affinity chromatography and HPAC to characterize the strength or rate of a biological interaction, the number and types of sites that are involved in this process, and the interactions between multiple solutes for the same binding agent. A number of applications for these methods are examined, with an emphasis on recent developments and high-performance affinity methods. These applications include the use of these techniques for fundamental studies of biological interactions, high-throughput screening of drugs, work with modified proteins, tools for personalized medicine, and studies of drug-drug competition for a common binding agent. SUMMARY The wide range of formats and detection methods that can be used with affinity chromatography and HPAC for examining biological interactions makes these tools attractive for various clinical and pharmaceutical applications. Future directions in the development of small-scale columns and the coupling of these methods with other techniques, such as mass spectrometry or other separation methods, should continue to increase the flexibility and ease with which these approaches can be used in work involving clinical or pharmaceutical samples. PMID:28396561

PhenomeExpress: a refined network analysis of expression datasets by inclusion of known disease phenotypes.

PubMed

Soul, Jamie; Hardingham, Timothy E; Boot-Handford, Raymond P; Schwartz, Jean-Marc

2015-01-29

We describe a new method, PhenomeExpress, for the analysis of transcriptomic datasets to identify pathogenic disease mechanisms. Our analysis method includes input from both protein-protein interaction and phenotype similarity networks. This introduces valuable information from disease relevant phenotypes, which aids the identification of sub-networks that are significantly enriched in differentially expressed genes and are related to the disease relevant phenotypes. This contrasts with many active sub-network detection methods, which rely solely on protein-protein interaction networks derived from compounded data of many unrelated biological conditions and which are therefore not specific to the context of the experiment. PhenomeExpress thus exploits readily available animal model and human disease phenotype information. It combines this prior evidence of disease phenotypes with the experimentally derived disease data sets to provide a more targeted analysis. Two case studies, in subchondral bone in osteoarthritis and in Pax5 in acute lymphoblastic leukaemia, demonstrate that PhenomeExpress identifies core disease pathways in both mouse and human disease expression datasets derived from different technologies. We also validate the approach by comparison to state-of-the-art active sub-network detection methods, which reveals how it may enhance the detection of molecular phenotypes and provide a more detailed context to those previously identified as possible candidates.

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study.

PubMed

Haghighi, Mona; Johnson, Suzanne Bennett; Qian, Xiaoning; Lynch, Kristian F; Vehik, Kendra; Huang, Shuai

2016-08-26

Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.

Selective enrichment and determination of monoamine neurotransmitters by CU(II) immobilized magnetic solid phase extraction coupled with high-performance liquid chromatography-fluorescence detection.

PubMed

He, Maofang; Wang, Chaozhan; Wei, Yinmao

2016-01-15

In this paper, iminodiacetic acid-Cu(II) functionalized Fe3O4@SiO2 magnetic nanoparticles were prepared and used as new adsorbents for magnetic solid phase extraction (MSPE) of six monoamine neurotransmitters (MNTs) from rabbit plasma. The selective enrichment of MNTs at pH 5.0 was motivated by the specific coordination interaction between amino groups of MNTs and the immobilized Cu(II). The employed weak acidic extraction condition avoided the oxidation of MNTs, and thus facilitated operation and ensured higher recoveries. Under optimal conditions, the recoveries of six MNTs from rabbit plasma were in the range of 83.9-109.4%, with RSD of 2.0-10.0%. When coupled the Cu(II) immobilized MSPE with high-performance liquid chromatography-fluorescence detection, the method exhibited relatively lower detection limits than the previously reported methods, and the method was successfully used to determine the endogenous MNTs in rabbit plasma. The proposed method has potential application for the determination of MNTs in biological samples. Also, the utilization of coordination interaction to improve the selectivity might open another way to selectively enrich small alkaloids from complex samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Critical Analysis of an e-Learning and Interactive Teaching Module with Respect to the Interpretation of Emergency Computed Tomography of the Brain.

PubMed

Groth, Michael; Barthe, Käthe Greta; Riemer, Martin; Ernst, Marielle; Herrmann, Jochen; Fiehler, Jens; Buhk, Jan-Hendrik

2018-04-01

 To compare the learning benefit of three different teaching strategies on the interpretation of emergency cerebral computed tomography (CT) pathologies by medical students.  Three groups of students with different types of teaching (e-learning, interactive teaching, and standard curricular education in neuroradiology) were tested with respect to the detection of seven CT pathologies. The test results of each group were compared for each CT pathology using the chi-square test. A p-value ≤ 0.05 was considered to be significant.  Opposed to the results of the comparison group (curricular education), the e-learning group and interactive teaching tutorial group both showed a significantly better performance in detecting hyperdense middle cerebral artery sign (p = 0.001 and p < 0.0001) as well as subarachnoid hemorrhage (p = 0.03 and p = 0.001) on CT. Moreover, an increase in performance for the detection of subdural hematoma and skull fracture could be observed for both the interactive teaching group and the e-learning group, with statistical significance in the latter (p = 0.03 and p < 0.0001, respectively). No statistically significant differences were found for the detection of intracranial and epidural hemorrhage, as well as midline shift, among the groups studied.  Our study demonstrates potential learning benefits for both the interactive teaching tutorial and e-learning module group with respect to reading CT scans with slightly different advantages. Thus, the introduction of new learning methods in radiological education might be reasonable at an undergraduate stage but requires learning content-based considerations.   · E-learning can offer benefits regarding the reading of cerebral CT scans by students. · Interactive tutorial can offer benefits regarding the reading of cerebral CT scans by students. · E-learning and interactive tutorial feature different strengths for student learning in radiology. · Application of interactive teaching methods in radiology requires learning content-based considerations. · Groth M, Barthe KG, Riemer M et al. Critical Analysis of an e-Learning and Interactive Teaching Module with Respect to the Interpretation of Emergency Computed Tomography of the Brain. Fortschr Röntgenstr 2017; 190: 334 - 340. © Georg Thieme Verlag KG Stuttgart · New York.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data

PubMed Central

Carty, Mark; Zamparo, Lee; Sahin, Merve; González, Alvaro; Pelossof, Raphael; Elemento, Olivier; Leslie, Christina S.

2017-01-01

Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts—for example, distance-dependent random polymer ligation and GC content and mappability bias—and model zero inflation and overdispersion. Applied to high-resolution Hi-C data in a lymphoblastoid cell line, HiC-DC detects significant interactions at the sub-topologically associating domain level, identifying potential structural and regulatory interactions supported by CTCF binding sites, DNase accessibility, and/or active histone marks. CTCF-associated interactions are most strongly enriched in the middle genomic distance range (∼700 kb–1.5 Mb), while interactions involving actively marked DNase accessible elements are enriched both at short (<500 kb) and longer (>1.5 Mb) genomic distances. There is a striking enrichment of longer-range interactions connecting replication-dependent histone genes on chromosome 6, potentially representing the chromatin architecture at the histone locus body. PMID:28513628

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

PubMed Central

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

2008-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

PubMed

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

2009-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

A Highly Sensitive Diagnostic System for Detecting Dengue Viruses Using the Interaction between a Sulfated Sugar Chain and a Virion.

PubMed

Saksono, Budi; Dewi, Beti Ernawati; Nainggolan, Leonardo; Suda, Yasuo

2015-01-01

We propose a novel method of detecting trace amounts of dengue virus (DENVs) from serum. Our method is based on the interaction between a sulfated sugar chain and a DENV surface glycoprotein. After capturing DENV with the sulfated sugar chain-immobilized gold nanoparticles (SGNPs), the resulting complex is precipitated and viral RNA content is measured using the reverse-transcription quantitative polymerase chain reaction SYBR Green I (RT-qPCR-Syb) method. Sugar chains that bind to DENVs were identified using the array-type sugar chain immobilized chip (Sugar Chip) and surface plasmon resonance (SPR) imaging. Heparin and low-molecular-weight dextran sulfate were identified as binding partners, and immobilized on gold nanoparticles to prepare 3 types of SGNPs. The capacity of these SGNPs to capture and concentrate trace amounts of DENVs was evaluated in vitro. The SGNP with greatest sensitivity was tested using clinical samples in Indonesia in 2013-2014. As a result, the novel method was able to detect low concentrations of DENVs using only 6 μL of serum, with similar sensitivity to that of a Qiagen RNA extraction kit using 140 μL of serum. In addition, this method allows for multiplex-like identification of serotypes of DENVs. This feature is important for good healthcare management of DENV infection in order to safely diagnose the dangerous, highly contagious disease quickly, with high sensitivity.

Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data.

PubMed

Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios

2014-01-01

To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Enhanced coupling of light into a turbid medium through microscopic interface engineering

PubMed Central

Thompson, Jonathan V.; Hokr, Brett H.; Kim, Wihan; Ballmann, Charles W.; Applegate, Brian E.; Jo, Javier; Yamilov, Alexey; Cao, Hui; Scully, Marlan O.; Yakovlev, Vladislav V.

2017-01-01

There are many optical detection and sensing methods used today that provide powerful ways to diagnose, characterize, and study materials. For example, the measurement of spontaneous Raman scattering allows for remote detection and identification of chemicals. Many other optical techniques provide unique solutions to learn about biological, chemical, and even structural systems. However, when these systems exist in a highly scattering or turbid medium, the optical scattering effects reduce the effectiveness of these methods. In this article, we demonstrate a method to engineer the geometry of the optical interface of a turbid medium, thereby drastically enhancing the coupling efficiency of light into the material. This enhanced optical coupling means that light incident on the material will penetrate deeper into (and through) the medium. It also means that light thus injected into the material will have an enhanced interaction time with particles contained within the material. These results show that, by using the multiple scattering of light in a turbid medium, enhanced light–matter interaction can be achieved; this has a direct impact on spectroscopic methods such as Raman scattering and fluorescence detection in highly scattering regimes. Furthermore, the enhanced penetration depth achieved by this method will directly impact optical techniques that have previously been limited by the inability to deposit sufficient amounts of optical energy below or through highly scattering layers. PMID:28701381

Detecting higher-order interactions among the spiking events in a group of neurons.

PubMed

Martignon, L; Von Hasseln, H; Grün, S; Aertsen, A; Palm, G

1995-06-01

We propose a formal framework for the description of interactions among groups of neurons. This framework is not restricted to the common case of pair interactions, but also incorporates higher-order interactions, which cannot be reduced to lower-order ones. We derive quantitative measures to detect the presence of such interactions in experimental data, by statistical analysis of the frequency distribution of higher-order correlations in multiple neuron spike train data. Our first step is to represent a frequency distribution as a Markov field on the minimal graph it induces. We then show the invariance of this graph with regard to changes of state. Clearly, only linear Markov fields can be adequately represented by graphs. Higher-order interdependencies, which are reflected by the energy expansion of the distribution, require more complex graphical schemes, like constellations or assembly diagrams, which we introduce and discuss. The coefficients of the energy expansion not only point to the interactions among neurons but are also a measure of their strength. We investigate the statistical meaning of detected interactions in an information theoretic sense and propose minimum relative entropy approximations as null hypotheses for significance tests. We demonstrate the various steps of our method in the situation of an empirical frequency distribution on six neurons, extracted from data on simultaneous multineuron recordings from the frontal cortex of a behaving monkey and close with a brief outlook on future work.

Protein-protein interaction predictions using text mining methods.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Iliopoulos, Ioannis

2015-03-01

It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimization of proximity ligation assay (PLA) for detection of protein interactions and fusion proteins in non-adherent cells: application to pre-B lymphocytes.

PubMed

Debaize, Lydie; Jakobczyk, Hélène; Rio, Anne-Gaëlle; Gandemer, Virginie; Troadec, Marie-Bérengère

2017-01-01

Genetic abnormalities, including chromosomal translocations, are described for many hematological malignancies. From the clinical perspective, detection of chromosomal abnormalities is relevant not only for diagnostic and treatment purposes but also for prognostic risk assessment. From the translational research perspective, the identification of fusion proteins and protein interactions has allowed crucial breakthroughs in understanding the pathogenesis of malignancies and consequently major achievements in targeted therapy. We describe the optimization of the Proximity Ligation Assay (PLA) to ascertain the presence of fusion proteins, and protein interactions in non-adherent pre-B cells. PLA is an innovative method of protein-protein colocalization detection by molecular biology that combines the advantages of microscopy with the advantages of molecular biology precision, enabling detection of protein proximity theoretically ranging from 0 to 40 nm. We propose an optimized PLA procedure. We overcome the issue of maintaining non-adherent hematological cells by traditional cytocentrifugation and optimized buffers, by changing incubation times, and modifying washing steps. Further, we provide convincing negative and positive controls, and demonstrate that optimized PLA procedure is sensitive to total protein level. The optimized PLA procedure allows the detection of fusion proteins and protein interactions on non-adherent cells. The optimized PLA procedure described here can be readily applied to various non-adherent hematological cells, from cell lines to patients' cells. The optimized PLA protocol enables detection of fusion proteins and their subcellular expression, and protein interactions in non-adherent cells. Therefore, the optimized PLA protocol provides a new tool that can be adopted in a wide range of applications in the biological field.

Liquid crystal based optical platform for the detection of Pb2+ ions using NiFe2O4 nanoparticles

NASA Astrophysics Data System (ADS)

Zehra, Saman; Gul, Iftikhar Hussain; Hussain, Zakir

2018-06-01

A simple, sensitive, selective and real time detection protocol was developed for Pb2+ ions in water using liquid crystals (LCs). In this method, NiFe2O4 nanoparticles were synthesized using chemical co-precipitation method. Crystallite size, morphological, functional groups and magnetization studies were confirmed using X-ray diffraction, Scanning Electron Microscopy, and Fourier transform infrared spectroscopy techniques, respectively. The nanoparticles were mono dispersed with average particle size of 20 ± 2 nm. The surfactant stabilized magnetic nanoparticles were incubated in liquid crystal based sensor system for the detection of Pb+2 ions. The bright to dark transition of LC was observed through optical microscope. When this system was further immersed with a solution containing Pb2+ ions, it caused homeotropic to planar orientation of LC. This interaction is attributed to the presence of abundant hydroxyl groups in such as M-OH, Fe-OH on the surface of spinel ferrites nanoparticles. These groups interact with metal ions at aqueous interface, causing disruption in LCs orientation giving bright texture. This sensor showed higher selectivity towards Pb2+ ions. The detection limit was estimated to be 100 ppb. The cheap and effective protocol reported here should make promising development of LC based sensor for lead ion detection.

Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC.

PubMed

Zhai, Jing-Xuan; Cao, Tian-Jie; An, Ji-Yong; Bian, Yong-Tao

2017-11-07

It is a challenging task for fundamental research whether proteins can interact with their partners. Protein self-interaction (SIP) is a special case of PPIs, which plays a key role in the regulation of cellular functions. Due to the limitations of experimental self-interaction identification, it is very important to develop an effective biological tool for predicting SIPs based on protein sequences. In the study, we developed a novel computational method called RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) for detecting SIPs from protein sequences. Firstly, Average Blocks (AB) feature extraction method is employed to represent protein sequences on a Position Specific Scoring Matrix (PSSM). Secondly, Principal Component Analysis (PCA) method is used to reduce the dimension of AB vector for reducing the influence of noise. Then, by employing the Relevance Vector Machine (RVM) algorithm, the performance of RVM-AB is assessed and compared with the state-of-the-art support vector machine (SVM) classifier and other exiting methods on yeast and human datasets respectively. Using the fivefold test experiment, RVM-AB model achieved very high accuracies of 93.01% and 97.72% on yeast and human datasets respectively, which are significantly better than the method based on SVM classifier and other previous methods. The experimental results proved that the RVM-AB prediction model is efficient and robust. It can be an automatic decision support tool for detecting SIPs. For facilitating extensive studies for future proteomics research, the RVMAB server is freely available for academic use at http://219.219.62.123:8888/SIP_AB. Copyright © 2017 Elsevier Ltd. All rights reserved.

Direct optical sensors: principles and selected applications.

PubMed

Gauglitz, Guenter

2005-01-01

In the field of bio and chemosensors a large number of detection principles has been published within the last decade. These detection principles are based either on the observation of fluorescence-labelled systems or on direct optical detection in the heterogeneous phase. Direct optical detection can be measured by remission (absorption of reflected radiation, opt(r)odes), by measuring micro-refractivity, or measuring interference. In the last case either Mach-Zehnder interferometers or measurement of changes in the physical thickness of the layer (measuring micro-reflectivity) caused, e.g., by swelling effects in polymers (due to interaction with analytes) or in bioassays (due to affinity reactions) also play an important role. Here, an overview of methods of microrefractometric and microreflectometric principles is given and benefits and drawbacks of the various approaches are demonstrated using samples from the chemo and biosensor field. The quality of sensors does not just depend on transduction principles but on the total sensor system defined by this transduction, the sensitive layer, data acquisition electronics, and evaluation software. The intention of this article is, therefore, to demonstrate the essentials of the interaction of these parts within the system, and the focus is on optical sensing using planar transducers, because fibre optical sensors have been reviewed in this journal only recently. Lack of selectivity of chemosensors can be compensated either by the use of sensor arrays or by evaluating time-resolved measurements of analyte/sensitive layer interaction. In both cases chemometrics enables the quantification of analyte mixtures. These data-processing methods have also been successfully applied to antibody/antigen interactions even using cross-reactive antibodies. Because miniaturisation and parallelisation are essential approaches in recent years, some aspects and current trends, especially for bio-applications, will be discussed. Miniaturisation is especially well covered in the literature.

The potential of seismic methods for detecting cavities and buried objects: experimentation at a test site

NASA Astrophysics Data System (ADS)

Grandjean, Gilles; Leparoux, Donatienne

2004-06-01

One of the recurring problems in civil engineering and landscape management is the detection of natural and man-made cavities in order to mitigate the problems of collapse and subsurface subsidence. In general, the position of the cavities is not known, either because they are not recorded in a database or because location maps are not available. In such cases, geophysical methods can provide an effective alternative for cavity detection, particularly ground-penetrating radar (GPR) and seismic methods, for which pertinent results have been recently obtained. Many studies carried out under real conditions have revealed that the signatures derived from interaction between seismic signals and voids are affected by complex geology, thus making them difficult to interpret. We decided to analyze this interaction under physical conditions as simple as possible, i.e., at a test site built specifically for that purpose. The test site was constructed of a homogeneous material and a void-equivalent body so that the ratio between wavelength and heterogeneity size was compatible with that encountered in reality. Numerical modeling was initially used to understand wave interaction with the body, prior to the design of various data-processing protocols. P-wave imagery and surface-wave sections were then acquired and processed. The work involved in this experiment and the associated results are presented, followed by a discussion concerning the reliability of such a study, and its consequences for future seismic projects.

A Protocol Specification-Based Intrusion Detection System for VoIP and Its Evaluation

NASA Astrophysics Data System (ADS)

Phit, Thyda; Abe, Kôki

We propose an architecture of Intrusion Detection System (IDS) for VoIP using a protocol specification-based detection method to monitor the network traffics and alert administrator for further analysis of and response to suspicious activities. The protocol behaviors and their interactions are described by state machines. Traffic that behaves differently from the standard specifications are considered to be suspicious. The IDS has been implemented and simulated using OPNET Modeler, and verified to detect attacks. It was found that our system can detect typical attacks within a reasonable amount of delay time.

Bacteriophage Amplification-Coupled Detection and Identification of Bacterial Pathogens

NASA Astrophysics Data System (ADS)

Cox, Christopher R.; Voorhees, Kent J.

Current methods of species-specific bacterial detection and identification are complex, time-consuming, and often require expensive specialized equipment and highly trained personnel. Numerous biochemical and genotypic identification methods have been applied to bacterial characterization, but all rely on tedious microbiological culturing practices and/or costly sequencing protocols which render them impractical for deployment as rapid, cost-effective point-of-care or field detection and identification methods. With a view towards addressing these shortcomings, we have exploited the evolutionarily conserved interactions between a bacteriophage (phage) and its bacterial host to develop species-specific detection methods. Phage amplification-coupled matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to rapidly detect phage propagation resulting from species-specific in vitro bacterial infection. This novel signal amplification method allowed for bacterial detection and identification in as little as 2 h, and when combined with disulfide bond reduction methods developed in our laboratory to enhance MALDI-TOF-MS resolution, was observed to lower the limit of detection by several orders of magnitude over conventional spectroscopy and phage typing methods. Phage amplification has been combined with lateral flow immunochromatography (LFI) to develop rapid, easy-to-operate, portable, species-specific point-of-care (POC) detection devices. Prototype LFI detectors have been developed and characterized for Yersinia pestis and Bacillus anthracis, the etiologic agents of plague and anthrax, respectively. Comparable sensitivity and rapidity was observed when phage amplification was adapted to a species-specific handheld LFI detector, thus allowing for rapid, simple, POC bacterial detection and identification while eliminating the need for bacterial culturing or DNA isolation and amplification techniques.

Detecting Cognitive Stress and Impairment Using Keystroke and Linguistic Features of Typed Text: Toward a Method for Continuous Monitoring of Cognitive Status

ERIC Educational Resources Information Center

Vizer, Lisa Michele

2013-01-01

Systems that can detect cognitive decline or harmful levels of stress could assist users in managing their stress and health. However, current assessments are often obtrusive or require specialized equipment, and not suited to continuous monitoring of cognitive status. This research leverages attributes of everyday keyboard interactions to…

Mapping the Small Molecule Interactome by Mass Spectrometry.

PubMed

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

Paper-based microfluidic sensing device for label-free immunoassay demonstrated by biotin-avidin binding interaction.

PubMed

Lei, Kin Fong; Yang, Shih-I; Tsai, Shiao-Wen; Hsu, Hsiao-Ting

2015-03-01

Efficient diagnosis is very important for the prevention and treatment of diseases. Rapid disease screening in ambulatory environment is one of the most pressing needs for disease control. Despite there are many methods to detect the results of immunoassays, quantitative measurement for rapid disease screening is still a great challenge for point-of-care applications. In this study, a fabrication method for depositing carbon nanotube bundles has been successfully developed for realization of functional paper-based microfluidic sensing device. Quantitative detection of label-free immunoassay, i.e., biotin-avidin binding interaction, was demonstrated by direct measurement of the current change of the biosensor after single application of the target analyte. Sensitivity of 0.33 μA/ng mL(-1) and minimal detectable analyte concentration of 25 ng/mL were achieved. The time necessary for the detection was 500 s which is a large reduction compared with the conventional immunoassay. Such paper-based biosensor has the benefits of portability, fast response, simple operation, and low cost and has the potential for the development of rapid disease screening devices. Copyright © 2014 Elsevier B.V. All rights reserved.

Ion sensing method

DOEpatents

Smith, Richard Harding; Martin, Glenn Brian

2004-05-18

The present invention allows the determination of trace levels of ionic substances in a sample solution (ions, metal ions, and other electrically charged molecules) by coupling a separation method, such as liquid chromatography, with ion selective electrodes (ISE) prepared so as to allow detection at activities below 10.sup.-6 M. The separation method distributes constituent molecules into fractions due to unique chemical and physical properties, such as charge, hydrophobicity, specific binding interactions, or movement in an electrical field. The separated fractions are detected by means of the ISE(s). These ISEs can be used singly or in an array. Accordingly, modifications in the ISEs are used to permit detection of low activities, specifically, below 10.sup.-6 M, by using low activities of the primary analyte (the molecular species which is specifically detected) in the inner filling solution of the ISE. Arrays constructed in various ways allow flow-through sensing for multiple ions.

Relation extraction for biological pathway construction using node2vec.

PubMed

Kim, Munui; Baek, Seung Han; Song, Min

2018-06-13

Systems biology is an important field for understanding whole biological mechanisms composed of interactions between biological components. One approach for understanding complex and diverse mechanisms is to analyze biological pathways. However, because these pathways consist of important interactions and information on these interactions is disseminated in a large number of biomedical reports, text-mining techniques are essential for extracting these relationships automatically. In this study, we applied node2vec, an algorithmic framework for feature learning in networks, for relationship extraction. To this end, we extracted genes from paper abstracts using pkde4j, a text-mining tool for detecting entities and relationships. Using the extracted genes, a co-occurrence network was constructed and node2vec was used with the network to generate a latent representation. To demonstrate the efficacy of node2vec in extracting relationships between genes, performance was evaluated for gene-gene interactions involved in a type 2 diabetes pathway. Moreover, we compared the results of node2vec to those of baseline methods such as co-occurrence and DeepWalk. Node2vec outperformed existing methods in detecting relationships in the type 2 diabetes pathway, demonstrating that this method is appropriate for capturing the relatedness between pairs of biological entities involved in biological pathways. The results demonstrated that node2vec is useful for automatic pathway construction.

Study and selection of in vivo protein interactions by coupling bimolecular fluorescence complementation and flow cytometry.

PubMed

Morell, Montse; Espargaro, Alba; Aviles, Francesc Xavier; Ventura, Salvador

2008-01-01

We present a high-throughput approach to study weak protein-protein interactions by coupling bimolecular fluorescent complementation (BiFC) to flow cytometry (FC). In BiFC, the interaction partners (bait and prey) are fused to two rationally designed fragments of a fluorescent protein, which recovers its function upon the binding of the interacting proteins. For weak protein-protein interactions, the detected fluorescence is proportional to the interaction strength, thereby allowing in vivo discrimination between closely related binders with different affinity for the bait protein. FC provides a method for high-speed multiparametric data acquisition and analysis; the assay is simple, thousands of cells can be analyzed in seconds and, if required, selected using fluorescence-activated cell sorting (FACS). The combination of both methods (BiFC-FC) provides a technically straightforward, fast and highly sensitive method to validate weak protein interactions and to screen and identify optimal ligands in biologically synthesized libraries. Once plasmids encoding the protein fusions have been obtained, the evaluation of a specific interaction, the generation of a library and selection of active partners using BiFC-FC can be accomplished in 5 weeks.

Unobtrusive monitoring of computer interactions to detect cognitive status in elders.

PubMed

Jimison, Holly; Pavel, Misha; McKanna, James; Pavel, Jesse

2004-09-01

The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.

Protein-Ligand Interaction Detection with a Novel Method of Transient Induced Molecular Electronic Spectroscopy (TIMES): Experimental and Theoretical Studies.

PubMed

Zhang, Tiantian; Wei, Tao; Han, Yuanyuan; Ma, Heng; Samieegohar, Mohammadreza; Chen, Ping-Wei; Lian, Ian; Lo, Yu-Hwa

2016-11-23

Protein-ligand interaction detection without disturbances (e.g., surface immobilization, fluorescent labeling, and crystallization) presents a key question in protein chemistry and drug discovery. The emergent technology of transient induced molecular electronic spectroscopy (TIMES), which incorporates a unique design of microfluidic platform and integrated sensing electrodes, is designed to operate in a label-free and immobilization-free manner to provide crucial information for protein-ligand interactions in relevant physiological conditions. Through experiments and theoretical simulations, we demonstrate that the TIMES technique actually detects protein-ligand binding through signals generated by surface electric polarization. The accuracy and sensitivity of experiments were demonstrated by precise measurements of dissociation constant of lysozyme and N -acetyl-d-glucosamine (NAG) ligand and its trimer, NAG 3 . Computational fluid dynamics (CFD) computation is performed to demonstrate that the surface's electric polarization signal originates from the induced image charges during the transition state of surface mass transport, which is governed by the overall effects of protein concentration, hydraulic forces, and surface fouling due to protein adsorption. Hybrid atomistic molecular dynamics (MD) simulations and free energy computation show that ligand binding affects lysozyme structure and stability, producing different adsorption orientation and surface polarization to give the characteristic TIMES signals. Although the current work is focused on protein-ligand interactions, the TIMES method is a general technique that can be applied to study signals from reactions between many kinds of molecules.

A Systematic Prediction of Drug-Target Interactions Using Molecular Fingerprints and Protein Sequences.

PubMed

Huang, Yu-An; You, Zhu-Hong; Chen, Xing

2018-01-01

Drug-Target Interactions (DTI) play a crucial role in discovering new drug candidates and finding new proteins to target for drug development. Although the number of detected DTI obtained by high-throughput techniques has been increasing, the number of known DTI is still limited. On the other hand, the experimental methods for detecting the interactions among drugs and proteins are costly and inefficient. Therefore, computational approaches for predicting DTI are drawing increasing attention in recent years. In this paper, we report a novel computational model for predicting the DTI using extremely randomized trees model and protein amino acids information. More specifically, the protein sequence is represented as a Pseudo Substitution Matrix Representation (Pseudo-SMR) descriptor in which the influence of biological evolutionary information is retained. For the representation of drug molecules, a novel fingerprint feature vector is utilized to describe its substructure information. Then the DTI pair is characterized by concatenating the two vector spaces of protein sequence and drug substructure. Finally, the proposed method is explored for predicting the DTI on four benchmark datasets: Enzyme, Ion Channel, GPCRs and Nuclear Receptor. The experimental results demonstrate that this method achieves promising prediction accuracies of 89.85%, 87.87%, 82.99% and 81.67%, respectively. For further evaluation, we compared the performance of Extremely Randomized Trees model with that of the state-of-the-art Support Vector Machine classifier. And we also compared the proposed model with existing computational models, and confirmed 15 potential drug-target interactions by looking for existing databases. The experiment results show that the proposed method is feasible and promising for predicting drug-target interactions for new drug candidate screening based on sizeable features. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Efficiently detecting outlying behavior in video-game players.

PubMed

Kim, Young Bin; Kang, Shin Jin; Lee, Sang Hyeok; Jung, Jang Young; Kam, Hyeong Ryeol; Lee, Jung; Kim, Young Sun; Lee, Joonsoo; Kim, Chang Hun

2015-01-01

In this paper, we propose a method for automatically detecting the times during which game players exhibit specific behavior, such as when players commonly show excitement, concentration, immersion, and surprise. The proposed method detects such outlying behavior based on the game players' characteristics. These characteristics are captured non-invasively in a general game environment. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players (i.e., data regarding adjustments to the volume and the use of the keyboard and mouse) was used to analyze high-dimensional game-player data. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. The proposed method can also be used for feedback analysis of various interactive content provided in PC environments.

Efficiently detecting outlying behavior in video-game players

PubMed Central

Kim, Young Bin; Kang, Shin Jin; Lee, Sang Hyeok; Jung, Jang Young; Kam, Hyeong Ryeol; Lee, Jung; Kim, Young Sun; Lee, Joonsoo

2015-01-01

In this paper, we propose a method for automatically detecting the times during which game players exhibit specific behavior, such as when players commonly show excitement, concentration, immersion, and surprise. The proposed method detects such outlying behavior based on the game players’ characteristics. These characteristics are captured non-invasively in a general game environment. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players (i.e., data regarding adjustments to the volume and the use of the keyboard and mouse) was used to analyze high-dimensional game-player data. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. The proposed method can also be used for feedback analysis of various interactive content provided in PC environments. PMID:26713250

Aptamer-based microspheres for highly sensitive protein detection using fluorescently-labeled DNA nanostructures.

PubMed

Han, Daehoon; Hong, Jinkee; Kim, Hyun Cheol; Sung, Jong Hwan; Lee, Jong Bum

2013-11-01

Many highly sensitive protein detection techniques have been developed and have played an important role in the analysis of proteins. Herein, we report a novel technique that can detect proteins sensitively and effectively using aptamer-based DNA nanostructures. Thrombin was used as a target protein and aptamer was used to capture fluorescent dye-labeled DNA nanobarcodes or thrombin on a microsphere. The captured DNA nanobarcodes were replaced by a thrombin and aptamer interaction. The detection ability of this approach was confirmed by flow cytometry with different concentrations of thrombin. Our detection method has great potential for rapid and simple protein detection with a variety of aptamers.

Detection and persistence of environmental DNA from an invasive, terrestrial mammal.

PubMed

Williams, Kelly E; Huyvaert, Kathryn P; Vercauteren, Kurt C; Davis, Amy J; Piaggio, Antoinette J

2018-01-01

Invasive Sus scrofa , a species commonly referred to as wild pig or feral swine, is a destructive invasive species with a rapidly expanding distribution across the United States. We used artificial wallows and small waterers to determine the minimum amount of time needed for pig eDNA to accumulate in the water source to a detectable level. We removed water from the artificial wallows and tested eDNA detection over the course of 2 weeks to understand eDNA persistence. We show that our method is sensitive enough to detect very low quantities of eDNA shed by a terrestrial mammal that has limited interaction with water. Our experiments suggest that the number of individuals shedding into a water system can affect persistence of eDNA. Use of an eDNA detection technique can benefit management efforts by providing a sensitive method for finding even small numbers of individuals that may be elusive using other methods.

On the use of interaction error potentials for adaptive brain computer interfaces.

PubMed

Llera, A; van Gerven, M A J; Gómez, V; Jensen, O; Kappen, H J

2011-12-01

We propose an adaptive classification method for the Brain Computer Interfaces (BCI) which uses Interaction Error Potentials (IErrPs) as a reinforcement signal and adapts the classifier parameters when an error is detected. We analyze the quality of the proposed approach in relation to the misclassification of the IErrPs. In addition we compare static versus adaptive classification performance using artificial and MEG data. We show that the proposed adaptive framework significantly improves the static classification methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

Laser Interferometry Method as a Novel Tool in Endotoxins Research.

PubMed

Arabski, Michał; Wąsik, Sławomir

2017-01-01

Optical properties of chemical substances are widely used at present for assays thereof in a variety of scientific disciplines. One of the measurement techniques applied in physical sciences, with a potential for novel applications in biology, is laser interferometry. This method enables to record the diffusion properties of chemical substances. Here we describe the novel application of laser interferometry in chitosan interactions with lipopolysaccharide by detection of colistin diffusion. The proposed model could be used in simple measurements of polymer interactions with endotoxins and/or biological active compounds, like antibiotics.

Coupling functions: Universal insights into dynamical interaction mechanisms

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Pereira, Tiago; McClintock, Peter V. E.; Stefanovska, Aneta

2017-10-01

The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.

Detection of interaction articles and experimental methods in biomedical literature.

PubMed

Schneider, Gerold; Clematide, Simon; Rinaldi, Fabio

2011-10-03

This article describes the approaches taken by the OntoGene group at the University of Zurich in dealing with two tasks of the BioCreative III competition: classification of articles which contain curatable protein-protein interactions (PPI-ACT) and extraction of experimental methods (PPI-IMT). Two main achievements are described in this paper: (a) a system for document classification which crucially relies on the results of an advanced pipeline of natural language processing tools; (b) a system which is capable of detecting all experimental methods mentioned in scientific literature, and listing them with a competitive ranking (AUC iP/R > 0.5). The results of the BioCreative III shared evaluation clearly demonstrate that significant progress has been achieved in the domain of biomedical text mining in the past few years. Our own contribution, together with the results of other participants, provides evidence that natural language processing techniques have become by now an integral part of advanced text mining approaches.

Detection of cancerous cervical cells using physical adhesion of fluorescent silica particles and centripetal force

PubMed Central

Gaikwad, Ravi M.; Dokukin, Maxim E.; Iyer, K. Swaminathan; Woodworth, Craig D.; Volkov, Dmytro O.; Sokolov, Igor

2012-01-01

Here we describe a non-traditional method to identify cancerous human cervical epithelial cells in a culture dish based on physical interaction between silica beads and cells. It is a simple optical fluorescence-based technique which detects the relative difference in the amount of fluorescent silica beads physically adherent to surfaces of cancerous and normal cervical cells. The method utilizes the centripetal force gradient that occurs in a rotating culture dish. Due to the variation in the balance between adhesion and centripetal forces, cancerous and normal cells demonstrate clearly distinctive distributions of the fluorescent particles adherent to the cell surface over the culture dish. The method demonstrates higher adhesion of silica particles to normal cells compared to cancerous cells. The difference in adhesion was initially observed by atomic force microscopy (AFM). The AFM data were used to design the parameters of the rotational dish experiment. The optical method that we describe is much faster and technically simpler than AFM. This work provides proof of the concept that physical interactions can be used to accurately discriminate normal and cancer cells. PMID:21305062

Dynamical Bayesian inference of time-evolving interactions: From a pair of coupled oscillators to networks of oscillators

NASA Astrophysics Data System (ADS)

Duggento, Andrea; Stankovski, Tomislav; McClintock, Peter V. E.; Stefanovska, Aneta

2012-12-01

Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.109.024101 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

Protein associations and analytical ultracentrifugation

NASA Astrophysics Data System (ADS)

Laue, Tom

2010-03-01

Analytical ultracentrifugation (AUC) is a first principle method for characterizing the thermodynamics of macromolecules in solution. Since AUC directly assesses mass, it is particularly useful for characterizing both reversible and irreversible binding interactions between macromolecules. The principle measurement in AUC is the concentration as a function of radial position, which may be provided by either absorbance, interference or fluorescence detection. Each of these three different detectors may be used to characterize protein associations using either sedimentation equilibrium or sedimentation velocity analysis. Examples will be shown for characterizing irreversible (aggregate) formation, high-accuracy reversible association analysis, and the detection of protein interactions in complex and concentrated fluids (e.g. serum, cell cytosol).

Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome.

PubMed

Naser, Fuad J; Mahieu, Nathaniel G; Wang, Lingjue; Spalding, Jonathan L; Johnson, Stephen L; Patti, Gary J

2018-02-01

Although it is common in untargeted metabolomics to apply reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) methods that have been systematically optimized for lipids and central carbon metabolites, here we show that these established protocols provide poor coverage of semipolar metabolites because of inadequate retention. Our objective was to develop an RPLC approach that improved detection of these metabolites without sacrificing lipid coverage. We initially evaluated columns recently released by Waters under the CORTECS line by analyzing 47 small-molecule standards that evenly span the nonpolar and semipolar ranges. An RPLC method commonly used in untargeted metabolomics was considered a benchmarking reference. We found that highly nonpolar and semipolar metabolites cannot be reliably profiled with any single method because of retention and solubility limitations of the injection solvent. Instead, we optimized a multiplexed approach using the CORTECS T3 column to analyze semipolar compounds and the CORTECS C 8 column to analyze lipids. Strikingly, we determined that combining these methods allowed detection of 41 of the total 47 standards, whereas our reference RPLC method detected only 10 of the 47 standards. We then applied credentialing to compare method performance at the comprehensive scale. The tandem method showed more than a fivefold increase in credentialing coverage relative to our RPLC benchmark. Our results demonstrate that comprehensive coverage of metabolites amenable to reversed-phase separation necessitates two reconstitution solvents and chromatographic methods. Thus, we suggest complementing HILIC methods with a dual T3 and C 8 RPLC approach to increase coverage of semipolar metabolites and lipids for untargeted metabolomics. Graphical abstract Analysis of semipolar and nonpolar metabolites necessitates two reversed-phase chromatography (RPLC) methods, which extend metabolome coverage more than fivefold for untargeted profiling. HILIC hydrophilic interaction liquid chromatography.

PPARγ Pro12Ala interacts with fat intake for obesity and weight loss in a behavioural treatment based on the Mediterranean diet

PubMed Central

Garaulet, Marta; Smith, Caren E; Hernández-González, Teresa; Lee, Yu-Chi; Ordovás, Jose M.

2014-01-01

Scope The goal of this study was to examine whether the Pro12Ala polymorphism of peroxisome proliferator-activated receptor γ (PPARγ) is associated with insulin resistance, obesity and weight loss and to analyze potential interactions between fat intake and PPARγ polymorphism in a Spanish overweight/obese population. Materials and methods We recruited 1465 subjects enrolled in a behavioural treatment program for obesity based on a Mediterranean diet, which included the following: dietary treatment, physical activity, nutritional education and behavioral techniques. A significant association was found between PPARγ2 Pro12Ala genotype and plasma insulin concentration and homeostasis model assessment insulin resistance. Subjects with the Ala12 genotype had lower insulin levels than those with the Pro12Pro genotype. We detected a gene–diet interaction between the PPARγ Pro12Ala polymorphism and MUFA for BMI and body fat. Furthermore, we detected an interaction between the PPARγ Pro12Ala polymorphism and fat intake for total weight loss (p<0.001). When total fat intake was high, Ala12-carriers exhibited a significantly lower percentage of total weight loss than major-allele-carriers (p=0.037). Conclusion Data are consistent with previous results showing a protective role for the Ala12 allele against insulin resistance, and replicate an earlier study that detected an interaction between dietary MUFA and PPARγ2 for BMI. Our detection of a gene–diet interaction between PPARγ Pro12Ala and fat intake for weight loss may explain previous discrepancies among different studies. PMID:22102511

Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

2002-10-15

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Detection of electrophilic and nucleophilic chemical agents

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

McElhanon, James R.; Shepodd, Timothy J.

2014-08-12

A "real time" method for detecting chemical agents generally and particularly electrophilic and nucleophilic species by employing tunable, precursor sensor materials that mimic the physiological interaction of these agents to form highly florescent berberine-type alkaloids that can be easily and rapidly detected. These novel precursor sensor materials can be tuned for reaction with both electrophilic (chemical species, toxins) and nucleophilic (proteins and other biological molecules) species. By bonding or otherwise attaching these precursor molecules to a surface or substrate they can be used in numerous applications.

Oil-particle interactions and submergence from crude oil spills in marine and freshwater environments: review of the science and future research needs

USGS Publications Warehouse

Fitzpatrick, Faith A.; Boufadel, Michael C.; Johnson, Rex; Lee, Kenneth W.; Graan, Thomas P.; Bejarano, Adriana C.; Zhu, Zhenduo; Waterman, David; Capone, Daniel M.; Hayter, Earl; Hamilton, Stephen K.; Dekker, Timothy; Garcia, Marcelo H.; Hassan, Jacob S.

2015-01-01

Although much is known about oil-particle interactions in coastal marine environments, there remains a need for additional science on methods to detect and quantify the presence of OPAs and to understand their effects on containment and recovery of oil spilled under various temperature regimes and in different aquatic habitats including freshwater environments.

Determining rotational dynamics of the guanidino group of arginine side chains in proteins by carbon-detected NMR.

PubMed

Gerecht, Karola; Figueiredo, Angelo Miguel; Hansen, D Flemming

2017-09-16

Arginine residues are imperative for many active sites and protein-interaction interfaces. A new NMR-based method is presented to determine the rotational dynamics around the N ε -C ζ bond of arginine side chains. An application to a 19 kDa protein shows that the strengths of interactions involving arginine side chains can be characterised.

In-situ characterization of nanoparticle beams focused with an aerodynamic lens by Laser-Induced Breakdown Detection

PubMed Central

Barreda, F.-A.; Nicolas, C.; Sirven, J.-B.; Ouf, F.-X.; Lacour, J.-L.; Robert, E.; Benkoula, S.; Yon, J.; Miron, C.; Sublemontier, O.

2015-01-01

The Laser-Induced Breakdown Detection technique (LIBD) was adapted to achieve fast in-situ characterization of nanoparticle beams focused under vacuum by an aerodynamic lens. The method employs a tightly focused, 21 μm, scanning laser microprobe which generates a local plasma induced by the laser interaction with a single particle. A counting mode optical detection allows the achievement of 2D mappings of the nanoparticle beams with a reduced analysis time thanks to the use of a high repetition rate infrared pulsed laser. As an example, the results obtained with Tryptophan nanoparticles are presented and the advantages of this method over existing ones are discussed. PMID:26498694

Optical and electrical nano eco-sensors using alternative deposition of charged layer

NASA Astrophysics Data System (ADS)

Ahmed, Syed Rahin; Hong, Seong Cheol; Lee, Jaebeom

2011-03-01

This review focuses on layer by layer (LBL) assembly-based nano ecological sensor (hereafter, eco-sensor) for pesticide detection, which is one of the most versatile methods. The effects of pesticides on human health and on the environment (air, water, soil, plants, and animals) are of great concern due to their increasing use. We highlight two of the most popular detecting methods, i.e., fluorescence and electrochemical detection of pesticides on an LBL assembly. Fluorescence materials are of great interest among researchers for their sensitivity and reliable detection, and electrochemical processes allow us to investigate synergistic interactions among film components through charge transfer mechanisms in LBL film at the molecular level. Then, we noted some prospective directions for development of different types of sensing systems.

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature.

PubMed

Wang, Xinglong; Rak, Rafal; Restificar, Angelo; Nobata, Chikashi; Rupp, C J; Batista-Navarro, Riza Theresa B; Nawaz, Raheel; Ananiadou, Sophia

2011-10-03

The selection of relevant articles for curation, and linking those articles to experimental techniques confirming the findings became one of the primary subjects of the recent BioCreative III contest. The contest's Protein-Protein Interaction (PPI) task consisted of two sub-tasks: Article Classification Task (ACT) and Interaction Method Task (IMT). ACT aimed to automatically select relevant documents for PPI curation, whereas the goal of IMT was to recognise the methods used in experiments for identifying the interactions in full-text articles. We proposed and compared several classification-based methods for both tasks, employing rich contextual features as well as features extracted from external knowledge sources. For IMT, a new method that classifies pair-wise relations between every text phrase and candidate interaction method obtained promising results with an F1 score of 64.49%, as tested on the task's development dataset. We also explored ways to combine this new approach and more conventional, multi-label document classification methods. For ACT, our classifiers exploited automatically detected named entities and other linguistic information. The evaluation results on the BioCreative III PPI test datasets showed that our systems were very competitive: one of our IMT methods yielded the best performance among all participants, as measured by F1 score, Matthew's Correlation Coefficient and AUC iP/R; whereas for ACT, our best classifier was ranked second as measured by AUC iP/R, and also competitive according to other metrics. Our novel approach that converts the multi-class, multi-label classification problem to a binary classification problem showed much promise in IMT. Nevertheless, on the test dataset the best performance was achieved by taking the union of the output of this method and that of a multi-class, multi-label document classifier, which indicates that the two types of systems complement each other in terms of recall. For ACT, our system exploited a rich set of features and also obtained encouraging results. We examined the features with respect to their contributions to the classification results, and concluded that contextual words surrounding named entities, as well as the MeSH headings associated with the documents were among the main contributors to the performance.

Methylsorb: a simple method for quantifying DNA methylation using DNA-gold affinity interactions.

PubMed

Sina, Abu Ali Ibn; Carrascosa, Laura G; Palanisamy, Ramkumar; Rauf, Sakandar; Shiddiky, Muhammad J A; Trau, Matt

2014-10-21

The analysis of DNA methylation is becoming increasingly important both in the clinic and also as a research tool to unravel key epigenetic molecular mechanisms in biology. Current methodologies for the quantification of regional DNA methylation (i.e., the average methylation over a region of DNA in the genome) are largely affected by comprehensive DNA sequencing methodologies which tend to be expensive, tedious, and time-consuming for many applications. Herein, we report an alternative DNA methylation detection method referred to as "Methylsorb", which is based on the inherent affinity of DNA bases to the gold surface (i.e., the trend of the affinity interactions is adenine > cytosine ≥ guanine > thymine).1 Since the degree of gold-DNA affinity interaction is highly sequence dependent, it provides a new capability to detect DNA methylation by simply monitoring the relative adsorption of bisulfite treated DNA sequences onto a gold chip. Because the selective physical adsorption of DNA fragments to gold enable a direct read-out of regional DNA methylation, the current requirement for DNA sequencing is obviated. To demonstrate the utility of this method, we present data on the regional methylation status of two CpG clusters located in the EN1 and MIR200B genes in MCF7 and MDA-MB-231 cells. The methylation status of these regions was obtained from the change in relative mass on gold surface with respect to relative adsorption of an unmethylated DNA source and this was detected using surface plasmon resonance (SPR) in a label-free and real-time manner. We anticipate that the simplicity of this method, combined with the high level of accuracy for identifying the methylation status of cytosines in DNA, could find broad application in biology and diagnostics.

Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance.

PubMed

Farkhatdinov, Ildar; Roehri, Nicolas; Burdet, Etienne

2017-09-26

Many wearable lower-limb robots for walking assistance have been developed in recent years. However, it remains unclear how they can be commanded in an intuitive and efficient way by their user. In particular, providing robotic assistance to neurologically impaired individuals in turning remains a significant challenge. The control should be safe to the users and their environment, yet yield sufficient performance and enable natural human-machine interaction. Here, we propose using the head and trunk anticipatory behaviour in order to detect the intention to turn in a natural, non-intrusive way, and use it for triggering turning movement in a robot for walking assistance. We therefore study head and trunk orientation during locomotion of healthy adults, and investigate upper body anticipatory behaviour during turning. The collected walking and turning kinematics data are clustered using the k-means algorithm and cross-validation tests and k-nearest neighbours method are used to evaluate the performance of turning detection during locomotion. Tests with seven subjects exhibited accurate turning detection. Head anticipated turning by more than 400-500 ms in average across all subjects. Overall, the proposed method detected turning 300 ms after its initiation and 1230 ms before the turning movement was completed. Using head anticipatory behaviour enabled to detect turning faster by about 100 ms, compared to turning detection using only pelvis orientation measurements. Finally, it was demonstrated that the proposed turning detection can improve the quality of human-robot interaction by improving the control accuracy and transparency.

IP-FCM measures physiologic protein-protein interactions modulated by signal transduction and small-molecule drug inhibition.

PubMed

Smith, Stephen E P; Bida, Anya T; Davis, Tessa R; Sicotte, Hugues; Patterson, Steven E; Gil, Diana; Schrum, Adam G

2012-01-01

Protein-protein interactions (PPI) mediate the formation of intermolecular networks that control biological signaling. For this reason, PPIs are of outstanding interest in pharmacology, as they display high specificity and may represent a vast pool of potentially druggable targets. However, the study of physiologic PPIs can be limited by conventional assays that often have large sample requirements and relatively low sensitivity. Here, we build on a novel method, immunoprecipitation detected by flow cytometry (IP-FCM), to assess PPI modulation during either signal transduction or pharmacologic inhibition by two different classes of small-molecule compounds. First, we showed that IP-FCM can detect statistically significant differences in samples possessing a defined PPI change as low as 10%. This sensitivity allowed IP-FCM to detect a PPI that increases transiently during T cell signaling, the antigen-inducible interaction between ZAP70 and the T cell antigen receptor (TCR)/CD3 complex. In contrast, IP-FCM detected no ZAP70 recruitment when T cells were stimulated with antigen in the presence of the src-family kinase inhibitor, PP2. Further, we tested whether IP-FCM possessed sufficient sensitivity to detect the effect of a second, rare class of compounds called SMIPPI (small-molecule inhibitor of PPI). We found that the first-generation non-optimized SMIPPI, Ro-26-4550, inhibited the IL-2:CD25 interaction detected by IP-FCM. This inhibition was detectable using either a recombinant CD25-Fc chimera or physiologic full-length CD25 captured from T cell lysates. Thus, we demonstrate that IP-FCM is a sensitive tool for measuring physiologic PPIs that are modulated by signal transduction and pharmacologic inhibition.

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text.

PubMed

Krallinger, Martin; Vazquez, Miguel; Leitner, Florian; Salgado, David; Chatr-Aryamontri, Andrew; Winter, Andrew; Perfetto, Livia; Briganti, Leonardo; Licata, Luana; Iannuccelli, Marta; Castagnoli, Luisa; Cesareni, Gianni; Tyers, Mike; Schneider, Gerold; Rinaldi, Fabio; Leaman, Robert; Gonzalez, Graciela; Matos, Sergio; Kim, Sun; Wilbur, W John; Rocha, Luis; Shatkay, Hagit; Tendulkar, Ashish V; Agarwal, Shashank; Liu, Feifan; Wang, Xinglong; Rak, Rafal; Noto, Keith; Elkan, Charles; Lu, Zhiyong; Dogan, Rezarta Islamaj; Fontaine, Jean-Fred; Andrade-Navarro, Miguel A; Valencia, Alfonso

2011-10-03

Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53%, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35%) the macro-averaged precision ranged between 50% and 80%, with a maximum F-Score of 55%. The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows.

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

PubMed Central

2011-01-01

Background Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. Results A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53%, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35%) the macro-averaged precision ranged between 50% and 80%, with a maximum F-Score of 55%. Conclusions The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows. PMID:22151929

Violent Interaction Detection in Video Based on Deep Learning

NASA Astrophysics Data System (ADS)

Zhou, Peipei; Ding, Qinghai; Luo, Haibo; Hou, Xinglin

2017-06-01

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

Pelvic artery calcification detection on CT scans using convolutional neural networks

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Lu, Le; Yao, Jianhua; Bagheri, Mohammadhadi; Summers, Ronald M.

2017-03-01

Artery calcification is observed commonly in elderly patients, especially in patients with chronic kidney disease, and may affect coronary, carotid and peripheral arteries. Vascular calcification has been associated with many clinical outcomes. Manual identification of calcification in CT scans requires substantial expert interaction, which makes it time-consuming and infeasible for large-scale studies. Many works have been proposed for coronary artery calcification detection in cardiac CT scans. In these works, coronary artery extraction is commonly required for calcification detection. However, there are few works about abdominal or pelvic artery calcification detection. In this work, we present a method for automatic pelvic artery calcification detection on CT scan. This method uses the recent advanced faster region-based convolutional neural network (R-CNN) to directly identify artery calcification without a need for artery extraction since pelvic artery extraction itself is challenging. Our method first generates category-independent region proposals for each slice of the input CT scan using region proposal networks (RPN). Then, each region proposal is jointly classified and refined by softmax classifier and bounding box regressor. We applied the detection method to 500 images from 20 CT scans of patients for evaluation. The detection system achieved a 77.4% average precision and a 85% sensitivity at 1 false positive per image.

Surface-enhanced Raman spectroscopy detection of polybrominated diphenylethers using a portable Raman spectrometer.

PubMed

Jiang, Xiaohong; Lai, Yongchao; Wang, Wei; Jiang, Wei; Zhan, Jinhua

2013-11-15

Polybrominated diphenylethers (PBDEs), one of the most common brominated flame retardants, are toxic and persistent, generally detected by the chromatographic method. In this work, qualitative and quantitative detection of PBDEs were explored based on surface-enhanced Raman spectroscopy (SERS) technique using a portable Raman spectrometer. Alkanethiol modified silver nanoparticle aggregates were used as the substrate and PBDEs could be pre-concentrated close to the substrate surface through their hydrophobic interactions with alkanethiol. The effect of alkanethiols with different chain length on the SERS detection of PBDEs was evaluated. It was shown that 1-hexanethiol (HT) modified substrate has higher sensitivity, good stability and reusability. Qualitative and quantitative SERS detection of PBDEs in real sea water was accomplished, with the measured detection limits at 1.2×10(2) μg L(-1). These results illustrate SERS could be used as an effective method for the detection of PBDEs. Copyright © 2013 Elsevier B.V. All rights reserved.

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

Apparatuses for large area radiation detection and related method

DOEpatents

Akers, Douglas W; Drigert, Mark W

2015-04-28

Apparatuses and a related method relating to radiation detection are disclosed. In one embodiment, an apparatus includes a first scintillator and a second scintillator adjacent to the first scintillator, with each of the first scintillator and second scintillator being structured to generate a light pulse responsive to interacting with incident radiation. The first scintillator is further structured to experience full energy deposition of a first low-energy radiation, and permit a second higher-energy radiation to pass therethrough and interact with the second scintillator. The apparatus further includes a plurality of light-to-electrical converters operably coupled to the second scintillator and configured to convert light pulses generated by the first scintillator and the second scintillator into electrical signals. The first scintillator and the second scintillator exhibit at least one mutually different characteristic for an electronic system to determine whether a given light pulse is generated by the first scintillator or the second scintillator.

Method, apparatus and system for low-energy beta particle detection

DOEpatents

Akers, Douglas W.; Drigert, Mark W.

2012-09-25

An apparatus, method, and system relating to radiation detection of low-energy beta particles are disclosed. An embodiment includes a radiation detector with a first scintillator and a second scintillator operably coupled to each other. The first scintillator and the second scintillator are each structured to generate a light pulse responsive to interaction with beta particles. The first scintillator is structured to experience full energy deposition of low-energy beta particles, and permit a higher-energy beta particle to pass therethrough and interact with the second scintillator. The radiation detector further includes a light-to-electrical converter operably coupled to the second scintillator and configured to convert light pulses generated by the first scintillator and the second scintillator into electrical signals. The first scintillator and the second scintillator have at least one mutually different characteristic to enable an electronic system to determine whether a given light pulse is generated in the first scintillator or the second scintillator.

a Probabilistic Embedding Clustering Method for Urban Structure Detection

NASA Astrophysics Data System (ADS)

Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

2017-09-01

Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

Quick and simple estimation of bacteria using a fluorescent paracetamol dimer-Au nanoparticle composite

NASA Astrophysics Data System (ADS)

Sahoo, Amaresh Kumar; Sharma, Shilpa; Chattopadhyay, Arun; Ghosh, Siddhartha Sankar

2012-02-01

Rapid, simple and sensitive detection of bacterial contamination is critical for safeguarding public health and the environment. Herein, we report an easy method of detection as well as enumeration of the bacterial cell number on the basis of fluorescence quenching of a non-antibacterial fluorescent nanocomposite, consisting of paracetamol dimer (PD) and Au nanoparticles (NPs), in the presence of bacteria. The composite was synthesized by reaction of paracetamol (p-hydroxyacetanilide) with HAuCl4. The Au NPs of the composite were characterized using UV-Vis spectroscopy, transmission electron microscopy (TEM), X-ray diffraction and selected area electron diffraction analysis. The paracetamol dimer in the composite showed emission peak at 435 nm when excited at 320 nm. The method successfully detected six bacterial strains with a sensitivity of 100 CFU mL-1. The Gram-positive and Gram-negative bacteria quenched the fluorescence of the composite differently, making it possible to distinguish between the two. The TEM analysis showed interaction of the composite with bacteria without any apparent damage to the bacteria. The chi-square test established the accuracy of the method. Quick, non-specific and highly sensitive detection of bacteria over a broad range of logarithmic dilutions within a short span of time demonstrates the potential of this method as an alternative to conventional methods.Rapid, simple and sensitive detection of bacterial contamination is critical for safeguarding public health and the environment. Herein, we report an easy method of detection as well as enumeration of the bacterial cell number on the basis of fluorescence quenching of a non-antibacterial fluorescent nanocomposite, consisting of paracetamol dimer (PD) and Au nanoparticles (NPs), in the presence of bacteria. The composite was synthesized by reaction of paracetamol (p-hydroxyacetanilide) with HAuCl4. The Au NPs of the composite were characterized using UV-Vis spectroscopy, transmission electron microscopy (TEM), X-ray diffraction and selected area electron diffraction analysis. The paracetamol dimer in the composite showed emission peak at 435 nm when excited at 320 nm. The method successfully detected six bacterial strains with a sensitivity of 100 CFU mL-1. The Gram-positive and Gram-negative bacteria quenched the fluorescence of the composite differently, making it possible to distinguish between the two. The TEM analysis showed interaction of the composite with bacteria without any apparent damage to the bacteria. The chi-square test established the accuracy of the method. Quick, non-specific and highly sensitive detection of bacteria over a broad range of logarithmic dilutions within a short span of time demonstrates the potential of this method as an alternative to conventional methods. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr11837h

Use of UV-vis-NIR spectroscopy to monitor label-free interaction between molecular recognition elements and erythropoietin on a gold-coated polycarbonate platform.

PubMed

Citartan, Marimuthu; Gopinath, Subash C B; Tominaga, Junji; Chen, Yeng; Tang, Thean-Hock

2014-08-01

Label-free-based detection is pivotal for real-time monitoring of biomolecular interactions and to eliminate the need for labeling with tags that can occupy important binding sites of biomolecules. One simplest form of label-free-based detection is ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopy, which measure changes in reflectivity as a means to monitor immobilization and interaction of biomolecules with their corresponding partners. In biosensor development, the platform used for the biomolecular interaction should be suitable for different molecular recognition elements. In this study, gold (Au)-coated polycarbonate was used as a platform and as a proof-of-concept, erythropoietin (EPO), a doping substance widely abused by the athletes was used as the target. The interaction of EPO with its corresponding molecular recognition elements (anti-EPO monoclonal antibody and anti-EPO DNA aptamer) is monitored by UV-vis-NIR spectroscopy. Prior to this, to show that UV-vis-NIR spectroscopy is a suitable method for measuring biomolecular interaction, the interaction between biotin and streptavidin was demonstrated via this strategy and reflectivity of this interaction decreased by 25%. Subsequent to this, interaction of the EPO with anti-EPO monoclonal antibody and anti-EPO DNA aptamer resulted in the decrease of reflectivity by 5% and 10%, respectively. The results indicated that Au-coated polycarbonate could be an ideal biosensor platform for monitoring biomolecular interactions using UV-vis-NIR spectroscopy. A smaller version of the Au-coated polycarbonate substrates can be derived from the recent set-up, to be applied towards detecting EPO abuse among atheletes. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative blood group typing using surface plasmon resonance.

PubMed

Then, Whui Lyn; Aguilar, Marie-Isabel; Garnier, Gil

2015-11-15

The accurate and reliable typing of blood groups is essential prior to blood transfusion. While current blood typing methods are well established, results are subjective and heavily reliant on analysis by trained personnel. Techniques for quantifying blood group antibody-antigen interactions are also very limited. Many biosensing systems rely on surface plasmon resonance (SPR) detection to quantify biomolecular interactions. While SPR has been widely used for characterizing antibody-antigen interactions, measuring antibody interactions with whole cells is significantly less common. Previous studies utilized SPR for blood group antigen detection, however, showed poor regeneration causing loss of functionality after a single use. In this study, a fully regenerable, multi-functional platform for quantitative blood group typing via SPR detection is achieved by immobilizing anti-human IgG antibody to the sensor surface, which binds to the Fc region of human IgG antibodies. The surface becomes an interchangeable platform capable of quantifying the blood group interactions between red blood cells (RBCs) and IgG antibodies. As with indirect antiglobulin tests (IAT), which use IgG antibodies for detection, IgG antibodies are initially incubated with RBCs. This facilitates binding to the immobilized monolayer and allows for quantitative blood group detection. Using the D-antigen as an example, a clear distinction between positive (>500 RU) and negative (<100 RU) RBCs is achieved using anti-D IgG. Complete regeneration of the anti-human IgG surface is also successful, showing negligible degradation of the surface after more than 100 regenerations. This novel approach is validated with human-sourced whole blood samples to demonstrate an interesting alternative for quantitative blood grouping using SPR analysis. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Highly sensitive electrochemical detection of human telomerase activity based on bio-barcode method.

PubMed

Li, Ying; Liu, Bangwei; Li, Xia; Wei, Qingli

2010-07-15

In the present study, an electrochemical method for highly sensitive detection of human telomerase activity was developed based on bio-barcode amplification assay. Telomerase was extracted from HeLa cells, then the extract was mixed with telomerase substrate (TS) primer to perform extension reaction. The extension product was hybridized with the capture DNA immobilized on the Au electrode and then reacted with the signal DNA on Au nanoparticles to form a sandwich hybridization mode. Electrochemical signals were generated by chronocoulometric interrogation of [Ru(NH(3))(6)](3+) that quantitatively binds to the DNA on Au nanoparticles via electrostatic interaction. This method can detect the telomerase activity from as little as 10 cultured cancer cells without the polymerase chain reaction (PCR) amplification of telomerase extension product. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Single particle electrochemical sensors and methods of utilization

DOEpatents

Schoeniger, Joseph [Oakland, CA; Flounders, Albert W [Berkeley, CA; Hughes, Robert C [Albuquerque, NM; Ricco, Antonio J [Los Gatos, CA; Wally, Karl [Lafayette, CA; Kravitz, Stanley H [Placitas, NM; Janek, Richard P [Oakland, CA

2006-04-04

The present invention discloses an electrochemical device for detecting single particles, and methods for using such a device to achieve high sensitivity for detecting particles such as bacteria, viruses, aggregates, immuno-complexes, molecules, or ionic species. The device provides for affinity-based electrochemical detection of particles with single-particle sensitivity. The disclosed device and methods are based on microelectrodes with surface-attached, affinity ligands (e.g., antibodies, combinatorial peptides, glycolipids) that bind selectively to some target particle species. The electrodes electrolyze chemical species present in the particle-containing solution, and particle interaction with a sensor element modulates its electrolytic activity. The devices may be used individually, employed as sensors, used in arrays for a single specific type of particle or for a range of particle types, or configured into arrays of sensors having both these attributes.

Optimizing occupancy surveys by maximizing detection probability: application to amphibian monitoring in the Mediterranean region.

PubMed

Petitot, Maud; Manceau, Nicolas; Geniez, Philippe; Besnard, Aurélien

2014-09-01

Setting up effective conservation strategies requires the precise determination of the targeted species' distribution area and, if possible, its local abundance. However, detection issues make these objectives complex for most vertebrates. The detection probability is usually <1 and is highly dependent on species phenology and other environmental variables. The aim of this study was to define an optimized survey protocol for the Mediterranean amphibian community, that is, to determine the most favorable periods and the most effective sampling techniques for detecting all species present on a site in a minimum number of field sessions and a minimum amount of prospecting effort. We visited 49 ponds located in the Languedoc region of southern France on four occasions between February and June 2011. Amphibians were detected using three methods: nighttime call count, nighttime visual encounter, and daytime netting. The detection nondetection data obtained was then modeled using site-occupancy models. The detection probability of amphibians sharply differed between species, the survey method used and the date of the survey. These three covariates also interacted. Thus, a minimum of three visits spread over the breeding season, using a combination of all three survey methods, is needed to reach a 95% detection level for all species in the Mediterranean region. Synthesis and applications: detection nondetection surveys combined to site occupancy modeling approach are powerful methods that can be used to estimate the detection probability and to determine the prospecting effort necessary to assert that a species is absent from a site.

BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.

PubMed

Wei, Qing; La, David; Kihara, Daisuke

2017-01-01

Prediction of protein-protein interaction sites in a protein structure provides important information for elucidating the mechanism of protein function and can also be useful in guiding a modeling or design procedures of protein complex structures. Since prediction methods essentially assess the propensity of amino acids that are likely to be part of a protein docking interface, they can help in designing protein-protein interactions. Here, we introduce BindML and BindML+ protein-protein interaction sites prediction methods. BindML predicts protein-protein interaction sites by identifying mutation patterns found in known protein-protein complexes using phylogenetic substitution models. BindML+ is an extension of BindML for distinguishing permanent and transient types of protein-protein interaction sites. We developed an interactive web-server that provides a convenient interface to assist in structural visualization of protein-protein interactions site predictions. The input data for the web-server are a tertiary structure of interest. BindML and BindML+ are available at http://kiharalab.org/bindml/ and http://kiharalab.org/bindml/plus/ .

The in Silico Insight into Carbon Nanotube and Nucleic Acid Bases Interaction.

PubMed

Karimi, Ali Asghar; Ghalandari, Behafarid; Tabatabaie, Seyed Saleh; Farhadi, Mohammad

2016-05-01

To explore practical applications of carbon nanotubes (CNTs) in biomedical fields the properties of their interaction with biomolecules must be revealed. Recent years, the interaction of CNTs with biomolecules is a subject of research interest for practical applications so that previous research explored that CNTs have complementary structure properties with single strand DNA (ssDNA). Hence, the quantum mechanics (QM) method based on ab initio was used for this purpose. Therefore values of binding energy, charge distribution, electronic energy and other physical properties of interaction were studied for interaction of nucleic acid bases and SCNT. In this study, the interaction between nucleic acid bases and a (4, 4) single-walled carbon nanotube (SCNT) were investigated through calculations within quantum mechanics (QM) method at theoretical level of Hartree-Fock (HF) method using 6-31G basis set. Hence, the physical properties such as electronic energy, total dipole moment, charge distributions and binding energy of nucleic acid bases interaction with SCNT were investigated based on HF method. It has been found that the guanine base adsorption is bound stronger to the outer surface of nanotube in comparison to the other bases, consistent with the recent theoretical studies. In the other words, the results explored that guanine interaction with SCNT has optimum level of electronic energy so that their interaction is stable. Also, the calculations illustrated that SCNT interact to nucleic acid bases by noncovalent interaction because of charge distribution an electrostatic area is created in place of interaction. Consequently, small diameter SCNT interaction with nucleic acid bases is noncovalent. Also, the results revealed that small diameter SCNT interaction especially SCNT (4, 4) with nucleic acid bases can be useful in practical application area of biomedical fields such detection and drug delivery.

Target-specific NMR detection of protein-ligand interactions with antibody-relayed 15N-group selective STD.

PubMed

Hetényi, Anasztázia; Hegedűs, Zsófia; Fajka-Boja, Roberta; Monostori, Éva; Kövér, Katalin E; Martinek, Tamás A

2016-12-01

Fragment-based drug design has been successfully applied to challenging targets where the detection of the weak protein-ligand interactions is a key element. 1 H saturation transfer difference (STD) NMR spectroscopy is a powerful technique for this work but it requires pure homogeneous proteins as targets. Monoclonal antibody (mAb)-relayed 15 N-GS STD spectroscopy has been developed to resolve the problem of protein mixtures and impure proteins. A 15 N-labelled target-specific mAb is selectively irradiated and the saturation is relayed through the target to the ligand. Tests on the anti-Gal-1 mAb/Gal-1/lactose system showed that the approach is experimentally feasible in a reasonable time frame. This method allows detection and identification of binding molecules directly from a protein mixture in a multicomponent system.

Superfluid quenching of the moment of inertia in a strongly interacting Fermi gas

NASA Astrophysics Data System (ADS)

Riedl, S.; Sánchez Guajardo, E. R.; Kohstall, C.; Hecker Denschlag, J.; Grimm, R.

2011-03-01

We report on the observation of a quenched moment of inertia resulting from superfluidity in a strongly interacting Fermi gas. Our method is based on setting the hydrodynamic gas in slow rotation and determining its angular momentum by detecting the precession of a radial quadrupole excitation. The measurements distinguish between the superfluid and collisional origins of hydrodynamic behavior, and show the phase transition.

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

NASA Astrophysics Data System (ADS)

Liang, Lijiao; Zhen, Shujun; Huang, Chengzhi

2017-02-01

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

Single column comprehensive analysis of pharmaceutical preparations using dual-injection mixed-mode (ion-exchange and reversed-phase) and hydrophilic interaction liquid chromatography.

PubMed

Kazarian, Artaches A; Taylor, Mark R; Haddad, Paul R; Nesterenko, Pavel N; Paull, Brett

2013-12-01

The comprehensive separation and detection of hydrophobic and hydrophilic active pharmaceutical ingredients (APIs), their counter-ions (organic, inorganic) and excipients, using a single mixed-mode chromatographic column, and a dual injection approach is presented. Using a mixed-mode Thermo Fisher Acclaim Trinity P1 column, APIs, their counter-ions and possible degradants were first separated using a combination of anion-exchange, cation-exchange and hydrophobic interactions, using a mobile phase consisting of a dual organic modifier/salt concentration gradient. A complementary method was also developed using the same column for the separation of hydrophilic bulk excipients, using hydrophilic interaction liquid chromatography (HILIC) under high organic solvent mobile phase conditions. These two methods were then combined within a single gradient run using dual sample injection, with the first injection at the start of the applied gradient (mixed-mode retention of solutes), followed by a second sample injection at the end of the gradient (HILIC retention of solutes). Detection using both ultraviolet absorbance and refractive index enabled the sensitive detection of APIs and UV-absorbing counter-ions, together with quantitative determination of bulk excipients. The developed approach was applied successfully to the analysis of a dry powder inhalers (Flixotide(®), Spiriva(®)), enabling comprehensive quantification of all APIs and excipients in the sample. Copyright © 2013 Elsevier B.V. All rights reserved.

Information-Theoretic Metrics for Visualizing Gene-Environment Interactions

PubMed Central

Chanda, Pritam ; Zhang, Aidong ; Brazeau, Daniel ; Sucheston, Lara ; Freudenheim, Jo L. ; Ambrosone, Christine ; Ramanathan, Murali 

2007-01-01

The purpose of our work was to develop heuristics for visualizing and interpreting gene-environment interactions (GEIs) and to assess the dependence of candidate visualization metrics on biological and study-design factors. Two information-theoretic metrics, the k-way interaction information (KWII) and the total correlation information (TCI), were investigated. The effectiveness of the KWII and TCI to detect GEIs in a diverse range of simulated data sets and a Crohn disease data set was assessed. The sensitivity of the KWII and TCI spectra to biological and study-design variables was determined. Head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and the pedigree disequilibrium test (PDT) methods were obtained. The KWII and TCI spectra, which are graphical summaries of the KWII and TCI for each subset of environmental and genotype variables, were found to detect each known GEI in the simulated data sets. The patterns in the KWII and TCI spectra were informative for factors such as case-control misassignment, locus heterogeneity, allele frequencies, and linkage disequilibrium. The KWII and TCI spectra were found to have excellent sensitivity for identifying the key disease-associated genetic variations in the Crohn disease data set. In head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and PDT methods, the results from visual interpretation of the KWII and TCI spectra performed satisfactorily. The KWII and TCI are promising metrics for visualizing GEIs. They are capable of detecting interactions among numerous single-nucleotide polymorphisms and environmental variables for a diverse range of GEI models. PMID:17924337

Investigation of sorption interactions between oil shale principal mineral phases and organic compounds

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

Bowen, J.M.

1988-09-01

The interactions between minerals representative of the bulk composition of oil shales and organic compounds that have been found in oil shale leachates were investigated. The method used to directly determine the type of interactions that could take place between organic compounds and oil shale mineral phases was Fourier transform infrared spectroscopy (FTIR) using several advanced detection methods, including diffuse reflectance (DRIFT) and photoacoustics (PAS). The minerals that were investigated include quartz, calcite, and dolomite, which are known to figure significantly in the composition of processed oil shales. The organic chemical compounds used were chosen from a list of compoundsmore » identified in spent oil shale leachates, and they include pyridine, phenol, p-cresol, and acetone. The sorption interactions for the study were prepared by exposing each of the minerals to the organic compounds by three different methods. These were vapor deposition, direct application, and immersion in an aqueous solution at pH 12. 41 refs., 3 figs., 4 tabs.« less

Online two-stage association method for robust multiple people tracking

NASA Astrophysics Data System (ADS)

Lv, Jingqin; Fang, Jiangxiong; Yang, Jie

2011-07-01

Robust multiple people tracking is very important for many applications. It is a challenging problem due to occlusion and interaction in crowded scenarios. This paper proposes an online two-stage association method for robust multiple people tracking. In the first stage, short tracklets generated by linking people detection responses grow longer by particle filter based tracking, with detection confidence embedded into the observation model. And, an examining scheme runs at each frame for the reliability of tracking. In the second stage, multiple people tracking is achieved by linking tracklets to generate trajectories. An online tracklet association method is proposed to solve the linking problem, which allows applications in time-critical scenarios. This method is evaluated on the popular CAVIAR dataset. The experimental results show that our two-stage method is robust.

Detection of substrate binding of a collagen-specific molecular chaperone HSP47 in solution using fluorescence correlation spectroscopy.

PubMed

Kitamura, Akira; Ishida, Yoshihito; Kubota, Hiroshi; Pack, Chan-Gi; Homma, Takayuki; Ito, Shinya; Araki, Kazutaka; Kinjo, Masataka; Nagata, Kazuhiro

2018-02-26

Heat shock protein 47 kDa (HSP47), an ER-resident and collagen-specific molecular chaperone, recognizes collagenous hydrophobic amino acid sequences (Gly-Pro-Hyp) and assists in secretion of correctly folded collagen. Elevated collagen production is correlated with HSP47 expression in various diseases, including fibrosis and keloid. HSP47 knockdown ameliorates liver fibrosis by inhibiting collagen secretion, and inhibition of the interaction of HSP47 with procollagen also prevents collagen secretion. Therefore, a high-throughput system for screening of drugs capable of inhibiting the interaction between HSP47 and collagen would aid the development of novel therapies for fibrotic diseases. In this study, we established a straightforward method for rapidly and quantitatively measuring the interaction between HSP47 and collagen in solution using fluorescence correlation spectroscopy (FCS). The diffusion rate of HSP47 labeled with Alexa Fluor 488 (HSP47-AF), a green fluorescent dye, decreased upon addition of type I or III collagen, whereas that of dye-labeled protein disulfide isomerase (PDI) or bovine serum albumin (BSA) did not, indicating that specific binding of HSP47 to collagen could be detected using FCS. Using this method, we calculated the dissociation constant of the interaction between HSP47 and collagen. The binding ratio between HSP47-AF and collagen did not change in the presence of sodium chloride, confirming that the interaction was hydrophobic in nature. In addition, we observed dissociation of collagen from HSP47 at low pH and re-association after recovery to neutral pH. These observations indicate that this system is appropriate for detecting the interaction between HSP47 and collagen, and could be applied to high-throughput screening for drugs capable of suppressing and/or curing fibrosis. Copyright © 2018 Elsevier Inc. All rights reserved.

A New Method, "Reverse Yeast Two-Hybrid Array" (RYTHA), Identifies Mutants that Dissociate the Physical Interaction Between Elg1 and Slx5.

PubMed

Lev, Ifat; Shemesh, Keren; Volpe, Marina; Sau, Soumitra; Levinton, Nelly; Molco, Maya; Singh, Shivani; Liefshitz, Batia; Ben Aroya, Shay; Kupiec, Martin

2017-07-01

The vast majority of processes within the cell are carried out by proteins working in conjunction. The Yeast Two-Hybrid (Y2H) methodology allows the detection of physical interactions between any two interacting proteins. Here, we describe a novel systematic genetic methodology, "Reverse Yeast Two-Hybrid Array" (RYTHA), that allows the identification of proteins required for modulating the physical interaction between two given proteins. Our assay starts with a yeast strain in which the physical interaction of interest can be detected by growth on media lacking histidine, in the context of the Y2H methodology. By combining the synthetic genetic array technology, we can systematically screen mutant libraries of the yeast Saccharomyces cerevisiae to identify trans -acting mutations that disrupt the physical interaction of interest. We apply this novel method in a screen for mutants that disrupt the interaction between the N-terminus of Elg1 and the Slx5 protein. Elg1 is part of an alternative replication factor C-like complex that unloads PCNA during DNA replication and repair. Slx5 forms, together with Slx8, a SUMO-targeted ubiquitin ligase (STUbL) believed to send proteins to degradation. Our results show that the interaction requires both the STUbL activity and the PCNA unloading by Elg1, and identify topoisomerase I DNA-protein cross-links as a major factor in separating the two activities. Thus, we demonstrate that RYTHA can be applied to gain insights about particular pathways in yeast, by uncovering the connection between the proteasomal ubiquitin-dependent degradation pathway, DNA replication, and repair machinery, which can be separated by the topoisomerase-mediated cross-links to DNA. Copyright © 2017 by the Genetics Society of America.

A label-free fluorescent biosensor for the detection of protein kinase activity based on gold nanoclusters/graphene oxide hybrid materials.

PubMed

Liu, Qing; Li, Ning; Wang, Mengke; Wang, Lei; Su, Xingguang

2018-07-12

Protein kinase (PKA) can regulate many cellular biological processes by phosphorylation substrate peptide or protein. A new fluorescent biosensing method for the detection of PKA activity was developed by using 11-mercaptoundecanoic acid-capped gold nanoclusters (MUA-Au NCs) and graphene oxide (GO) with low background noise. In this strategy, the special designed peptide could be anchored on the surface of MUA-Au NCs by the Au-S bond and also adsorbed on the surface of GO owing to the electrostatic interaction. As a result, the fluorescence of MUA-Au NCs was quenched leading to low background fluorescence due to the forster resonance energy transfer (FRET) between MUA-Au NCs and GO via peptide as a bridge. However, when the substrate peptide was phosphorylated by PKA, the FRET between GO and MUA-Au NCs was disrupted because of the weakened interaction between the phosphorylated peptide and the GO, resulting in recovery of the fluorescence intensity. The developed label-free fluorescence "turn-off-on" method can detect protein kinase activity in the range of 0.6-2.0 U mL -1 with a detection limit of 0.17 U mL -1 (3σ). The feasibility of this present method for kinase inhibitor screening was also studied by assessment of H-89 kinase inhibition with an IC 50 value of 0.049 μmol L -1 . Copyright © 2018. Published by Elsevier B.V.

Quantitative determination of trigonelline in mouse serum by means of hydrophilic interaction liquid chromatography-MS/MS analysis: Application to a pharmacokinetic study.

PubMed

Szczesny, Damian; Bartosińska, Ewa; Jacyna, Julia; Patejko, Małgorzata; Siluk, Danuta; Kaliszan, Roman

2018-02-01

Trigonelline is a pyridine alkaloid found in fenugreek seeds and coffee beans. Most of the previous studies are concerned with the quantification of trigonelline along with other constituents in coffee herbs or beverages. Only a few have focused on its determination in animal or human tissues by applying different modes of HPLC with UV or MS detection. The aim of the study was to develop and validate a fast and simple method for trigonelline determination in serum by the use of hydrophilic interaction liquid chromatography (HILIC) with ESI-MS/MS detection. Separation of trigonelline was achieved on a Kinetex HILIC column operated at 35°C with acetonitrile-ammonium formate (10 mm, pH = 3) buffer mixture (55:45, v/v) as the mobile phase. The developed method was successfully applied to determine trigonelline concentration in mouse serum after intravenous administration of 10 mg/kg. The developed assay is sensitive (limit of detection = 1.5 ng/mL, limit of quantification = 5.0 ng/mL) and linear in a concentration range from 5.0 to 250.0 ng/mL. Sample preparation is limited to deproteinization, centrifugation and filtration. The application of the HILIC mode of chromatography with MS detection and selection of deuterated trigonelline as internal standard allowed a rapid and precise method of trigonelline quantification to be to developed. Copyright © 2017 John Wiley & Sons, Ltd.

Improving strategies to assess competitive effects of barred owls on northern spotted owls in the Pacific Northwest

USGS Publications Warehouse

Wiens, J. David; Weekes, Anne

2011-01-01

A scientific study has determined that survey methods designed for spotted owls do not always detect barred owls that are actually present in spotted owl habitat. The researchers suggest that strategies to address potential interactions between spotted owls and barred owls will require carefully designed surveys that account for response behaviors and imperfect detection of both species. Species-specific sampling methods, which are proposed, can be used by forest managers to determine the occurrence and distribution of barred owls with high confidence. This fact sheet provides highlights of the research (Wiens and others, 2011).

Directional Sensitivity in Light-Mass Dark Matter Searches with Single-Electron-Resolution Ionization Detectors

NASA Astrophysics Data System (ADS)

Kadribasic, Fedja; Mirabolfathi, Nader; Nordlund, Kai; Sand, Andrea E.; Holmström, Eero; Djurabekova, Flyura

2018-03-01

We propose a method using solid state detectors with directional sensitivity to dark matter interactions to detect low-mass weakly interacting massive particles (WIMPs) originating from galactic sources. In spite of a large body of literature for high-mass WIMP detectors with directional sensitivity, no available technique exists to cover WIMPs in the mass range <1 GeV /c2 . We argue that single-electron-resolution semiconductor detectors allow for directional sensitivity once properly calibrated. We examine the commonly used semiconductor material response to these low-mass WIMP interactions.

Monitoring microbial metabolites using an inductively coupled resonance circuit

NASA Astrophysics Data System (ADS)

Karnaushenko, Daniil; Baraban, Larysa; Ye, Dan; Uguz, Ilke; Mendes, Rafael G.; Rümmeli, Mark H.; de Visser, J. Arjan G. M.; Schmidt, Oliver G.; Cuniberti, Gianaurelio; Makarov, Denys

2015-08-01

We present a new approach to monitor microbial population dynamics in emulsion droplets via changes in metabolite composition, using an inductively coupled LC resonance circuit. The signal measured by such resonance detector provides information on the magnetic field interaction with the bacterial culture, which is complementary to the information accessible by other detection means, based on electric field interaction, i.e. capacitive or resistive, as well as optical techniques. Several charge-related factors, including pH and ammonia concentrations, were identified as possible contributors to the characteristic of resonance detector profile. The setup enables probing the ionic byproducts of microbial metabolic activity at later stages of cell growth, where conventional optical detection methods have no discriminating power.

Post-capillary reaction detection in capillary electrophoresis based on the streptavidin-biotin interaction. Optimization and application to single cell analysis.

PubMed

Feltus, A; Hentz, N G; Daunert, S

2001-05-25

A class-selective post-capillary reaction detection method for capillary electrophoresis is described in which a streptavidin-fluorescein isothiocyanate (streptavidin-FITC) conjugate is used to detect biotin moieties. The selective binding of biotin moieties to the streptavidin-FITC conjugate causes an enhancement of fluorescence proportional to the concentration of biotin present. After capillary electrophoresis the separated analytes react with streptavidin-FITC in a coaxial reactor and are then detected either by a benchtop spectrofluorometer (2.5 microM detection limit) or by an epi-fluorescence microscope (1 x 10(-7) M detection limit). The method is used to examine biotinylated species in a crude mammalian cell lysate which was found to contain 83+/-3 fmol in 3600 cell volumes. In addition, it is used to examine the uptake of biotin by individual sea urchin oocytes. The results indicate that, in the oocytes, biocytin is the prevalent form of biotin and its concentration varies widely between cells (mean=2+/-2 microM).

Dual-Mode Electro-Optical Techniques for Biosensing Applications: A Review

PubMed Central

Johnson, Steven

2017-01-01

The monitoring of biomolecular interactions is a key requirement for the study of complex biological processes and the diagnosis of disease. Technologies that are capable of providing label-free, real-time insight into these interactions are of great value for the scientific and clinical communities. Greater understanding of biomolecular interactions alongside increased detection accuracy can be achieved using technology that can provide parallel information about multiple parameters of a single biomolecular process. For example, electro-optical techniques combine optical and electrochemical information to provide more accurate and detailed measurements that provide unique insights into molecular structure and function. Here, we present a comparison of the main methods for electro-optical biosensing, namely, electrochemical surface plasmon resonance (EC-SPR), electrochemical optical waveguide lightmode spectroscopy (EC-OWLS), and the recently reported silicon-based electrophotonic approach. The comparison considers different application spaces, such as the detection of low concentrations of biomolecules, integration, the tailoring of light-matter interaction for the understanding of biomolecular processes, and 2D imaging of biointeractions on a surface. PMID:28880211

Dual-Mode Electro-Optical Techniques for Biosensing Applications: A Review.

PubMed

Juan-Colás, José; Johnson, Steven; Krauss, Thomas F

2017-09-07

The monitoring of biomolecular interactions is a key requirement for the study of complex biological processes and the diagnosis of disease. Technologies that are capable of providing label-free, real-time insight into these interactions are of great value for the scientific and clinical communities. Greater understanding of biomolecular interactions alongside increased detection accuracy can be achieved using technology that can provide parallel information about multiple parameters of a single biomolecular process. For example, electro-optical techniques combine optical and electrochemical information to provide more accurate and detailed measurements that provide unique insights into molecular structure and function. Here, we present a comparison of the main methods for electro-optical biosensing, namely, electrochemical surface plasmon resonance (EC-SPR), electrochemical optical waveguide lightmode spectroscopy (EC-OWLS), and the recently reported silicon-based electrophotonic approach. The comparison considers different application spaces, such as the detection of low concentrations of biomolecules, integration, the tailoring of light-matter interaction for the understanding of biomolecular processes, and 2D imaging of biointeractions on a surface.

Hydrogen bonding recognition and colorimetric detection of isoprenaline using 2-amino-5-mercapto-1,3,4-thiadiazol functionalized gold nanoparticles

NASA Astrophysics Data System (ADS)

Khezri, Somayeh; Bahram, Morteza; Samadi, Naser

2018-01-01

In this paper, we describe a rapid, low-cost and highly sensitive colorimetric method for the detection of isoprenaline, based on 2-amino-5-mercapto-1,3,4-thiadiazol (AMTD) functionalized gold nanoparticles (AMTD-AuNPs) as a sensing element. Hydrogen bonding interaction between isoprenaline and AMTD resulted in the aggregation of AuNPs and a consequent color change of AuNPs from red to blue. The concentration of isoprenaline could be detected with the naked eye or a UV-visible spectrometer. Results showed that the absorbance ratio (A650/A524) was linear with isoprenaline concentrations in the range of 0.2 to 2.6 μM (R = 0.997). The detection limit of this method was 0.08 μM. The proposed method is simple, without using complicated instruments and adding salts for enhancing sensitivity. This probe could be successfully applied to the determination of isoprenaline in human serum samples and urine samples after deproteinization.

Micro-Machined Thin Film Sensor Arrays For The Detection Of H2, Containing Gases, And Method Of Making And Using The Same.

DOEpatents

DiMeo, Jr., Frank; Baum, Thomas H.

2003-07-22

The present invention provides a hydrogen sensor including a thin film sensor element formed by metal organic chemical vapor deposition (MOCVD) or physical vapor deposition (PVD), on a micro-hotplate structure. The thin film sensor element includes a film of a hydrogen-interactive metal film that reversibly interacts with hydrogen to provide a correspondingly altered response characteristic, such as optical transmissivity, electrical conductance, electrical resistance, electrical capacitance, magneto resistance, photoconductivity, etc., relative to the response characteristic of the film in the absence of hydrogen. The hydrogen-interactive metal film may be overcoated with a thin film hydrogen-permeable barrier layer to protect the hydrogen-interactive film from deleterious interaction with non-hydrogen species. The hydrogen permeable barrier may comprise species to scavenge oxygen and other like species. The hydrogen sensor of the invention may be usefully employed for the detection of hydrogen in an environment susceptible to the incursion or generation of hydrogen and may be conveniently configured as a hand-held apparatus.

Data-driven approach of CUSUM algorithm in temporal aberrant event detection using interactive web applications.

PubMed

Li, Ye; Whelan, Michael; Hobbs, Leigh; Fan, Wen Qi; Fung, Cecilia; Wong, Kenny; Marchand-Austin, Alex; Badiani, Tina; Johnson, Ian

2016-06-27

In 2014/2015, Public Health Ontario developed disease-specific, cumulative sum (CUSUM)-based statistical algorithms for detecting aberrant increases in reportable infectious disease incidence in Ontario. The objective of this study was to determine whether the prospective application of these CUSUM algorithms, based on historical patterns, have improved specificity and sensitivity compared to the currently used Early Aberration Reporting System (EARS) algorithm, developed by the US Centers for Disease Control and Prevention. A total of seven algorithms were developed for the following diseases: cyclosporiasis, giardiasis, influenza (one each for type A and type B), mumps, pertussis, invasive pneumococcal disease. Historical data were used as baseline to assess known outbreaks. Regression models were used to model seasonality and CUSUM was applied to the difference between observed and expected counts. An interactive web application was developed allowing program staff to directly interact with data and tune the parameters of CUSUM algorithms using their expertise on the epidemiology of each disease. Using these parameters, a CUSUM detection system was applied prospectively and the results were compared to the outputs generated by EARS. The outcome was the detection of outbreaks, or the start of a known seasonal increase and predicting the peak in activity. The CUSUM algorithms detected provincial outbreaks earlier than the EARS algorithm, identified the start of the influenza season in advance of traditional methods, and had fewer false positive alerts. Additionally, having staff involved in the creation of the algorithms improved their understanding of the algorithms and improved use in practice. Using interactive web-based technology to tune CUSUM improved the sensitivity and specificity of detection algorithms.

People Detection by a Mobile Robot Using Stereo Vision in Dynamic Indoor Environments

NASA Astrophysics Data System (ADS)

Méndez-Polanco, José Alberto; Muñoz-Meléndez, Angélica; Morales, Eduardo F.

People detection and tracking is a key issue for social robot design and effective human robot interaction. This paper addresses the problem of detecting people with a mobile robot using a stereo camera. People detection using mobile robots is a difficult task because in real world scenarios it is common to find: unpredictable motion of people, dynamic environments, and different degrees of human body occlusion. Additionally, we cannot expect people to cooperate with the robot to perform its task. In our people detection method, first, an object segmentation method that uses the distance information provided by a stereo camera is used to separate people from the background. The segmentation method proposed in this work takes into account human body proportions to segment people and provides a first estimation of people location. After segmentation, an adaptive contour people model based on people distance to the robot is used to calculate a probability of detecting people. Finally, people are detected merging the probabilities of the contour people model and by evaluating evidence over time by applying a Bayesian scheme. We present experiments on detection of standing and sitting people, as well as people in frontal and side view with a mobile robot in real world scenarios.

Reconsideration of the Detection and Fluorescence Mechanism of a Pyrene-Based Chemosensor for TNT.

PubMed

Lu, Meiheng; Zhou, Panwang; Ma, Yinhua; Tang, Zhe; Yang, Yanqiang; Han, Keli

2018-02-08

The rapid detection of chemical explosives is crucial for national security and public safety, and the investigation of sensing mechanisms is important for designing highly efficient chemosensors. This study theoretically investigates the detection and fluorescence mechanism of a newly synthesized pyrene-based chemosensor for the detection of trinitrotoluene (TNT) through density-functional-theory (DFT) and time-dependent density-functional-theory (TDDFT) methods and suggests a different interaction product of the probe and TNT from previously reported ones [ Mosca et al. J. Am. Chem. Soc. 2015 , 137 , 7967 ]. Instead of forming Meisenheimer complexes, the energies of which are beyond those of the reactants, a low-energy product generated by a π-π-stacking interaction is more rational and favorable. The fluorescence-quenching property further confirms that the π-π-stacking product is the predicted one rather than luminescent Meisenheimer complexes. Frontier-molecular-orbital (FMO)-analysis results show that photoinduced electron transfer (PET) is the mechanism underlying the luminescence quenching of the probe upon exposure to TNT.

An empirical comparison of several recent epistatic interaction detection methods.

PubMed

Wang, Yue; Liu, Guimei; Feng, Mengling; Wong, Limsoon

2011-11-01

Many new methods have recently been proposed for detecting epistatic interactions in GWAS data. There is, however, no in-depth independent comparison of these methods yet. Five recent methods-TEAM, BOOST, SNPHarvester, SNPRuler and Screen and Clean (SC)-are evaluated here in terms of power, type-1 error rate, scalability and completeness. In terms of power, TEAM performs best on data with main effect and BOOST performs best on data without main effect. In terms of type-1 error rate, TEAM and BOOST have higher type-1 error rates than SNPRuler and SNPHarvester. SC does not control type-1 error rate well. In terms of scalability, we tested the five methods using a dataset with 100 000 SNPs on a 64 bit Ubuntu system, with Intel (R) Xeon(R) CPU 2.66 GHz, 16 GB memory. TEAM takes ~36 days to finish and SNPRuler reports heap allocation problems. BOOST scales up to 100 000 SNPs and the cost is much lower than that of TEAM. SC and SNPHarvester are the most scalable. In terms of completeness, we study how frequently the pruning techniques employed by these methods incorrectly prune away the most significant epistatic interactions. We find that, on average, 20% of datasets without main effect and 60% of datasets with main effect are pruned incorrectly by BOOST, SNPRuler and SNPHarvester. The software for the five methods tested are available from the URLs below. TEAM: http://csbio.unc.edu/epistasis/download.php BOOST: http://ihome.ust.hk/~eeyang/papers.html. SNPHarvester: http://bioinformatics.ust.hk/SNPHarvester.html. SNPRuler: http://bioinformatics.ust.hk/SNPRuler.zip. Screen and Clean: http://wpicr.wpic.pitt.edu/WPICCompGen/. wangyue@nus.edu.sg.

Weld quality inspection using laser-EMAT ultrasonic system and C-scan method

NASA Astrophysics Data System (ADS)

Yang, Lei; Ume, I. Charles

2014-02-01

Laser/EMAT ultrasonic technique has attracted more and more interests in weld quality inspection because of its non-destructive and non-contact characteristics. When ultrasonic techniques are used to detect welds joining relative thin plates, the dominant ultrasonic waves present in the plates are Lamb waves, which propagate all through the thickness. Traditional Time of Flight(ToF) method loses its power. The broadband nature of laser excited ultrasound plus dispersive and multi-modal characteristic of Lamb waves make the EMAT acquired signals very complicated in this situation. Challenge rises in interpreting the received signals and establishing relationship between signal feature and weld quality. In this paper, the laser/EMAT ultrasonic technique was applied in a C-scan manner to record full wave propagation field over an area close to the weld. Then the effect of weld defect on the propagation field of Lamb waves was studied visually by watching an movie resulted from the recorded signals. This method was proved to be effective to detect the presence of hidden defect in the weld. Discrete wavelet transform(DWT) was applied to characterize the acquired ultrasonic signals and ideal band-pass filter was used to isolate wave components most sensitive to the weld defect. Different interactions with the weld defect were observed for different wave components. Thus this C-Scan method, combined with DWT and ideal band-pass filter, proved to be an effective methodology to experimentally study interactions of various laser excited Lamb Wave components with weld defect. In this work, the method was demonstrated by inspecting a hidden local incomplete penetration in weld. In fact, this method can be applied to study Lamb Wave interactions with any type of structural inconsistency. This work also proposed a ideal filtered based method to effectively reduce the total experimental time.

Utilizing Intrinsic Properties of Polyaniline to Detect Nucleic Acid Hybridization through UV-Enhanced Electrostatic Interaction.

PubMed

Sengupta, Partha Pratim; Gloria, Jared N; Amato, Dahlia N; Amato, Douglas V; Patton, Derek L; Murali, Beddhu; Flynt, Alex S

2015-10-12

Detection of specific RNA or DNA molecules by hybridization to "probe" nucleic acids via complementary base-pairing is a powerful method for analysis of biological systems. Here we describe a strategy for transducing hybridization events through modulating intrinsic properties of the electroconductive polymer polyaniline (PANI). When DNA-based probes electrostatically interact with PANI, its fluorescence properties are increased, a phenomenon that can be enhanced by UV irradiation. Hybridization of target nucleic acids results in dissociation of probes causing PANI fluorescence to return to basal levels. By monitoring restoration of base PANI fluorescence as little as 10(-11) M (10 pM) of target oligonucleotides could be detected within 15 min of hybridization. Detection of complementary oligos was specific, with introduction of a single mismatch failing to form a target-probe duplex that would dissociate from PANI. Furthermore, this approach is robust and is capable of detecting specific RNAs in extracts from animals. This sensor system improves on previously reported strategies by transducing highly specific probe dissociation events through intrinsic properties of a conducting polymer without the need for additional labels.

Optical sensor for fluoride determination in tea sample based on evanescent-wave interaction and fiber-optic integration.

PubMed

Xiong, Yan; Wu, Jiayi; Wang, Qing; Xu, Jing; Fang, Shenwen; Chen, Jie; Duan, Ming

2017-11-01

In this work, a miniaturized optical sensor was developed for fluoride determination in tea samples to evaluate their specific risks of fluorosis for public health based on evanescent-wave interaction. The sensor design was integrated on the optical fiber by utilizing the evanescent wave produced on the fiber surface to react with sensing reagents. According to the absorption change at 575nm, fluoride could be determined by colorimetric method and evaluated by Beer's law. With improved performances of small detection volume (1.2μL), fast analysis (0.41min), wide linear range (0.01-1.4mgL -1 ), low detection limit (3.5μgL -1 , 3σ) and excellent repeatability (2.34%), the sensor has been applied to fluoride determination in six different tea samples. Conventional spectrophotometry and ion chromatography were employed to validate the sensor's accuracy and potential application. Furthermore, this sensor fabrication provided a miniaturized colorimetric detection platform for other hazardous species monitoring based on evanescent wave interaction. Copyright © 2017 Elsevier B.V. All rights reserved.

An Educational MONTE CARLO Simulation/Animation Program for the Cosmic Rays Muons and a Prototype Computer-Driven Hardware Display.

ERIC Educational Resources Information Center

Kalkanis, G.; Sarris, M. M.

1999-01-01

Describes an educational software program for the study of and detection methods for the cosmic ray muons passing through several light transparent materials (i.e., water, air, etc.). Simulates muons and Cherenkov photons' paths and interactions and visualizes/animates them on the computer screen using Monte Carlo methods/techniques which employ…

An optical biosensor for detection of pathogen biomarkers from Shiga toxin-producing Escherichia coli in ground beef samples

NASA Astrophysics Data System (ADS)

Lamoureux, Loreen; Adams, Peter; Banisadr, Afsheen; Stromberg, Zachary; Graves, Steven; Montano, Gabriel; Moxley, Rodney; Mukundan, Harshini

2014-03-01

Shiga toxin-producing Escherichia coli (STEC) poses a serious threat to human health through the consumption of contaminated food products, particularly beef and produce. Early detection in the food chain, and discrimination from other non-pathogenic Escherichia coli (E. coli), is critical to preventing human outbreaks, and meeting current agricultural screening standards. These pathogens often present in low concentrations in contaminated samples, making discriminatory detection difficult without the use of costly, time-consuming methods (e.g. culture). Using multiple signal transduction schemes (including novel optical methods designed for amphiphiles), specific recognition antibodies, and a waveguide-based optical biosensor developed at Los Alamos National Laboratory, we have developed ultrasensitive detection methods for lipopolysaccharides (LPS), and protein biomarkers (Shiga toxin) of STEC in complex samples (e.g. beef lysates). Waveguides functionalized with phospholipid bilayers were used to pull down amphiphilic LPS, using methods (membrane insertion) developed by our team. The assay format exploits the amphiphilic biochemistry of lipoglycans, and allows for rapid, sensitive detection with a single fluorescent reporter. We have used a combination of biophysical methods (atomic force and fluorescence microscopy) to characterize the interaction of amphiphiles with lipid bilayers, to efficiently design these assays. Sandwich immunoassays were used for detection of protein toxins. Biomarkers were spiked into homogenated ground beef samples to determine performance and limit of detection. Future work will focus on the development of discriminatory antibodies for STEC serotypes, and using quantum dots as the fluorescence reporter to enable multiplex screening of biomarkers.

Quantum dots as optical labels for ultrasensitive detection of polyphenols.

PubMed

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

2014-07-15

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

PolyaPeak: Detecting Transcription Factor Binding Sites from ChIP-seq Using Peak Shape Information

PubMed Central

Wu, Hao; Ji, Hongkai

2014-01-01

ChIP-seq is a powerful technology for detecting genomic regions where a protein of interest interacts with DNA. ChIP-seq data for mapping transcription factor binding sites (TFBSs) have a characteristic pattern: around each binding site, sequence reads aligned to the forward and reverse strands of the reference genome form two separate peaks shifted away from each other, and the true binding site is located in between these two peaks. While it has been shown previously that the accuracy and resolution of binding site detection can be improved by modeling the pattern, efficient methods are unavailable to fully utilize that information in TFBS detection procedure. We present PolyaPeak, a new method to improve TFBS detection by incorporating the peak shape information. PolyaPeak describes peak shapes using a flexible Pólya model. The shapes are automatically learnt from the data using Minorization-Maximization (MM) algorithm, then integrated with the read count information via a hierarchical model to distinguish true binding sites from background noises. Extensive real data analyses show that PolyaPeak is capable of robustly improving TFBS detection compared with existing methods. An R package is freely available. PMID:24608116

Epiregulin (EREG) and human V-ATPase (TCIRG1): genetic variation, ethnicity and pulmonary tuberculosis susceptibility in Guinea-Bissau and The Gambia

PubMed Central

White, Marquitta J.; Tacconelli, Alessandra; Chen, Jane S.; Wejse, Christian; Hill, Philip C.; Gomez, Victor F; Velez-Edwards, Digna R.; Østergaard, Lars J.; Hu, Ting; Moore, Jason H.; Novelli, Giuseppe; Scott, William K.; Williams, Scott M.; Sirugo, Giorgio

2017-01-01

We analyzed two West African samples (Guinea-Bissau: n = 289 cases, 322 controls; The Gambia: n = 240 cases, 248 controls) to evaluate single nucleotide polymorphisms (SNPs) in Epiregulin (EREG) and V-ATPase (T cell immune regulator 1, TCIRG1) using single and multi-locus analyses to determine whether previously described associations with pulmonary tuberculosis (PTB) in Vietnamese and Italians would replicate in African populations. We did not detect any significant single locus or haplotype associations in either sample. We also performed exploratory pairwise interaction analyses using Visualization of Statistical Epistasis Networks (ViSEN), a novel method to detect only interactions among multiple variables, to elucidate possible interaction effects between SNPs and demographic factors. Although we found no strong evidence of marginal effects, there were several significant pairwise interactions that were identified in either the Guinea-Bissau or The Gambia samples, two of which replicated across populations. Our results indicate that the effects of EREG and TCIRG1 variants on PTB susceptibility, to the extent that they exist, are dependent on gene-gene interactions in West African populations as detected with ViSEN. In addition, epistatic effects are likely to be influenced by inter- and intra-population differences in genetic or environmental context and/or the mycobacterial lineages causing disease. PMID:24898387

A novel method for detection of apoptosis

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

Zagariya, Alexander M., E-mail: zagariya@uic.edu

2012-04-15

There are two different Angiotensin II (ANG II) peptides in nature: Human type (ANG II) and Bovine type (ANG II*). These eight amino acid peptides differ only at position 5 where Valine is replaced by Isoleucine in the Bovine type. They are present in all species studied so far. These amino acids are different by only one atom of carbon. This difference is so small, that it will allow any of ANG II, Bovine or Human antibodies to interact with all species and create a universal method for apoptosis detection. ANG II concentrations are found at substantially higher levels inmore » apoptotic, compared to non-apoptotic, tissues. ANG II accumulation can lead to DNA damage, mutations, carcinogenesis and cell death. We demonstrate that Bovine antiserum can be used for universal detection of apoptosis. In 2010, the worldwide market for apoptosis detection reached the $20 billion mark and significantly increases each year. Most commercially available methods are related to Annexin V and TUNNEL. Our new method based on ANG II is more widely known to physicians and scientists compared to previously used methods. Our approach offers a novel alternative for assessing apoptosis activity with enhanced sensitivity, at a lower cost and ease of use.« less

Evaluation of a surface plasmon resonance imaging-based multiplex O-antigen serogrouping for Escherichia coli using eleven major serotypes of Shiga -toxin-producing E. coli.

PubMed

Nakano, Satoshi; Nagao, Miki; Yamasaki, Tomomi; Morimura, Hiroyuki; Hama, Natsuki; Iijima, Yoshio; Shinomiya, Hiroto; Tanaka, Michio; Yamamoto, Masaki; Matsumura, Yasufumi; Miyake, Shiro; Ichiyama, Satoshi

2018-06-01

The early detection of Shiga toxin-producing Escherichia coli (STEC) is important for early diagnosis and preventing the spread of STEC. Although the confirmatory test for STEC should be based on the detection of Shiga toxin using molecular analysis, isolation permits additional characterization of STEC using a variety of methods, including O:H serotyping. The conventional slide agglutination O-antigen serogrouping used in many clinical laboratories is laborious and time-consuming. Surface plasmon resonance (SPR)-based immunosensors are commonly used to investigate a large variety of bio-interactions such as antibody/antigen, peptide/antibody, DNA/DNA, and antibody/bacteria interactions. SPR imaging (SPRi) is characterized by multiplexing capabilities for rapidly screening (approximately 100 to several hundred sensorgrams in parallel) molecules. SPRi-based O-antigen serogrouping method for STEC was recently developed by detecting the interactions between O-antigen-specific antibodies and bacterial cells themselves. The aim of this study was to evaluate its performance for E. coli serogrouping using clinical STEC isolates by comparing the results of slide agglutination tests. We tested a total of 188 isolates, including O26, O45, O91, O103, O111, O115, O121, O128, O145, O157, and O159. The overall sensitivity of SPRi-based O-antigen serogrouping was 98.9%. Only two O157 isolates were misidentified as nontypeable and O121. The detection limits of all serotypes were distributed between 1.1 × 10 6 and 17.6 × 10 6  CFU/ml. Pulsed-field gel electrophoresis (PFGE) revealed the heterogeneity of the examined isolates. In conclusion, SPRi is a useful method for the O-antigen serogrouping of STEC isolates, but the further evaluation of non-O157 minor serogroups is needed. Copyright © 2018 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Selective collection and detection of MCF-7 breast cancer cells using aptamer-functionalized magnetic beads and quantum dots based nano-bio-probes.

PubMed

Hua, Xin; Zhou, Zhenxian; Yuan, Liang; Liu, Songqin

2013-07-25

A novel strategy for selective collection and detection of breast cancer cells (MCF-7) based on aptamer-cell interaction was developed. Mucin 1 protein (MUC1) aptamer (Apt1) was covalently conjugated to magnetic beads to capture MCF-7 cell through affinity interaction between Apt1 and MUC1 protein that overexpressed on the surface of MCF-7 cells. Meanwhile, a nano-bio-probe was constructed by coupling of nucleolin aptamer AS1411 (Apt2) to CdTe quantum dots (QDs) which were homogeneously coated on the surfaces of monodispersed silica nanoparticles (SiO2 NPs). The nano-bio-probe displayed similar optical and electrochemical performances to free CdTe QDs, and remained high affinity to nucleolin overexpressed cells through the interaction between AS1411 and nucleolin protein. Photoluminescence (PL) and square-wave voltammetric (SWV) assays were used to quantitatively detect MCF-7 cells. Improved selectivity was obtained by using these two aptamers together as recognition elements simultaneously, compared to using any single aptamer. Based on the signal amplification of QDs coated silica nanoparticles (QDs/SiO2), the detection sensitivity was enhanced and a detection limit of 201 and 85 cells mL(-1) by PL and SWV method were achieved, respectively. The proposed strategy could be extended to detect other cells, and showed potential applications in cell imaging and drug delivery. Copyright © 2013 Elsevier B.V. All rights reserved.

Interactive surface correction for 3D shape based segmentation

NASA Astrophysics Data System (ADS)

Schwarz, Tobias; Heimann, Tobias; Tetzlaff, Ralf; Rau, Anne-Mareike; Wolf, Ivo; Meinzer, Hans-Peter

2008-03-01

Statistical shape models have become a fast and robust method for segmentation of anatomical structures in medical image volumes. In clinical practice, however, pathological cases and image artifacts can lead to local deviations of the detected contour from the true object boundary. These deviations have to be corrected manually. We present an intuitively applicable solution for surface interaction based on Gaussian deformation kernels. The method is evaluated by two radiological experts on segmentations of the liver in contrast-enhanced CT images and of the left heart ventricle (LV) in MRI data. For both applications, five datasets are segmented automatically using deformable shape models, and the resulting surfaces are corrected manually. The interactive correction step improves the average surface distance against ground truth from 2.43mm to 2.17mm for the liver, and from 2.71mm to 1.34mm for the LV. We expect this method to raise the acceptance of automatic segmentation methods in clinical application.

A genome-wide 3C-method for characterizing the three-dimensional architectures of genomes.

PubMed

Duan, Zhijun; Andronescu, Mirela; Schutz, Kevin; Lee, Choli; Shendure, Jay; Fields, Stanley; Noble, William S; Anthony Blau, C

2012-11-01

Accumulating evidence demonstrates that the three-dimensional (3D) organization of chromosomes within the eukaryotic nucleus reflects and influences genomic activities, including transcription, DNA replication, recombination and DNA repair. In order to uncover structure-function relationships, it is necessary first to understand the principles underlying the folding and the 3D arrangement of chromosomes. Chromosome conformation capture (3C) provides a powerful tool for detecting interactions within and between chromosomes. A high throughput derivative of 3C, chromosome conformation capture on chip (4C), executes a genome-wide interrogation of interaction partners for a given locus. We recently developed a new method, a derivative of 3C and 4C, which, similar to Hi-C, is capable of comprehensively identifying long-range chromosome interactions throughout a genome in an unbiased fashion. Hence, our method can be applied to decipher the 3D architectures of genomes. Here, we provide a detailed protocol for this method. Published by Elsevier Inc.

Dynamic Bayesian network modeling for longitudinal brain morphometry

PubMed Central

Chen, Rong; Resnick, Susan M; Davatzikos, Christos; Herskovits, Edward H

2011-01-01

Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment — the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group. PMID:21963916

Manual-slide-engaged paper chip for parallel SERS-immunoassay measurement of clenbuterol from swine hair.

PubMed

Zheng, Tingting; Gao, Zhigang; Luo, Yong; Liu, Xianming; Zhao, Weijie; Lin, Bingcheng

2016-02-01

Clenbuterol (CL), as a feed additive, has been banned in many countries due to its potential threat to human health. In detection of CL, a fast, low-cost technique with high accuracy and specificity would be ideal for its administrative on-field inspections. Among the attempts to pursue a reliable detection tool of CL, a technique that combines surface enhanced Raman spectroscopy (SERS) and immunoassay, is close to meet the requirements as above. However, multiple steps of interactions between CL analyte, antibody, and antigen are involved in this method, and under conventional setup, the operation of SERS/immunoassay were unwieldy. In this paper, to facilitate a more manageable sample manipulation for SERS-immunoassay measurement, a 3D paper chip was suggested. A switch-on-chip multilayered (abbreviated as SoCM-) microfluidic paper-based analysis device (μPad) was fabricated to provide operators with manual switches on the interactions between different microfluids. Besides, on a detection slip we made on the main body of our SoCM-μPad, antigen was anchored in pattern. With this architecture, multistep interactions between the CL analyte in swine hair extract and the SERS probe-modified antibody and antigen, were managed for on-chip SERS-immunoassay detection. This would be very attractive for fast, cheap, accurate, and on-site specific detection of CL from real samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detecting Protein-Glycolipid Interactions Using Glycomicelles and CaR-ESI-MS

NASA Astrophysics Data System (ADS)

Han, Ling; Kitova, Elena N.; Klassen, John S.

2016-11-01

This study reports on the use of the catch-and-release electrospray ionization mass spectrometry (CaR-ESI-MS) assay, combined with glycomicelles, as a method for detecting specific interactions between water-soluble proteins and glycolipids (GLs) in aqueous solution. The B subunit homopentamers of cholera toxin (CTB5) and Shiga toxin type 1 B (Stx1B5) and the gangliosides GM1, GM2, GM3, GD1a, GD1b, GT1b, and GD2 served as model systems for this study. The CTB5 exhibits broad specificity for gangliosides and binds to GM1, GM2, GM3, GD1a, GD1b, and GT1b; Stx1B5 does not recognize gangliosides. The CaR-ESI-MS assay was used to analyze solutions of CTB5 or Stx1B5 and individual gangliosides (GM1, GM2, GM3, GD1a, GD1b, GT1b, and GD2) or mixtures thereof. The high affinity interaction of CTB5 with GM1 was successfully detected. However, the apparent affinity, as determined from the mass spectra, is significantly lower than that of the corresponding pentasaccharide or when GM1 is presented in model membranes such as nanodiscs. Interactions between CTB5 and the low affinity gangliosides GD1a, GD1b, and GT1b, as well as GD2, which served as a negative control, were detected; no binding of CTB5 to GM2 or GM3 was observed. The CaR-ESI-MS results obtained for Stx1B5 reveal that nonspecific protein-ganglioside binding can occur during the ESI process, although the extent of binding varies between gangliosides. Consequently, interactions detected for CTB5 with GD1a, GD1b, and GT1b are likely nonspecific in origin. Taken together, these results reveal that the CaR-ESI-MS/glycomicelle approach for detecting protein-GL interactions is prone to false positives and false negatives and must be used with caution.

Detecting Protein-Glycolipid Interactions Using Glycomicelles and CaR-ESI-MS.

PubMed

Han, Ling; Kitova, Elena N; Klassen, John S

2016-11-01

This study reports on the use of the catch-and-release electrospray ionization mass spectrometry (CaR-ESI-MS) assay, combined with glycomicelles, as a method for detecting specific interactions between water-soluble proteins and glycolipids (GLs) in aqueous solution. The B subunit homopentamers of cholera toxin (CTB 5 ) and Shiga toxin type 1 B (Stx1B 5 ) and the gangliosides GM1, GM2, GM3, GD1a, GD1b, GT1b, and GD2 served as model systems for this study. The CTB 5 exhibits broad specificity for gangliosides and binds to GM1, GM2, GM3, GD1a, GD1b, and GT1b; Stx1B 5 does not recognize gangliosides. The CaR-ESI-MS assay was used to analyze solutions of CTB 5 or Stx1B 5 and individual gangliosides (GM1, GM2, GM3, GD1a, GD1b, GT1b, and GD2) or mixtures thereof. The high affinity interaction of CTB 5 with GM1 was successfully detected. However, the apparent affinity, as determined from the mass spectra, is significantly lower than that of the corresponding pentasaccharide or when GM1 is presented in model membranes such as nanodiscs. Interactions between CTB 5 and the low affinity gangliosides GD1a, GD1b, and GT1b, as well as GD2, which served as a negative control, were detected; no binding of CTB 5 to GM2 or GM3 was observed. The CaR-ESI-MS results obtained for Stx1B 5 reveal that nonspecific protein-ganglioside binding can occur during the ESI process, although the extent of binding varies between gangliosides. Consequently, interactions detected for CTB 5 with GD1a, GD1b, and GT1b are likely nonspecific in origin. Taken together, these results reveal that the CaR-ESI-MS/glycomicelle approach for detecting protein-GL interactions is prone to false positives and false negatives and must be used with caution. Graphical Abstract .

VARIABLE SELECTION FOR QUALITATIVE INTERACTIONS IN PERSONALIZED MEDICINE WHILE CONTROLLING THE FAMILY-WISE ERROR RATE

PubMed Central

Gunter, Lacey; Zhu, Ji; Murphy, Susan

2012-01-01

For many years, subset analysis has been a popular topic for the biostatistics and clinical trials literature. In more recent years, the discussion has focused on finding subsets of genomes which play a role in the effect of treatment, often referred to as stratified or personalized medicine. Though highly sought after, methods for detecting subsets with altering treatment effects are limited and lacking in power. In this article we discuss variable selection for qualitative interactions with the aim to discover these critical patient subsets. We propose a new technique designed specifically to find these interaction variables among a large set of variables while still controlling for the number of false discoveries. We compare this new method against standard qualitative interaction tests using simulations and give an example of its use on data from a randomized controlled trial for the treatment of depression. PMID:22023676

The Use of Two-Photon FRET-FLIM to Study Protein Interactions During Nuclear Envelope Fusion In Vivo and In Vitro.

PubMed

Byrne, Richard D; Larijani, Banafshé; Poccia, Dominic L

2016-01-01

FRET-FLIM techniques have wide application in the study of protein and protein-lipid interactions in cells. We have pioneered an imaging platform for accurate detection of functional states of proteins and their interactions in fixed cells. This platform, two-site-amplified Förster resonance energy transfer (a-FRET), allows greater signal generation while retaining minimal noise thus enabling application of fluorescence lifetime imaging microscopy (FLIM) to be routinely deployed in different types of cells and tissue. We have used the method described here, time-resolved FRET monitored by two-photon FLIM, to demonstrate the direct interaction of Phospholipase Cγ (PLCγ) by Src Family Kinase 1 (SFK1) during nuclear envelope formation and during male and female pronuclear membrane fusion in fertilized sea urchin eggs. We describe here a generic method that can be applied to monitor any proteins of interest.

Automatically generated acceptance test: A software reliability experiment

NASA Technical Reports Server (NTRS)

Protzel, Peter W.

1988-01-01

This study presents results of a software reliability experiment investigating the feasibility of a new error detection method. The method can be used as an acceptance test and is solely based on empirical data about the behavior of internal states of a program. The experimental design uses the existing environment of a multi-version experiment previously conducted at the NASA Langley Research Center, in which the launch interceptor problem is used as a model. This allows the controlled experimental investigation of versions with well-known single and multiple faults, and the availability of an oracle permits the determination of the error detection performance of the test. Fault interaction phenomena are observed that have an amplifying effect on the number of error occurrences. Preliminary results indicate that all faults examined so far are detected by the acceptance test. This shows promise for further investigations, and for the employment of this test method on other applications.

A hybrid network-based method for the detection of disease-related genes

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

Simultaneous segmentation of the bone and cartilage surfaces of a knee joint in 3D

NASA Astrophysics Data System (ADS)

Yin, Y.; Zhang, X.; Anderson, D. D.; Brown, T. D.; Hofwegen, C. Van; Sonka, M.

2009-02-01

We present a novel framework for the simultaneous segmentation of multiple interacting surfaces belonging to multiple mutually interacting objects. The method is a non-trivial extension of our previously reported optimal multi-surface segmentation. Considering an example application of knee-cartilage segmentation, the framework consists of the following main steps: 1) Shape model construction: Building a mean shape for each bone of the joint (femur, tibia, patella) from interactively segmented volumetric datasets. Using the resulting mean-shape model - identification of cartilage, non-cartilage, and transition areas on the mean-shape bone model surfaces. 2) Presegmentation: Employment of iterative optimal surface detection method to achieve approximate segmentation of individual bone surfaces. 3) Cross-object surface mapping: Detection of inter-bone equidistant separating sheets to help identify corresponding vertex pairs for all interacting surfaces. 4) Multi-object, multi-surface graph construction and final segmentation: Construction of a single multi-bone, multi-surface graph so that two surfaces (bone and cartilage) with zero and non-zero intervening distances can be detected for each bone of the joint, according to whether or not cartilage can be locally absent or present on the bone. To define inter-object relationships, corresponding vertex pairs identified using the separating sheets were interlinked in the graph. The graph optimization algorithm acted on the entire multiobject, multi-surface graph to yield a globally optimal solution. The segmentation framework was tested on 16 MR-DESS knee-joint datasets from the Osteoarthritis Initiative database. The average signed surface positioning error for the 6 detected surfaces ranged from 0.00 to 0.12 mm. When independently initialized, the signed reproducibility error of bone and cartilage segmentation ranged from 0.00 to 0.26 mm. The results showed that this framework provides robust, accurate, and reproducible segmentation of the knee joint bone and cartilage surfaces of the femur, tibia, and patella. As a general segmentation tool, the developed framework can be applied to a broad range of multi-object segmentation problems.

Cryo-balloon catheter localization in fluoroscopic images

NASA Astrophysics Data System (ADS)

Kurzendorfer, Tanja; Brost, Alexander; Jakob, Carolin; Mewes, Philip W.; Bourier, Felix; Koch, Martin; Kurzidim, Klaus; Hornegger, Joachim; Strobel, Norbert

2013-03-01

Minimally invasive catheter ablation has become the preferred treatment option for atrial fibrillation. Although the standard ablation procedure involves ablation points set by radio-frequency catheters, cryo-balloon catheters have even been reported to be more advantageous in certain cases. As electro-anatomical mapping systems do not support cryo-balloon ablation procedures, X-ray guidance is needed. However, current methods to provide support for cryo-balloon catheters in fluoroscopically guided ablation procedures rely heavily on manual user interaction. To improve this, we propose a first method for automatic cryo-balloon catheter localization in fluoroscopic images based on a blob detection algorithm. Our method is evaluated on 24 clinical images from 17 patients. The method successfully detected the cryoballoon in 22 out of 24 images, yielding a success rate of 91.6 %. The successful localization achieved an accuracy of 1.00 mm +/- 0.44 mm. Even though our methods currently fails in 8.4 % of the images available, it still offers a significant improvement over manual methods. Furthermore, detecting a landmark point along the cryo-balloon catheter can be a very important step for additional post-processing operations.

Ultrasensitive colorimetric detection of heparin based on self-assembly of gold nanoparticles on graphene oxide.

PubMed

Fu, Xiuli; Chen, Lingxin; Li, Jinhua

2012-08-21

A novel colorimetric method was developed for ultrasensitive detection of heparin based on self-assembly of gold nanoparticles (AuNPs) onto the surface of graphene oxide (GO). Polycationic protamine was used as a medium for inducing the self-assembly of citrate-capped AuNPs on GO through electrostatic interaction, resulting in a shift in the surface plasmon resonance (SPR) absorption of AuNPs and exhibiting a blue color. Addition of polyanionic heparin disturbed the self-assemble of AuNPs due to its strong affinity to protamine. With the increase of heparin concentration, the amounts of self-assembly AuNPs decreased and the color changed from blue to red in solution. Therefore, a "blue-to-red" colorimetric sensing strategy based on self-assembly of AuNPs could be established for heparin detection. Compared with the commonly reported aggregation-based methods ("red-to-blue"), the color change from blue to red was more eye-sensitive, especially in low concentration of target. Moreover, stronger interaction between protamine and heparin led to distinguish heparin from its analogues as well as various potentially coexistent physiological species. The strategy was simply achieved by the self-assembly nature of AuNPs and the application of two types of polyionic media, showing it to be label-free, simple, rapid and visual. This method could selectively detect heparin with a detection limit of 3.0 ng mL(-1) in standard aqueous solution and good linearity was obtained over the range 0.06-0.36 μg mL(-1) (R = 0.9936). It was successfully applied to determination of heparin in fetal bovine serum samples as low as 1.7 ng mL(-1) with a linear range of 0-0.8 μg mL(-1).

Detecting event-related changes in organizational networks using optimized neural network models.

PubMed

Li, Ze; Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques.

Detecting event-related changes in organizational networks using optimized neural network models

PubMed Central

Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques. PMID:29190799

Humic substances interfere with detection of pathogenic prion protein

USGS Publications Warehouse

Smith, Christen B.; Booth, Clarissa J.; Wadzinski, Tyler J.; Legname, Giuseppe; Chappell, Rick; Johnson, Christopher J.; Pedersen, Joel A.

2014-01-01

Studies examining the persistence of prions (the etiological agent of transmissible spongiform encephalopathies) in soil require accurate quantification of pathogenic prion protein (PrPTSE) extracted from or in the presence of soil particles. Here, we demonstrate that natural organic matter (NOM) in soil impacts PrPTSE detection by immunoblotting. Methods commonly used to extract PrPTSE from soils release substantial amounts of NOM, and NOM inhibited PrPTSE immunoblot signal. The degree of immunoblot interference increased with increasing NOM concentration and decreasing NOM polarity. Humic substances affected immunoblot detection of prion protein from both deer and hamsters. We also establish that after interaction with humic acid, PrPTSE remains infectious to hamsters inoculated intracerebrally, and humic acid appeared to slow disease progression. These results provide evidence for interactions between PrPTSE and humic substances that influence both accurate measurement of PrPTSE in soil and disease transmission.

Organic light emitting board for dynamic interactive display

PubMed Central

Kim, Eui Hyuk; Cho, Sung Hwan; Lee, Ju Han; Jeong, Beomjin; Kim, Richard Hahnkee; Yu, Seunggun; Lee, Tae-Woo; Shim, Wooyoung; Park, Cheolmin

2017-01-01

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications. PMID:28406151

Organic light emitting board for dynamic interactive display

NASA Astrophysics Data System (ADS)

Kim, Eui Hyuk; Cho, Sung Hwan; Lee, Ju Han; Jeong, Beomjin; Kim, Richard Hahnkee; Yu, Seunggun; Lee, Tae-Woo; Shim, Wooyoung; Park, Cheolmin

2017-04-01

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications.

Spectral Induced Polarization Signatures of Ethanol in Sand-Clay Medium

EPA Science Inventory

The spectral Induced Polarization (SIP) method has previously been investigated as a tool for detecting physicochemical changes occurring as result of clay-organic interactions in porous media. We performed SIP measurements with a dynamic signal analyzer (NI-4551) on laboratory ...

An information-gain approach to detecting three-way epistatic interactions in genetic association studies

PubMed Central

Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W; Collins, Ryan L; Wejse, Christian; Sirugo, Giorgio; Williams, Scott M; Moore, Jason H

2013-01-01

Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies. Objectives In this study, we propose a fast, non-parametric, and model-free measure for three-way epistasis. Methods Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way epistasis. Results Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies. PMID:23396514

Detection and characterization of protein interactions in vivo by a simple live-cell imaging method.

PubMed

Gallego, Oriol; Specht, Tanja; Brach, Thorsten; Kumar, Arun; Gavin, Anne-Claude; Kaksonen, Marko

2013-01-01

Over the last decades there has been an explosion of new methodologies to study protein complexes. However, most of the approaches currently used are based on in vitro assays (e.g. nuclear magnetic resonance, X-ray, electron microscopy, isothermal titration calorimetry etc). The accurate measurement of parameters that define protein complexes in a physiological context has been largely limited due to technical constrains. Here, we present PICT (Protein interactions from Imaging of Complexes after Translocation), a new method that provides a simple fluorescence microscopy readout for the study of protein complexes in living cells. We take advantage of the inducible dimerization of FK506-binding protein (FKBP) and FKBP-rapamycin binding (FRB) domain to translocate protein assemblies to membrane associated anchoring platforms in yeast. In this assay, GFP-tagged prey proteins interacting with the FRB-tagged bait will co-translocate to the FKBP-tagged anchor sites upon addition of rapamycin. The interactions are thus encoded into localization changes and can be detected by fluorescence live-cell imaging under different physiological conditions or upon perturbations. PICT can be automated for high-throughput studies and can be used to quantify dissociation rates of protein complexes in vivo. In this work we have used PICT to analyze protein-protein interactions from three biological pathways in the yeast Saccharomyces cerevisiae: Mitogen-activated protein kinase cascade (Ste5-Ste11-Ste50), exocytosis (exocyst complex) and endocytosis (Ede1-Syp1).

Nonparametric evaluation of birth cohort trends in disease rates.

PubMed

Tarone, R E; Chu, K C

2000-01-01

Although interpretation of age-period-cohort analyses is complicated by the non-identifiability of maximum likelihood estimates, changes in the slope of the birth-cohort effect curve are identifiable and have potential aetiologic significance. A nonparametric test for a change in the slope of the birth-cohort trend has been developed. The test is a generalisation of the sign test and is based on permutational distributions. A method for identifying interactions between age and calendar-period effects is also presented. The nonparametric method is shown to be powerful in detecting changes in the slope of the birth-cohort trend, although its power can be reduced considerably by calendar-period patterns of risk. The method identifies a previously unidentified decrease in the birth-cohort risk of lung-cancer mortality from 1912 to 1919, which appears to reflect a reduction in the initiation of smoking by young men at the beginning of the Great Depression (1930s). The method also detects an interaction between age and calendar period in leukemia mortality rates, reflecting the better response of children to chemotherapy. The proposed nonparametric method provides a data analytic approach, which is a useful adjunct to log-linear Poisson analysis of age-period-cohort models, either in the initial model building stage, or in the final interpretation stage.

Visualizing Active Enzyme Complexes Using a Photoreactive Inhibitor for Proximity Ligation – Application on γ-Secretase

PubMed Central

Schedin-Weiss, Sophia; Inoue, Mitsuhiro; Teranishi, Yasuhiro; Yamamoto, Natsuko Goto; Karlström, Helena; Winblad, Bengt; Tjernberg, Lars O.

2013-01-01

Here, we present a highly sensitive method to study protein-protein interactions and subcellular location selectively for active multicomponent enzymes. We apply the method on γ-secretase, the enzyme complex that catalyzes the cleavage of the amyloid precursor protein (APP) to generate amyloid β-peptide (Aβ), the major causative agent in Alzheimer disease (AD). The novel assay is based on proximity ligation, which can be used to study protein interactions in situ with very high sensitivity. In traditional proximity ligation assay (PLA), primary antibody recognition is typically accompanied by oligonucleotide-conjugated secondary antibodies as detection probes. Here, we first performed PLA experiments using antibodies against the γ-secretase components presenilin 1 (PS1), containing the catalytic site residues, and nicastrin, suggested to be involved in substrate recognition. To selectively study the interactions of active γ-secretase, we replaced one of the primary antibodies with a photoreactive γ-secretase inhibitor containing a PEG linker and a biotin group (GTB), and used oligonucleotide-conjugated streptavidin as a probe. Interestingly, significantly fewer interactions were detected with the latter, novel, assay, which is a reasonable finding considering that a substantial portion of PS1 is inactive. In addition, the PLA signals were located more peripherally when GTB was used instead of a PS1 antibody, suggesting that γ-secretase matures distal from the perinuclear ER region. This novel technique thus enables highly sensitive protein interaction studies, determines the subcellular location of the interactions, and differentiates between active and inactive γ-secretase in intact cells. We suggest that similar PLA assays using enzyme inhibitors could be useful also for other enzyme interaction studies. PMID:23717518

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

Using an innovative multiple regression procedure in a cancer population (Part 1): detecting and probing relationships of common interacting symptoms (pain, fatigue/weakness, sleep problems) as a strategy to discover influential symptom pairs and clusters.

PubMed

Francoeur, Richard B

2015-01-01

The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain-fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain-fatigue/weakness-sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial.

Nanoparticle-Enhanced Plasmonic Biosensor for Digital Biomarker Detection in a Microarray.

PubMed

Belushkin, Alexander; Yesilkoy, Filiz; Altug, Hatice

2018-05-22

Nanoplasmonic devices have become a paradigm for biomolecular detection enabled by enhanced light-matter interactions in the fields from biological and pharmaceutical research to medical diagnostics and global health. In this work, we present a bright-field imaging plasmonic biosensor that allows visualization of single subwavelength gold nanoparticles (NPs) on large-area gold nanohole arrays (Au-NHAs). The sensor generates image heatmaps that reveal the locations of single NPs as high-contrast spikes, enabling the detection of individual NP-labeled molecules. We implemented the proposed method in a sandwich immunoassay for the detection of biotinylated bovine serum albumin (bBSA) and human C-reactive protein (CRP), a clinical biomarker of acute inflammatory diseases. Our method can detect 10 pg/mL of bBSA and 27 pg/mL CRP in 2 h, which is at least 4 orders of magnitude lower than the clinically relevant concentrations. Our sensitive and rapid detection approach paired with the robust large-area plasmonic sensor chips, which are fabricated using scalable and low-cost manufacturing, provides a powerful platform for multiplexed biomarker detection in various settings.

Colorimetric detection of cholesterol based on enzyme modified gold nanoparticles

NASA Astrophysics Data System (ADS)

Nirala, Narsingh R.; Saxena, Preeti S.; Srivastava, Anchal

2018-02-01

We develop a simple colorimetric method for determination of free cholesterol in aqueous solution based on functionalized gold nanoparticles with cholesterol oxidase. Functionalized gold nanoparticles interact with free cholesterol to produce H2O2 in proportion to the level of cholesterol visually is being detected. The quenching in optical properties and agglomeration of functionalized gold nanoparticles play a key role in cholesterol sensing due to the electron accepting property of H2O2. While the lower ranges of cholesterol (lower detection limit i.e. 0.2 mg/dL) can be effectively detected using fluorescence study, the absorption study attests evident visual color change which becomes effective for detection of higher ranges of cholesterol (lower detection limit i.e. 19 mg/dL). The shades of red gradually change to blue/purple as the level of cholesterol detected (as evident at 100 mg/dL) using unaided eye without the use of expensive instruments. The potential of the proposed method to be applied in the field is shown by the proposed cholesterol measuring color wheel.

Developing a fluorescence-coupled capillary electrophoresis based method to probe interactions between QDs and colorectal cancer targeting peptides.

PubMed

Liu, Feifei; Wang, Jianhao; Yang, Li; Liu, Li; Ding, Shumin; Fu, Minli; Deng, Linhong; Gao, Li-Qian

2016-08-01

As is well known, quantum dots (QDs) have become valuable probes for cancer imaging. In particular, QD-labeled targeting peptides are capable of identifying cancer or tumors cells. A new colorectal cancer targeting peptide, cyclo(1, 9)-CTPSPFSHC, has strong targeting ability and also shows great potential in the identification and treatment of colon cancer. Herein, we synthesized a dual functional polypeptide, cyclo(1, 9)-CTPSPFSHCD2 G2 DP9 G3 H6 (H6 -TCP), to investigate its interaction with QDs inside the capillary. Fluorescence-coupled CE was adopted and applied to characterize the self-assembly of H6 -TCP onto QDs. It was indicated that the formation of the assembly was affected by H6 -TCP/QD molar ratio and sampling time. This novel in-capillary assay greatly reduced the sample consumption and the detection time, which was beneficial for the environment. It is expected that this kind of detection method could find more applications to provide more useful information for cancer diagnosis and detection of harm and hazardous substances/organisms in the environment in the future. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Supramolecular interaction of methotrexate with cucurbit[7]uril and analytical application

NASA Astrophysics Data System (ADS)

Chang, Yin-Xia; Zhang, Xiang-Mei; Duan, Xue-Chao; Liu, Fan; Du, Li-Ming

2017-08-01

The supramolecular interaction between cucurbit[7]uril (CB[7]) as the host and the anti-cancer drug methotrexate (MTX) as the guest was studied using fluorescence spectroscopy, UV-visible absorption spectroscopy, 1H NMR, 2D NOESY, and theoretical calculations. The experimental results confirmed the formation of 1:2 inclusion complex with CB[7] and indicated a simple and sensitive competitive method for the fluorescence detection of MTX. It was found that the fluorescence intensities of CB[7]-palmatine, CB[7]-berberine and CB[7]-coptisine were quenched linearly upon the addition of MTX. The linear ranges obtained in the detection of MTX were 0.1-15 μg mL- 1, 0.2-15 μg mL- 1, and 0.4-15 μg mL- 1 with detection limits of 0.03 μg mL-1, 0.06 μg mL-1, and 0.13 μg mL-1, respectively. This method can be used for the determination of MTX in biological fluids. These results suggested that cucurbit[7]uril is a promising drug carrier for targeted MTX delivery and monitoring, with improved efficacy and reduced toxicity in normal tissues.

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature

PubMed Central

2011-01-01

Background The selection of relevant articles for curation, and linking those articles to experimental techniques confirming the findings became one of the primary subjects of the recent BioCreative III contest. The contest’s Protein-Protein Interaction (PPI) task consisted of two sub-tasks: Article Classification Task (ACT) and Interaction Method Task (IMT). ACT aimed to automatically select relevant documents for PPI curation, whereas the goal of IMT was to recognise the methods used in experiments for identifying the interactions in full-text articles. Results We proposed and compared several classification-based methods for both tasks, employing rich contextual features as well as features extracted from external knowledge sources. For IMT, a new method that classifies pair-wise relations between every text phrase and candidate interaction method obtained promising results with an F1 score of 64.49%, as tested on the task’s development dataset. We also explored ways to combine this new approach and more conventional, multi-label document classification methods. For ACT, our classifiers exploited automatically detected named entities and other linguistic information. The evaluation results on the BioCreative III PPI test datasets showed that our systems were very competitive: one of our IMT methods yielded the best performance among all participants, as measured by F1 score, Matthew’s Correlation Coefficient and AUC iP/R; whereas for ACT, our best classifier was ranked second as measured by AUC iP/R, and also competitive according to other metrics. Conclusions Our novel approach that converts the multi-class, multi-label classification problem to a binary classification problem showed much promise in IMT. Nevertheless, on the test dataset the best performance was achieved by taking the union of the output of this method and that of a multi-class, multi-label document classifier, which indicates that the two types of systems complement each other in terms of recall. For ACT, our system exploited a rich set of features and also obtained encouraging results. We examined the features with respect to their contributions to the classification results, and concluded that contextual words surrounding named entities, as well as the MeSH headings associated with the documents were among the main contributors to the performance. PMID:22151769

Imaging and Elastometry of Blood Clots Using Magnetomotive Optical Coherence Tomography and Labeled Platelets.

PubMed

Oldenburg, Amy L; Wu, Gongting; Spivak, Dmitry; Tsui, Frank; Wolberg, Alisa S; Fischer, Thomas H

2011-07-21

Improved methods for imaging and assessment of vascular defects are needed for directing treatment of cardiovascular pathologies. In this paper, we employ magnetomotive optical coherence tomography (MMOCT) as a platform both to detect and to measure the elasticity of blood clots. Detection is enabled through the use of rehydrated, lyophilized platelets loaded with superparamagnetic iron oxides (SPIO-RL platelets) that are functional infusion agents that adhere to sites of vascular endothelial damage. Evidence suggests that the sensitivity for detection is improved over threefold by magnetic interactions between SPIOs inside RL platelets. Using the same MMOCT system, we show how elastometry of simulated clots, using resonant acoustic spectroscopy, is correlated with the fibrin content of the clot. Both methods are based upon magnetic actuation and phase-sensitive optical monitoring of nanoscale displacements using MMOCT, underscoring its utility as a broad-based platform to detect and measure the molecular structure and composition of blood clots.

Simple colorimetric detection of doxycycline and oxytetracycline using unmodified gold nanoparticles

NASA Astrophysics Data System (ADS)

Li, Jie; Fan, Shumin; Li, Zhigang; Xie, Yuanzhe; Wang, Rui; Ge, Baoyu; Wu, Jing; Wang, Ruiyong

2014-08-01

The interaction between tetracycline antibiotics and gold nanoparticles was studied. With citrate-coated gold nanoparticles as colorimetric probe, a simple and rapid detection method for doxycycline and oxytetracycline has been developed. This method relies on the distance-dependent optical properties of gold nanoparticles. In weakly acidic buffer medium, doxycycline and oxytetracycline could rapidly induce the aggregation of gold nanoparticles, resulting in red-to-blue (or purple) colour change. The experimental parameters were optimized with regard to pH, the concentration of the gold nanoparticles and the reaction time. Under optimal experimental conditions, the linear range of the colorimetric sensor for doxycycline/oxytetracycline was 0.06-0.66 and 0.59-8.85 μg mL-1, respectively. The corresponding limit of detection for doxycycline and oxytetracycline was 0.0086 and 0.0838 μg mL-1, respectively. This assay was sensitive, selective, simple and readily used to detect tetracycline antibiotics in food products.

Gold Nanorods as Plasmonic Sensors for Particle Diffusion.

PubMed

Wulf, Verena; Knoch, Fabian; Speck, Thomas; Sönnichsen, Carsten

2016-12-01

Plasmonic gold nanoparticles are normally used as sensor to detect analytes permanently bound to their surface. If the interaction between the analyte and the nanosensor surface is negligible, it only diffuses through the sensor's sensing volume, causing a small temporal shift of the plasmon resonance position. By using a very sensitive and fast detection scheme, we are able to detect these small fluctuations in the plasmon resonance. With the help of a theoretical model consistent with our detection geometry, we determine the analyte's diffusion coefficient. The method is verified by observing the trends upon changing diffusor size and medium viscosity, and the diffusion coefficients obtained were found to reflect reduced diffusion close to a solid interface. Our method, which we refer to as NanoPCS (for nanoscale plasmon correlation spectroscopy), is of practical importance for any application involving the diffusion of analytes close to nanoparticles.

Optical resonance-enhanced absorption-based near-field immunochip biosensor for allergen detection.

PubMed

Maier, Irene; Morgan, Michael R A; Lindner, Wolfgang; Pittner, Fritz

2008-04-15

An optical immunochip biosensor has been developed as a rapid method for allergen detection in complex food matrixes, and its application evaluated for the detection of the egg white allergens, ovalbumin and ovomucoid. The optical near-field phenomenon underlying the basic principle of the sensor design is called resonance-enhanced absorption (REA), which utilizes gold nanoparticles (Au NPs) as signal transducers in a highly sensitive interferometric setup. Using this approach, a novel, simple, and rapid colorimetric solid-phase immunoassay on a planar chip substrate was realized in direct and sandwich assay formats, with a detection system that does not require any instrumentation for readout. Semiquantitative immunochemical responses are directly visible to the naked eye of the analyst. The biosensor shows concentration-dependent color development by capturing antibody-functionalized Au NPs on allergen-coated chips and has a detection limit of 1 ng/mL. To establish a rapid method, we took advantage of the physicochemical microenvironment of the Au NP-antibody bioconjugate to be bound directly over an interacting poly(styrene-methyl methacrylate) interlayer by an immobilized antigen. In the direct assay format, a coating time with allergen of only 5 min under "soft" nondenaturing conditions was sufficient for accurate reproducibility and sensitivity. In conclusion, the REA-based immunochip sensor is easy to fabricate, is reproducible and selective in its performance, has minimal technical requirements, and will enable high-throughput screening of affinity binding interactions in technological and medical applications.

Theoretical limitations of quantification for noncompetitive sandwich immunoassays.

PubMed

Woolley, Christine F; Hayes, Mark A; Mahanti, Prasun; Douglass Gilman, S; Taylor, Tom

2015-11-01

Immunoassays exploit the highly selective interaction between antibodies and antigens to provide a vital method for biomolecule detection at low concentrations. Developers and practitioners of immunoassays have long known that non-specific binding often restricts immunoassay limits of quantification (LOQs). Aside from non-specific binding, most efforts by analytical chemists to reduce the LOQ for these techniques have focused on improving the signal amplification methods and minimizing the limitations of the detection system. However, with detection technology now capable of sensing single-fluorescence molecules, this approach is unlikely to lead to dramatic improvements in the future. Here, fundamental interactions based on the law of mass action are analytically connected to signal generation, replacing the four- and five-parameter fittings commercially used to approximate sigmoidal immunoassay curves and allowing quantitative consideration of non-specific binding and statistical limitations in order to understand the ultimate detection capabilities of immunoassays. The restrictions imposed on limits of quantification by instrumental noise, non-specific binding, and counting statistics are discussed based on equilibrium relations for a sandwich immunoassay. Understanding the maximal capabilities of immunoassays for each of these regimes can greatly assist in the development and evaluation of immunoassay platforms. While many studies suggest that single molecule detection is possible through immunoassay techniques, here, it is demonstrated that the fundamental limit of quantification (precision of 10 % or better) for an immunoassay is approximately 131 molecules and this limit is based on fundamental and unavoidable statistical limitations.

Capturing and concentrating adenovirus using magnetic anionic nanobeads

PubMed Central

Sakudo, Akikazu; Baba, Koichi; Ikuta, Kazuyoshi

2016-01-01

We recently demonstrated how various enveloped viruses can be efficiently concentrated using magnetic beads coated with an anionic polymer, poly(methyl vinyl ether-maleic anhydrate). However, the exact mechanism of interaction between the virus particles and anionic beads remains unclear. To further investigate whether these magnetic anionic beads specifically bind to the viral envelope, we examined their potential interaction with a nonenveloped virus (adenovirus). The beads were incubated with either adenovirus-infected cell culture medium or nasal aspirates from adenovirus-infected individuals and then separated from the supernatant by applying a magnetic field. After thoroughly washing the beads, adsorption of adenovirus was confirmed by a variety of techniques, including immunochromatography, polymerase chain reaction, Western blotting, and cell culture infection assays. These detection methods positively identified the hexon and penton capsid proteins of adenovirus along with the viral genome on the magnetic beads. Furthermore, various types of adenovirus including Types 5, 6, 11, 19, and 41 were captured using the magnetic bead procedure. Our bead capture method was also found to increase the sensitivity of viral detection. Adenovirus below the detectable limit for immunochromatography was efficiently concentrated using the magnetic bead procedure, allowing the virus to be successfully detected using this methodology. Moreover, these findings clearly demonstrate that a viral envelope is not required for binding to the anionic magnetic beads. Taken together, our results show that this capture procedure increases the sensitivity of detection of adenovirus and would, therefore, be a valuable tool for analyzing both clinical and experimental samples. PMID:27274228

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

Predicting protein complexes using a supervised learning method combined with local structural information.

PubMed

Dong, Yadong; Sun, Yongqi; Qin, Chao

2018-01-01

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

APTS and rGO co-functionalized pyrenated fluorescent nanonets for representative vapor phase nitroaromatic explosive detection

NASA Astrophysics Data System (ADS)

Guo, Linjuan; Zu, Baiyi; Yang, Zheng; Cao, Hongyu; Zheng, Xuefang; Dou, Xincun

2014-01-01

For the first time, flexible PVP/pyrene/APTS/rGO fluorescent nanonets were designed and synthesized via a one-step electrospinning method to detect representative subsaturated nitroaromatic explosive vapor. The functional fluorescent nanonets, which were highly stable in air, showed an 81% quenching efficiency towards TNT vapor (~10 ppb) with an exposure time of 540 s at room temperature. The nice performance of the nanonets was ascribed to the synergistic effects induced by the specific adsorption properties of APTS, the fast charge transfer properties and the effective π-π interaction with pyrene and TNT of rGO. Compared to the analogues of TNT, the PVP/pyrene/APTS/rGO nanonets showed notable selectivity towards TNT and DNT vapors. The explored functionalization method opens up brand new insight into sensitive and selective detection of vapor phase nitroaromatic explosives.For the first time, flexible PVP/pyrene/APTS/rGO fluorescent nanonets were designed and synthesized via a one-step electrospinning method to detect representative subsaturated nitroaromatic explosive vapor. The functional fluorescent nanonets, which were highly stable in air, showed an 81% quenching efficiency towards TNT vapor (~10 ppb) with an exposure time of 540 s at room temperature. The nice performance of the nanonets was ascribed to the synergistic effects induced by the specific adsorption properties of APTS, the fast charge transfer properties and the effective π-π interaction with pyrene and TNT of rGO. Compared to the analogues of TNT, the PVP/pyrene/APTS/rGO nanonets showed notable selectivity towards TNT and DNT vapors. The explored functionalization method opens up brand new insight into sensitive and selective detection of vapor phase nitroaromatic explosives. Electronic supplementary information (ESI) available: Vapor pressure of TNT and its analogues, fluorescence quenching kinetics, fluorescence quenching efficiencies and additional SEM images. See DOI: 10.1039/c3nr04960d

Detection of specific protein-protein interactions in nanocages by engineering bipartite FlAsH binding sites.

PubMed

Cornell, Thomas A; Fu, Jing; Newland, Stephanie H; Orner, Brendan P

2013-11-06

Proteins that form cage-like structures have been of much recent cross-disciplinary interest due to their application to bioconjugate and materials chemistry, their biological functions spanning multiple essential cellular processes, and their complex structure, often defined by highly symmetric protein–protein interactions. Thus, establishing the fundamentals of their formation, through detecting and quantifying important protein–protein interactions, could be crucial to understanding essential cellular machinery, and for further development of protein-based technologies. Herein we describe a method to monitor the assembly of protein cages by detecting specific, oligomerization state dependent, protein–protein interactions. Our strategy relies on engineering protein monomers to include cysteine pairs that are presented proximally if the cage state assembles. These assembled pairs of cysteines act as binding sites for the fluorescent reagent FlAsH, which, once bound, provides a readout for successful oligomerization. As a proof of principle, we applied this technique to the iron storage protein, DNA-binding protein from starved cells from E. coli. Several linker lengths and conformations for the presentation of the cysteine pairs were screened to optimize the engineered binding sites. We confirmed that our designs were successful in both lysates and with purified proteins, and that FlAsH binding was dependent upon cage assembly. Following successful characterization of the assay, its throughput was expanded. A two-dimension matrix of pH and denaturing buffer conditions was screened to optimize nanocage stability. We intend to use this method for the high throughput screening of protein cage libraries and of conditions for the generation of inorganic nanoparticles within the cavity of these and other cage proteins.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Method for Determining the Sensitivity of a Physical Security System.

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

Speed, Ann; Gauthier, John H.; Hoffman, Matthew John

Modern systems, such as physical security systems, are often designed to involve complex interactions of technological and human elements. Evaluation of the performance of these systems often overlooks the human element. A method is proposed here to expand the concept of sensitivity—as denoted by d’—from signal detection theory (Green & Swets 1966; Macmillan & Creelman 2005), which came out of the field of psychophysics, to cover not only human threat detection but also other human functions plus the performance of technical systems in a physical security system, thereby including humans in the overall evaluation of system performance. New in thismore » method is the idea that probabilities of hits (accurate identification of threats) and false alarms (saying “threat” when there is not one), which are used to calculate d’ of the system, can be applied to technologies and, furthermore, to different functions in the system beyond simple yes-no threat detection. At the most succinct level, the method returns a single number that represents the effectiveness of a physical security system; specifically, the balance between the handling of actual threats and the distraction of false alarms. The method can be automated, and the constituent parts revealed, such that given an interaction graph that indicates the functional associations of system elements and the individual probabilities of hits and false alarms for those elements, it will return the d’ of the entire system as well as d’ values for individual parts. The method can also return a measure of the response bias* of the system. One finding of this work is that the d’ for a physical security system can be relatively poor in spite of having excellent d’s for each of its individual functional elements.« less

Detection of Cu2+ in Water Based on Histidine-Gold Labeled Multiwalled Carbon Nanotube Electrochemical Sensor

PubMed Central

Zhu, Rilong; Zhou, Gangqiang; Tang, Fengxia; Wang, Yeyao

2017-01-01

Based on the strong interaction between histidine and copper ions and the signal enhancement effect of gold-labeling carbon nanotubes, an electrochemical sensor is established and used to measure copper ions in river water. In this study the results show that the concentrations of copper ion have well linear relationship with the peak current in the range of 10−11–10−7 mol/L, and the limit of detection is 10−12 mol/L. When using this method to detect copper ions in the Xiangjiang River, the test results are consistent with the atomic absorption method. This study shows that the sensor is convenient to be used in daily monitoring of copper ions in river water. PMID:28408929

Tracking time-varying causality and directionality of information flow using an error reduction ratio test with applications to electroencephalography data.

PubMed

Zhao, Yifan; Billings, Steve A; Wei, Hualiang; Sarrigiannis, Ptolemaios G

2012-11-01

This paper introduces an error reduction ratio-causality (ERR-causality) test that can be used to detect and track causal relationships between two signals. In comparison to the traditional Granger method, one significant advantage of the new ERR-causality test is that it can effectively detect the time-varying direction of linear or nonlinear causality between two signals without fitting a complete model. Another important advantage is that the ERR-causality test can detect both the direction of interactions and estimate the relative time shift between the two signals. Numerical examples are provided to illustrate the effectiveness of the new method together with the determination of the causality between electroencephalograph signals from different cortical sites for patients during an epileptic seizure.

Using Pool-seq to Search for Genomic Regions Affected by Hybrid Inviability in the copepod T. californicus.

PubMed

Lima, Thiago G; Willett, Christopher S

2018-05-11

The formation of reproductive barriers between allopatric populations involves the accumulation of incompatibilities that lead to intrinsic postzygotic isolation. The evolution of these incompatibilities is usually explained by the Dobzhansky-Muller model, where epistatic interactions that arise within the diverging populations, lead to deleterious interactions when they come together in a hybrid genome. These incompatibilities can lead to hybrid inviability, killing individuals with certain genotypic combinations, and causing the population's allele frequency to deviate from Mendelian expectations. Traditionally, hybrid inviability loci have been detected by genotyping individuals at different loci across the genome. However, this method becomes time consuming and expensive as the number of markers or individuals increases. Here, we test if a Pool-seq method can be used to scan the genome of F2 hybrids to detect genomic regions that are affected by hybrid inviability. We survey the genome of hybrids between 2 populations of the copepod Tigriopus californicus, and show that this method has enough power to detect even small changes in allele frequency caused by hybrid inviability. We show that allele frequency estimates in Pool-seq can be affected by the sampling of alleles from the pool of DNA during the library preparation and sequencing steps and that special considerations must be taken when aligning hybrid reads to a reference when the populations/species are divergent.

Monitoring microbial metabolites using an inductively coupled resonance circuit

PubMed Central

Karnaushenko, Daniil; Baraban, Larysa; Ye, Dan; Uguz, Ilke; Mendes, Rafael G.; Rümmeli, Mark H.; de Visser, J. Arjan G. M.; Schmidt, Oliver G.; Cuniberti, Gianaurelio; Makarov, Denys

2015-01-01

We present a new approach to monitor microbial population dynamics in emulsion droplets via changes in metabolite composition, using an inductively coupled LC resonance circuit. The signal measured by such resonance detector provides information on the magnetic field interaction with the bacterial culture, which is complementary to the information accessible by other detection means, based on electric field interaction, i.e. capacitive or resistive, as well as optical techniques. Several charge-related factors, including pH and ammonia concentrations, were identified as possible contributors to the characteristic of resonance detector profile. The setup enables probing the ionic byproducts of microbial metabolic activity at later stages of cell growth, where conventional optical detection methods have no discriminating power. PMID:26264183

Detection of phase synchronization from the data: Application to physiology

NASA Astrophysics Data System (ADS)

Rosenblum, Michael G.; Pikovsky, Arkady S.; Schäfer, Carsten; Tass, Peter; Kurths, Jürgen

2000-02-01

Synchronization of coupled oscillating systems means appearance of certain relations between their phases and frequencies. Here we use this concept in order to address the inverse problem and to reveal interaction between systems from experimental data. We discuss how the phases and frequencies can be estimated from time series and present the techniques for detection and quantification of synchronization. We apply our approach to multichannel magnetoencephalography data and records of muscle activity of a Parkinsonian patient, and also use it to analyze the cardiorespiratory interaction in humans. By means of these examples we demonstrate that our method is effective for the analysis of systems interrelation from noisy nonstationary bivariate data and provides other information than traditional correlation (spectral) techniques.

How to detect an excited atom without disturbing it or how to locate a super-mine without exploding it

NASA Technical Reports Server (NTRS)

Vaidman, Lev

1994-01-01

Possible realistic implementations of a method for interaction-free measurements, due to Elitzur and Vaidman, are proposed and discussed. It is argued that the effect can be easily demonstrated in an optical laboratory.

ELISA: Methods and Protocols

USDA-ARS?s Scientific Manuscript database

The antibody is central to the performance of an ELISA providing the basis of analyte selection and detection. It is the interaction of antibody with analyte under defined conditions that dictates the outcome of the ELISA and deviations in those conditions will impact assay performance. The aim of...

SpatialEpiApp: A Shiny web application for the analysis of spatial and spatio-temporal disease data.

PubMed

Moraga, Paula

2017-11-01

During last years, public health surveillance has been facilitated by the existence of several packages implementing statistical methods for the analysis of spatial and spatio-temporal disease data. However, these methods are still inaccesible for many researchers lacking the adequate programming skills to effectively use the required software. In this paper we present SpatialEpiApp, a Shiny web application that integrate two of the most common approaches in health surveillance: disease mapping and detection of clusters. SpatialEpiApp is easy to use and does not require any programming knowledge. Given information about the cases, population and optionally covariates for each of the areas and dates of study, the application allows to fit Bayesian models to obtain disease risk estimates and their uncertainty by using R-INLA, and to detect disease clusters by using SaTScan. The application allows user interaction and the creation of interactive data visualizations and reports showing the analyses performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Glycan profiling of monoclonal antibodies using zwitterionic-type hydrophilic interaction chromatography coupled with electrospray ionization mass spectrometry detection.

PubMed

Mauko, Lea; Nordborg, Anna; Hutchinson, Joseph P; Lacher, Nathan A; Hilder, Emily F; Haddad, Paul R

2011-01-15

We present a new method for the analysis of glycans enzymatically released from monoclonal antibodies (MAbs) employing a zwitterionic-type hydrophilic interaction chromatography (ZIC-HILIC) column coupled with electrospray ionization mass spectrometry (ESI-MS). Both native and reduced glycans were analyzed, and the developed procedure was compared with a standard HILIC procedure used in the pharmaceutical industry whereby fluorescent-labeled glycans are analyzed using a TSK Amide-80 column coupled with fluorescence detection. The separation of isobaric alditol oligosaccharides present in monoclonal antibodies and ribonuclease B is demonstrated, and ZIC-HILIC is shown to have good capability for structural recognition. Glycan profiles obtained with the ZIC-HILIC column and ESI-MS provided detailed information on MAb glycosylation, including identification of some less abundant glycan species, and are consistent with the profiles generated with the standard procedure. This new ZIC-HILIC method offers a simpler and faster approach for glycosylation analysis of therapeutic antibodies. Copyright © 2010 Elsevier Inc. All rights reserved.

Gold nanoparticles mediated colorimetric assay for HIV-Tat protein detection

NASA Astrophysics Data System (ADS)

Hashwan, Saeed S. Ba; Ruslinda, A. Rahim; Fatin, M. F.; Gopinath, Subash C. B.; Thivina, V.; Tony, V. C. S.; Arshad, M. K. Md.; Hashim, U.

2016-07-01

Gold-nanoparticle (AuNP) based colorimetric assays have been formulated for different biomolecular interactions. With this assay the probe such as antibody immobilized on the Au surface and in the presence of appropriate binding partner (antigen), will interact with each other on the Au surface. By following this strategy, herein we formulated a detection system with two anti-HIV-Tat antibodies, Mono (McAb) - and polyclonal (PcAb) by immobilizing them independently with different AuNPs. Under this condition, these two antibodies are under dispersed condition, and in the presence of HIV-Tat antigen, these molecules will be connected and forms the aggregation of AuNPs. This strategy yield rapid results, can be monitored by the spectral changes in UV-Vis spectrophotometry. Experiments were performed with two different methods using two anti-HIV-Tats monoclonal and one Polyclonal antibody against the antigen HIV-Tat. Between these methods conjugation of HIV-Tat and McAb on the AuNP followed by addition of PcAb yielded better results.

Quantification of vicine and convicine in faba bean seeds using hydrophilic interaction liquid chromatography.

PubMed

Purves, Randy W; Khazaei, Hamid; Vandenberg, Albert

2018-02-01

Faba bean (Vicia faba L.) provides environmental and health benefits; however, the presence of the pyrimidine glycosides vicine and convicine (v-c) in its seeds limits consumption. Low v-c genotypes have been introduced, but the convicine levels in these genotypes have not been quantified. To improve detection, the polar nature of v-c was exploited by implementing hydrophilic interaction liquid chromatography (HILIC). A sample preparation method using a two-step extraction was developed for use with UV and/or tandem mass spectrometry (SRM) detection. The HILIC-UV method was suitable for over three orders of magnitude, covering the range of v-c concentrations in faba bean seeds across all genotypes tested. The linear range of HILIC-SRM was slightly less (∼3 orders of magnitude), but improved sensitivity and selectivity make it more suitable for quantifying low v-c samples. The analysis of 13 genotypes suggests that v-c concentrations in faba bean seeds may be independent quantitative traits. Copyright © 2017 Elsevier Ltd. All rights reserved.

Systems and methods for detecting x-rays

DOEpatents

Bross, Alan D.; Mellott, Kerry L.; Pla-Dalmau, Anna

2006-05-02

Systems and methods for detecting x-rays are disclosed herein. One or more x-ray-sensitive scintillators can be configured from a plurality of heavy element nano-sized particles and a plastic material, such as polystyrene. As will be explained in greater detail herein, the heavy element nano-sized particles (e.g., PbWO₄) can be compounded into the plastic material with at least one dopant that permits the plastic material to scintillate. X-rays interact with the heavy element nano-sized particles to produce electrons that can deposit energy in the x-ray sensitive scintillator, which in turn can produce light.

Effect of reference genome selection on the performance of computational methods for genome-wide protein-protein interaction prediction.

PubMed

Muley, Vijaykumar Yogesh; Ranjan, Akash

2012-01-01

Recent progress in computational methods for predicting physical and functional protein-protein interactions has provided new insights into the complexity of biological processes. Most of these methods assume that functionally interacting proteins are likely to have a shared evolutionary history. This history can be traced out for the protein pairs of a query genome by correlating different evolutionary aspects of their homologs in multiple genomes known as the reference genomes. These methods include phylogenetic profiling, gene neighborhood and co-occurrence of the orthologous protein coding genes in the same cluster or operon. These are collectively known as genomic context methods. On the other hand a method called mirrortree is based on the similarity of phylogenetic trees between two interacting proteins. Comprehensive performance analyses of these methods have been frequently reported in literature. However, very few studies provide insight into the effect of reference genome selection on detection of meaningful protein interactions. We analyzed the performance of four methods and their variants to understand the effect of reference genome selection on prediction efficacy. We used six sets of reference genomes, sampled in accordance with phylogenetic diversity and relationship between organisms from 565 bacteria. We used Escherichia coli as a model organism and the gold standard datasets of interacting proteins reported in DIP, EcoCyc and KEGG databases to compare the performance of the prediction methods. Higher performance for predicting protein-protein interactions was achievable even with 100-150 bacterial genomes out of 565 genomes. Inclusion of archaeal genomes in the reference genome set improves performance. We find that in order to obtain a good performance, it is better to sample few genomes of related genera of prokaryotes from the large number of available genomes. Moreover, such a sampling allows for selecting 50-100 genomes for comparable accuracy of predictions when computational resources are limited.

Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions

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

Ma Yingliang; Housden, R. James; Razavi, Reza

2013-07-15

Purpose: X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction.Methods: In this paper, the authors presentmore » a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time.Results: The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 {+-} 0.29, 0.92 {+-} 0.61, and 0.63 {+-} 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 {+-} 0.28, 0.64 {+-} 0.37, and 0.53 {+-} 0.38 mm and success rates increased to 100%, 99.2%, and 96.5% for the CS, ablation, and lasso catheters, respectively. Subjective clinical evaluation by three experienced electrophysiologists showed that the detection and tracking results were clinically acceptable.Conclusions: The proposed detection and tracking methods are automatic and can detect and track CS, ablation, and lasso catheters simultaneously and in real-time. The accuracy of the proposed methods is sub-mm and the methods are robust toward low-dose x-ray fluoroscopic images, which are mainly used during EP procedures to maintain low radiation dose.« less

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

Functional and genomic analyses of alpha-solenoid proteins.

PubMed

Fournier, David; Palidwor, Gareth A; Shcherbinin, Sergey; Szengel, Angelika; Schaefer, Martin H; Perez-Iratxeta, Carol; Andrade-Navarro, Miguel A

2013-01-01

Alpha-solenoids are flexible protein structural domains formed by ensembles of alpha-helical repeats (Armadillo and HEAT repeats among others). While homology can be used to detect many of these repeats, some alpha-solenoids have very little sequence homology to proteins of known structure and we expect that many remain undetected. We previously developed a method for detection of alpha-helical repeats based on a neural network trained on a dataset of protein structures. Here we improved the detection algorithm and updated the training dataset using recently solved structures of alpha-solenoids. Unexpectedly, we identified occurrences of alpha-solenoids in solved protein structures that escaped attention, for example within the core of the catalytic subunit of PI3KC. Our results expand the current set of known alpha-solenoids. Application of our tool to the protein universe allowed us to detect their significant enrichment in proteins interacting with many proteins, confirming that alpha-solenoids are generally involved in protein-protein interactions. We then studied the taxonomic distribution of alpha-solenoids to discuss an evolutionary scenario for the emergence of this type of domain, speculating that alpha-solenoids have emerged in multiple taxa in independent events by convergent evolution. We observe a higher rate of alpha-solenoids in eukaryotic genomes and in some prokaryotic families, such as Cyanobacteria and Planctomycetes, which could be associated to increased cellular complexity. The method is available at http://cbdm.mdc-berlin.de/~ard2/.

Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data.

PubMed

Sariyar, Murat; Hoffmann, Isabell; Binder, Harald

2014-02-26

Molecular data, e.g. arising from microarray technology, is often used for predicting survival probabilities of patients. For multivariate risk prediction models on such high-dimensional data, there are established techniques that combine parameter estimation and variable selection. One big challenge is to incorporate interactions into such prediction models. In this feasibility study, we present building blocks for evaluating and incorporating interactions terms in high-dimensional time-to-event settings, especially for settings in which it is computationally too expensive to check all possible interactions. We use a boosting technique for estimation of effects and the following building blocks for pre-selecting interactions: (1) resampling, (2) random forests and (3) orthogonalization as a data pre-processing step. In a simulation study, the strategy that uses all building blocks is able to detect true main effects and interactions with high sensitivity in different kinds of scenarios. The main challenge are interactions composed of variables that do not represent main effects, but our findings are also promising in this regard. Results on real world data illustrate that effect sizes of interactions frequently may not be large enough to improve prediction performance, even though the interactions are potentially of biological relevance. Screening interactions through random forests is feasible and useful, when one is interested in finding relevant two-way interactions. The other building blocks also contribute considerably to an enhanced pre-selection of interactions. We determined the limits of interaction detection in terms of necessary effect sizes. Our study emphasizes the importance of making full use of existing methods in addition to establishing new ones.

Enzymatically Regulated Peptide Pairing and Catalysis for the Bioanalysis of Extracellular Prometastatic Activities of Functionally Linked Enzymes

NASA Astrophysics Data System (ADS)

Li, Hao; Huang, Yue; Yu, Yue; Li, Tianqi; Li, Genxi; Anzai, Jun-Ichi

2016-05-01

Diseases such as cancer arise from systematical reconfiguration of interactions of exceedingly large numbers of proteins in cell signaling. The study of such complicated molecular mechanisms requires multiplexed detection of the inter-connected activities of several proteins in a disease-associated context. However, the existing methods are generally not well-equipped for this kind of application. Here a method for analyzing functionally linked protein activities is developed based on enzyme controlled pairing between complementary peptide helix strands, which simultaneously enables elaborate regulation of catalytic activity of the paired peptides. This method has been used to detect three different types of protein modification enzymes that participate in the modification of extracellular matrix and the formation of invasion front in tumour. In detecting breast cancer tissue samples using this method, up-regulated activity can be observed for two of the assessed enzymes, while the third enzyme is found to have a subtle fluctuation of activity. These results may point to the application of this method in evaluating prometastatic activities of proteins in tumour.

Investigation of laser-tissue interaction in medicine by means of laser spectroscopic measurements

NASA Astrophysics Data System (ADS)

Lademann, Juergen; Weigmann, Hans-Juergen

1995-01-01

Toxic and carcinogenic substances were produced during laser application in medicine for the cutting and evaporation of tissue. The laser smoke presents a danger potential for the medical staff and the patients. The laser tissue interaction process was investigated by means of laser spectroscopic measurements which give the possibility of measuring metastable molecular states directly as a prerequisite to understand and to influence fundamental laser tissue interaction processes in order to reduce the amount of harmful chemicals. Highly excited atomic and molecular states and free radicals (CN, OH, C2, CH, CH2) have been detected applying spontaneous and laser induced fluorescence methods. It was found that the formation of harmful substances in the laser plumes can be reduced significantly by optimization of the surrounding gas atmosphere. A high content of oxygen or water in the interaction zone has been found, in agreement with the results of classical and analytical methods, as a suitable way to decrease pollutant emission. The experimental methods and the principal results are applicable not only in laser medicine but in laser material treatment generally.

The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

PubMed

Vilar, Santiago; Hripcsak, George

2017-07-01

Explosion of the availability of big data sources along with the development in computational methods provides a useful framework to study drugs' actions, such as interactions with pharmacological targets and off-targets. Databases related to protein interactions, adverse effects and genomic profiles are available to be used for the construction of computational models. In this article, we focus on the description of biological profiles for drugs that can be used as a system to compare similarity and create methods to predict and analyze drugs' actions. We highlight profiles constructed with different biological data, such as target-protein interactions, gene expression measurements, adverse effects and disease profiles. We focus on the discovery of new targets or pathways for drugs already in the pharmaceutical market, also called drug repurposing, in the interaction with off-targets responsible for adverse reactions and in drug-drug interaction analysis. The current and future applications, strengths and challenges facing all these methods are also discussed. Biological profiles or signatures are an important source of data generation to deeply analyze biological actions with important implications in drug-related studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Selection of organisms for the co-evolution-based study of protein interactions.

PubMed

Herman, Dorota; Ochoa, David; Juan, David; Lopez, Daniel; Valencia, Alfonso; Pazos, Florencio

2011-09-12

The prediction and study of protein interactions and functional relationships based on similarity of phylogenetic trees, exemplified by the mirrortree and related methodologies, is being widely used. Although dependence between the performance of these methods and the set of organisms used to build the trees was suspected, so far nobody assessed it in an exhaustive way, and, in general, previous works used as many organisms as possible. In this work we asses the effect of using different sets of organism (chosen according with various phylogenetic criteria) on the performance of this methodology in detecting protein interactions of different nature. We show that the performance of three mirrortree-related methodologies depends on the set of organisms used for building the trees, and it is not always directly related to the number of organisms in a simple way. Certain subsets of organisms seem to be more suitable for the predictions of certain types of interactions. This relationship between type of interaction and optimal set of organism for detecting them makes sense in the light of the phylogenetic distribution of the organisms and the nature of the interactions. In order to obtain an optimal performance when predicting protein interactions, it is recommended to use different sets of organisms depending on the available computational resources and data, as well as the type of interactions of interest.

Selection of organisms for the co-evolution-based study of protein interactions

PubMed Central

2011-01-01

Background The prediction and study of protein interactions and functional relationships based on similarity of phylogenetic trees, exemplified by the mirrortree and related methodologies, is being widely used. Although dependence between the performance of these methods and the set of organisms used to build the trees was suspected, so far nobody assessed it in an exhaustive way, and, in general, previous works used as many organisms as possible. In this work we asses the effect of using different sets of organism (chosen according with various phylogenetic criteria) on the performance of this methodology in detecting protein interactions of different nature. Results We show that the performance of three mirrortree-related methodologies depends on the set of organisms used for building the trees, and it is not always directly related to the number of organisms in a simple way. Certain subsets of organisms seem to be more suitable for the predictions of certain types of interactions. This relationship between type of interaction and optimal set of organism for detecting them makes sense in the light of the phylogenetic distribution of the organisms and the nature of the interactions. Conclusions In order to obtain an optimal performance when predicting protein interactions, it is recommended to use different sets of organisms depending on the available computational resources and data, as well as the type of interactions of interest. PMID:21910884

Rapid and sensitive MRM-based mass spectrometry approach for systematically exploring ganglioside-protein interactions.

PubMed

Tian, Ruijun; Jin, Jing; Taylor, Lorne; Larsen, Brett; Quaggin, Susan E; Pawson, Tony

2013-04-01

Gangliosides are ubiquitous components of cell membranes. Their interactions with bacterial toxins and membrane-associated proteins (e.g. receptor tyrosine kinases) have important roles in the regulation of multiple cellular functions. Currently, an effective approach for measuring ganglioside-protein interactions especially in a large-scale fashion is largely missing. To this end, we report a facile MS-based approach to explore gangliosides extracted from cells and measure their interactions with protein of interest globally. We optimized a two-step protocol for extracting total gangliosides from cells within 2 h. Easy-to-use magnetic beads conjugated with a protein of interest were used to capture interacting gangliosides. To measure ganglioside-protein interaction on a global scale, we applied a high-sensitive LC-MS system, containing hydrophilic interaction LC separation and multiple reaction monitoring-based MS for ganglioside detection. Sensitivity for ganglioside GM1 is below 100 pg, and the whole analysis can be done in 20 min with isocratic elution. To measure ganglioside interactions with soluble vascular endothelial growth factor receptor 1 (sFlt1), we extracted and readily detected 36 species of gangliosides from perivascular retinal pigment epithelium cells across eight different classes. Twenty-three ganglioside species have significant interactions with sFlt1 as compared with IgG control based on p value cutoff <0.05. These results show that the described method provides a rapid and high-sensitive approach for systematically measuring ganglioside-protein interactions. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection of First-Line Drug Resistance Mutations and Drug-Protein Interaction Dynamics from Tuberculosis Patients in South India.

PubMed

Nachappa, Somanna Ajjamada; Neelambike, Sumana M; Amruthavalli, Chokkanna; Ramachandra, Nallur B

2018-05-01

Diagnosis of drug-resistant tuberculosis predominantly relies on culture-based drug susceptibility testing, which take weeks to produce a result and a more time-efficient alternative method is multiplex allele-specific PCR (MAS-PCR). Also, understanding the role of mutations in causing resistance helps better drug designing. To evaluate the ability of MAS-PCR in the detection of drug resistance and to understand the mechanism of interaction of drugs with mutant proteins in Mycobacterium tuberculosis. Detection of drug-resistant mutations using MAS-PCR and validation through DNA sequencing. MAS-PCR targeted five loci on three genes, katG 315 and inhA -15 for the drug isoniazid (INH), and rpoB 516, 526, and 531 for rifampicin (RIF). Furthermore, the sequence data were analyzed to study the effect on interaction of the anti-TB drug molecule with the target protein using in silico docking. We identified drug-resistant mutations in 8 out of 114 isolates with 2 of them as multidrug-resistant TB using MAS-PCR. DNA sequencing confirmed only six of these, recording a sensitivity of 85.7% and specificity of 99.3% for MAS-PCR. Molecular docking showed estimated free energy of binding (ΔG) being higher for RIF binding with RpoB S531L mutant. Codon 315 in KatG does not directly interact with INH but blocks the drug access to active site. We propose DNA sequencing-based drug resistance detection for TB, which is more accurate than MAS-PCR. Understanding the action of resistant mutations in disrupting the normal drug-protein interaction aids in designing effective drug alternatives.

Single-well monitoring of protein-protein interaction and phosphorylation-dephosphorylation events.

PubMed

Arcand, Mathieu; Roby, Philippe; Bossé, Roger; Lipari, Francesco; Padrós, Jaime; Beaudet, Lucille; Marcil, Alexandre; Dahan, Sophie

2010-04-20

We combined oxygen channeling assays with two distinct chemiluminescent beads to detect simultaneously protein phosphorylation and interaction events that are usually monitored separately. This novel method was tested in the ERK1/2 MAP kinase pathway. It was first used to directly monitor dissociation of MAP kinase ERK2 from MEK1 upon phosphorylation and to evaluate MAP kinase phosphatase (MKP) selectivity and mechanism of action. In addition, MEK1 and ERK2 were probed with an ATP competitor and an allosteric MEK1 inhibitor, which generated distinct phosphorylation-interaction patterns. Simultaneous monitoring of protein-protein interactions and substrate phosphorylation can provide significant mechanistic insight into enzyme activity and small molecule action.

Virtual performer: single camera 3D measuring system for interaction in virtual space

NASA Astrophysics Data System (ADS)

Sakamoto, Kunio; Taneji, Shoto

2006-10-01

The authors developed interaction media systems in the 3D virtual space. In these systems, the musician virtually plays an instrument like the theremin in the virtual space or the performer plays a show using the virtual character such as a puppet. This interactive virtual media system consists of the image capture, measuring performer's position, detecting and recognizing motions and synthesizing video image using the personal computer. In this paper, we propose some applications of interaction media systems; a virtual musical instrument and superimposing CG character. Moreover, this paper describes the measuring method of the positions of the performer, his/her head and both eyes using a single camera.

Visual detection technique for efficient screening and isolation of Salmonella based on a novel enrichment assay using chromatography membrane.

PubMed

Tang, F; Xiong, Y; Zhang, H; Wu, K; Xiang, Y; Shao, J-B; Ai, H-W; Xiang, Y-P; Zheng, X-L; Lv, J-R; Sun, H; Bao, L-S; Zhang, Z; Hu, H-B; Zhang, J-Y; Chen, L; Lu, J; Liu, W-Y; Mei, H; Ma, Y; Xu, C-F; Fang, A-Y; Gu, M; Xu, C-Y; Chen, Y; Chen, Z; Sun, Z-Y

2016-03-01

To detect Salmonella more efficiently and isolate strains more easily, a novel and simple detection method that uses an enrichment assay and two chromogenic reactions on a chromatography membrane was developed. Grade 3 chromatography paper is used as functionalized solid phase support (SPS), which contains specially optimized medium. One reaction for screening is based on the sulfate-reducing capacity of Salmonella. Hydrogen sulfide (H2S) generated by Salmonella reacts with ammonium ferric citrate to produce black colored ferrous sulfide. Another reaction is based on Salmonella C8 esterase that is unique for Enterobacteriaceae except Serratia and interacts with 4-methylumbelliferyl caprylate (MUCAP) to produce fluorescent umbelliferone, which is visible under ultraviolet light. A very low detection limit (10(1) CFU ml(-1)) for Salmonella was achieved on the background of 10(5) CFU ml(-1) Escherichia coli. More importantly, testing with more than 1,000 anal samples indicated that our method has a high positive detection rate and is relatively low cost, compared with the traditional culture-based method. It took only 1 day for the preliminary screening and 2 days to efficiently isolate the Salmonella cells, indicating that the new assay is specific, rapid, and simple for Salmonella detection. In contrast to the traditional culture-based method, this method can be easily used to screen and isolate targeted strains with the naked eye. The results of quantitative and comparative experiments showed that the visual detection technique is an efficient alternative method for the screening of Salmonella spp. in many applications of large-sized samples related to public health surveillance.

Collision detection and modeling of rigid and deformable objects in laparoscopic simulator

NASA Astrophysics Data System (ADS)

Dy, Mary-Clare; Tagawa, Kazuyoshi; Tanaka, Hiromi T.; Komori, Masaru

2015-03-01

Laparoscopic simulators are viable alternatives for surgical training and rehearsal. Haptic devices can also be incorporated with virtual reality simulators to provide additional cues to the users. However, to provide realistic feedback, the haptic device must be updated by 1kHz. On the other hand, realistic visual cues, that is, the collision detection and deformation between interacting objects must be rendered at least 30 fps. Our current laparoscopic simulator detects the collision between a point on the tool tip, and on the organ surfaces, in which haptic devices are attached on actual tool tips for realistic tool manipulation. The triangular-mesh organ model is rendered using a mass spring deformation model, or finite element method-based models. In this paper, we investigated multi-point-based collision detection on the rigid tool rods. Based on the preliminary results, we propose a method to improve the collision detection scheme, and speed up the organ deformation reaction. We discuss our proposal for an efficient method to compute simultaneous multiple collision between rigid (laparoscopic tools) and deformable (organs) objects, and perform the subsequent collision response, with haptic feedback, in real-time.

Proteins detection by polymer optical fibers sensitised with overlayers of block and random copolymers

NASA Astrophysics Data System (ADS)

El Sachat, Alexandros; Meristoudi, Anastasia; Markos, Christos; Pispas, Stergios; Riziotis, Christos

2014-03-01

A low cost and low complexity optical detection method of proteins is presented by employing a detection scheme based on electrostatic interactions, and implemented by sensitization of a polymer optical fibers' (POF) surface by thin overlayers of properly designed sensitive copolymer materials with predesigned charges. This method enables the fast detection of proteins having opposite charge to the overlayer, and also the effective discrimination of differently charged proteins like lysozyme (LYS) and bovine serum albumin (BSA). As sensitive materials the block and the random copolymers of the same monomers were employed, namely the block copolymer poly(styrene-b-2vinylpyridine) (PS-b- P2VP) and the corresponding random copolymer poly(styrene-r-2vinylpyridine) (PS-r-P2VP), of similar composition and molecular weights. Results show systematically different response between the block and the random copolymers, although of the same order of magnitude, drawing thus important conclusions on their applications' techno-economic aspects given that they have significantly different associated manufacturing method and costs. The use of the POF platform, in combination with those adaptable copolymer sensing materials could lead to efficient low cost bio-detection schemes.

The case-only test for gene-environment interaction is not uniformly powerful: an empirical example

PubMed Central

Wu, Chen; Chang, Jiang; Ma, Baoshan; Miao, Xiaoping; Zhou, Yifeng; Liu, Yu; Li, Yun; Wu, Tangchun; Hu, Zhibin; Shen, Hongbing; Jia, Weihua; Zeng, Yixin; Lin, Dongxin; Kraft, Peter

2016-01-01

The case-only test has been proposed as a more powerful approach to detect gene-environment (G×E) interactions. This approach assumes that the genetic and environmental factors are independent. While it is well known that Type I error rate will increase if this assumption is violated, it is less widely appreciated that gene-environment correlation can also lead to power loss. We illustrate this phenomenon by comparing the performance of the case-only test to other approaches to detect G×E interactions in a genome-wide association study of esophageal squamous carcinoma (ESCC) in Chinese populations. Some of these approaches do not use information on the correlation between exposure and genotype (standard logistic regression), while others seek to use this information in a robust fashion to boost power without increasing Type I error (two-step, empirical Bayes and cocktail methods). G×E interactions were identified involving drinking status and two regions containing genes in the alcohol metabolism pathway, 4q23 and 12q24. Although the case-only test yielded the most significant tests of G×E interaction in the 4q23 region, the case-only test failed to identify significant interactions in the 12q24 region which were readily identified using other approaches. The low power of the case-only test in the 12q24 region is likely due to the strong inverse association between the SNPs in this region and drinking status. This example underscores the need to consider multiple approaches to detect gene-environment interactions, as different tests are more or less sensitive to different alternative hypotheses and violations of the gene-environment independence assumption. PMID:23595356

HiTAD: detecting the structural and functional hierarchies of topologically associating domains from chromatin interactions

PubMed Central

Wang, Xiao-Tao; Cui, Wang

2017-01-01

Abstract A current question in the high-order organization of chromatin is whether topologically associating domains (TADs) are distinct from other hierarchical chromatin domains. However, due to the unclear TAD definition in tradition, the structural and functional uniqueness of TAD is not well studied. In this work, we refined TAD definition by further constraining TADs to the optimal separation on global intra-chromosomal interactions. Inspired by this constraint, we developed a novel method, called HiTAD, to detect hierarchical TADs from Hi-C chromatin interactions. HiTAD performs well in domain sensitivity, replicate reproducibility and inter cell-type conservation. With a novel domain-based alignment proposed by us, we defined several types of hierarchical TAD changes which were not systematically studied previously, and subsequently used them to reveal that TADs and sub-TADs differed statistically in correlating chromosomal compartment, replication timing and gene transcription. Finally, our work also has the implication that the refinement of TAD definition could be achieved by only utilizing chromatin interactions, at least in part. HiTAD is freely available online. PMID:28977529

MPQ-cytometry: a magnetism-based method for quantification of nanoparticle-cell interactions

NASA Astrophysics Data System (ADS)

Shipunova, V. O.; Nikitin, M. P.; Nikitin, P. I.; Deyev, S. M.

2016-06-01

Precise quantification of interactions between nanoparticles and living cells is among the imperative tasks for research in nanobiotechnology, nanotoxicology and biomedicine. To meet the challenge, a rapid method called MPQ-cytometry is developed, which measures the integral non-linear response produced by magnetically labeled nanoparticles in a cell sample with an original magnetic particle quantification (MPQ) technique. MPQ-cytometry provides a sensitivity limit 0.33 ng of nanoparticles and is devoid of a background signal present in many label-based assays. Each measurement takes only a few seconds, and no complicated sample preparation or data processing is required. The capabilities of the method have been demonstrated by quantification of interactions of iron oxide nanoparticles with eukaryotic cells. The total amount of targeted nanoparticles that specifically recognized the HER2/neu oncomarker on the human cancer cell surface was successfully measured, the specificity of interaction permitting the detection of HER2/neu positive cells in a cell mixture. Moreover, it has been shown that MPQ-cytometry analysis of a HER2/neu-specific iron oxide nanoparticle interaction with six cell lines of different tissue origins quantitatively reflects the HER2/neu status of the cells. High correlation of MPQ-cytometry data with those obtained by three other commonly used in molecular and cell biology methods supports consideration of this method as a prospective alternative for both quantifying cell-bound nanoparticles and estimating the expression level of cell surface antigens. The proposed method does not require expensive sophisticated equipment or highly skilled personnel and it can be easily applied for rapid diagnostics, especially under field conditions.Precise quantification of interactions between nanoparticles and living cells is among the imperative tasks for research in nanobiotechnology, nanotoxicology and biomedicine. To meet the challenge, a rapid method called MPQ-cytometry is developed, which measures the integral non-linear response produced by magnetically labeled nanoparticles in a cell sample with an original magnetic particle quantification (MPQ) technique. MPQ-cytometry provides a sensitivity limit 0.33 ng of nanoparticles and is devoid of a background signal present in many label-based assays. Each measurement takes only a few seconds, and no complicated sample preparation or data processing is required. The capabilities of the method have been demonstrated by quantification of interactions of iron oxide nanoparticles with eukaryotic cells. The total amount of targeted nanoparticles that specifically recognized the HER2/neu oncomarker on the human cancer cell surface was successfully measured, the specificity of interaction permitting the detection of HER2/neu positive cells in a cell mixture. Moreover, it has been shown that MPQ-cytometry analysis of a HER2/neu-specific iron oxide nanoparticle interaction with six cell lines of different tissue origins quantitatively reflects the HER2/neu status of the cells. High correlation of MPQ-cytometry data with those obtained by three other commonly used in molecular and cell biology methods supports consideration of this method as a prospective alternative for both quantifying cell-bound nanoparticles and estimating the expression level of cell surface antigens. The proposed method does not require expensive sophisticated equipment or highly skilled personnel and it can be easily applied for rapid diagnostics, especially under field conditions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03507h

Constrained Kinematics of ICMEs from Multi-point in Situ and Heliospheric Imaging Data

NASA Astrophysics Data System (ADS)

Rollett, T.; Temmer, M.; Moestl, C.; Veronig, A. M.; Lugaz, N.; Vrsnak, B.; Farrugia, C. J.; Amerstorfer, U.

2013-12-01

The constrained harmonic mean (CHM) method is used to calculate the direction of motion of ICMEs and their kinematical profiles. Combining single spacecraft white-light observations from STEREO/HI with supplementary in situ data, it is possible to derive the propagation speed varying with heliocentric distance. This is a big advantage against other single-viewpoint methods, i.e. fitting methods, which assume a constant propagation speed. We show two different applications for the CHM method: first, an analysis of the interaction between the solar wind and ICMEs, and second, the interaction between two ICMEs. For analyzing interaction processes it is crucial to use a method that has the ability to investigate the corresponding effects on ICME kinematics. Additionally, we show the analysis of an outstanding fast ICME event of March 2012, which was detected in situ by Venus Express, Messenger and Wind and also observed by STEREO-A/HI. Due to these multiple in situ measurements it was possible to constrain the ICME kinematics by three different boundary values. These studies are fundamental in order to deepen the understanding of ICME evolution and to enhance existing forecasting methods. This work has received funding from the European Commission FP7 Project COMESEP (263252).

BiFC Assay to Detect Calmodulin Binding to Plant Receptor Kinases.

PubMed

Fischer, Cornelia; Sauter, Margret; Dietrich, Petra

2017-01-01

Plant receptor-like kinases (RLKs) are regulated at various levels including posttranscriptional modification and interaction with regulatory proteins. Calmodulin (CaM) is a calcium-sensing protein that was shown to bind to some RLKs such as the PHYTOSULFOKINE RECEPTOR1 (PSKR1). The CaM-binding site is embedded in subdomain VIa of the kinase domain. It is possible that many more of RLKs interact with CaM than previously described. To unequivocally confirm CaM binding, several methods exist. Bimolecular fluorescence complementation (BiFC) and pull-down assays have been successfully used to study CaM binding to PSKR1 and are described in this chapter (BiFC) and in Chapter 15 (pull down). The two methods are complementary. BiFC is useful to show localization and interaction of soluble as well as of membrane-bound proteins in planta.

Electrochemical Detection of the Molecules of Life

NASA Technical Reports Server (NTRS)

Thomson, Seamus; Quinn, Richard; Koehne, Jessica

2017-01-01

All forms of life on Earth contain cellular machinery that can transform and regulate chemical energy through metabolic pathways. These processes are oxidation-reduction reactions that are performed by four key classes of molecules: flavins, nicotinamaides, porphyrins, and quinones. By detecting the electrochemical interaction of these redox-active molecules with an electrode, a method of differentiating them by their class could be established and incorporated into future life-detecting missions. This body of work investigates the electrochemistry of ubiquitous molecules found in life and how they may be detected. Molecules can oxidise or reduce the surface of an electrode - giving or receiving electrons - and these interactions are represented by changes in current with respect to an applied voltage. This relationship varies with: electrolyte type and concentration, working electrode material, the redox-active molecule itself, and scan rate. Flavin adenine dinucleotide (FAD), riboflavin, nicotinamide adenine dinucleotide (NADH), and anthraquinone are all molecules found intracellularly in almost all living organisms. An organism-synthesised extracellular redox-active molecule, Plumbagin, was also selected as part of this study. The goal of this work is to detect these molecules in seawater and assess its application in searching for life on Ocean Worlds.

Evidence for gene-gene epistatic interactions among susceptibility loci for systemic lupus erythematosus.

PubMed

Hughes, Travis; Adler, Adam; Kelly, Jennifer A; Kaufman, Kenneth M; Williams, Adrienne H; Langefeld, Carl D; Brown, Elizabeth E; Alarcón, Graciela S; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Petri, Michelle; Boackle, Susan A; Stevens, Anne M; Reveille, John D; Sanchez, Elena; Martín, Javier; Niewold, Timothy B; Vilá, Luis M; Scofield, R Hal; Gilkeson, Gary S; Gaffney, Patrick M; Criswell, Lindsey A; Moser, Kathy L; Merrill, Joan T; Jacob, Chaim O; Tsao, Betty P; James, Judith A; Vyse, Timothy J; Alarcón-Riquelme, Marta E; Harley, John B; Richardson, Bruce C; Sawalha, Amr H

2012-02-01

Several confirmed genetic susceptibility loci for lupus have been described. To date, no clear evidence for genetic epistasis in lupus has been established. The aim of this study was to test for gene-gene interactions in a number of known lupus susceptibility loci. Eighteen single-nucleotide polymorphisms tagging independent and confirmed lupus susceptibility loci were genotyped in a set of 4,248 patients with lupus and 3,818 normal healthy control subjects of European descent. Epistasis was tested by a 2-step approach using both parametric and nonparametric methods. The false discovery rate (FDR) method was used to correct for multiple testing. We detected and confirmed gene-gene interactions between the HLA region and CTLA4, IRF5, and ITGAM and between PDCD1 and IL21 in patients with lupus. The most significant interaction detected by parametric analysis was between rs3131379 in the HLA region and rs231775 in CTLA4 (interaction odds ratio 1.19, Z = 3.95, P = 7.8 × 10(-5) [FDR ≤0.05], P for multifactor dimensionality reduction = 5.9 × 10(-45)). Importantly, our data suggest that in patients with lupus, the presence of the HLA lupus risk alleles in rs1270942 and rs3131379 increases the odds of also carrying the lupus risk allele in IRF5 (rs2070197) by 17% and 16%, respectively (P = 0.0028 and P = 0.0047, respectively). We provide evidence for gene-gene epistasis in systemic lupus erythematosus. These findings support a role for genetic interaction contributing to the complexity of lupus heritability. Copyright © 2012 by the American College of Rheumatology.

Biochemical and biophysical investigations of the interaction between human glucokinase and pro-apoptotic BAD.

PubMed

Rexford, Alix; Zorio, Diego A R; Miller, Brian G

2017-01-01

The glycolytic enzyme glucokinase (GCK) and the pro-apoptotic protein BAD reportedly reside within a five-membered complex that localizes to the mitochondria of mammalian hepatocytes and pancreatic β-cells. Photochemical crosslinking studies using a synthetic analog of BAD's BH3 domain and in vitro transcription/translation experiments support a direct interaction between BAD and GCK. To investigate the biochemical and biophysical consequences of the BAD:GCK interaction, we developed a method for the production of recombinant human BAD. Consistent with published reports, recombinant BAD displays high affinity for Bcl-xL (KD = 7 nM), and phosphorylation of BAD at S118, within the BH3 domain, abolishes this interaction. Unexpectedly, we do not detect association of recombinant, full-length BAD with recombinant human pancreatic GCK over a range of protein concentrations using various biochemical methods including size-exclusion chromatography, chemical cross-linking, analytical ultracentrifugation, and isothermal titration calorimetry. Furthermore, fluorescence polarization assays and isothermal titration calorimetry detect no direct interaction between GCK and BAD BH3 peptides. Kinetic characterization of GCK in the presence of high concentrations of recombinant BAD show modest (<15%) increases in GCK activity, observable only at glucose concentrations well below the K0.5 value. GCK activity is unaffected by BAD BH3 peptides. These results raise questions as to the mechanism of action of stapled peptide analogs modeled after the BAD BH3 domain, which reportedly enhance the Vmax value of GCK and stimulate insulin release in BAD-deficient islets. Based on our results, we postulate that the BAD:GCK interaction, and any resultant regulatory effect(s) upon GCK activity, requires the participation of additional members of the mitochondrial complex.

Detection of molecular interactions

DOEpatents

Groves, John T [Berkeley, CA; Baksh, Michael M [Fremont, CA; Jaros, Michal [Brno, CH

2012-02-14

A method and assay are described for measuring the interaction between a ligand and an analyte. The assay can include a suspension of colloidal particles that are associated with a ligand of interest. The colloidal particles are maintained in the suspension at or near a phase transition state from a condensed phase to a dispersed phase. An analyte to be tested is then added to the suspension. If the analyte binds to the ligand, a phase change occurs to indicate that the binding was successful.

Determining rotational dynamics of the guanidino group of arginine side chains in proteins by carbon-detected NMR† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7cc04821a

PubMed Central

Gerecht, Karola; Figueiredo, Angelo Miguel

2017-01-01

Arginine residues are imperative for many active sites and protein-interaction interfaces. A new NMR-based method is presented to determine the rotational dynamics around the Nε–Cζ bond of arginine side chains. An application to a 19 kDa protein shows that the strengths of interactions involving arginine side chains can be characterised. PMID:28840203

Odor detection of mixtures of homologous carboxylic acids and coffee aroma compounds by humans.

PubMed

Miyazawa, Toshio; Gallagher, Michele; Preti, George; Wise, Paul M

2009-11-11

Mixture summation among homologous carboxylic acids, that is, the relationship between detection probabilities for mixtures and detection probabilities for their unmixed components, varies with similarity in carbon-chain length. The current study examined detection of acetic, butyric, hexanoic, and octanoic acids mixed with three other model odorants that differ greatly from the acids in both structure and odor character, namely, 2-hydroxy-3-methylcyclopent-2-en-1-one, furan-2-ylmethanethiol, and (3-methyl-3-sulfanylbutyl) acetate. Psychometric functions were measured for both single compounds and binary mixtures (2 of 5, forced-choice method). An air dilution olfactometer delivered stimuli, with vapor-phase calibration using gas chromatography-mass spectrometry. Across the three odorants that differed from the acids, acetic and butyric acid showed approximately additive (or perhaps even supra-additive) summation at low perithreshold concentrations, but subadditive interactions at high perithreshold concentrations. In contrast, the medium-chain acids showed subadditive interactions across a wide range of concentrations. Thus, carbon-chain length appears to influence not only summation with other carboxylic acids but also summation with at least some unrelated compounds.

Femtomolar detection of single mismatches by discriminant analysis of DNA hybridization events using gold nanoparticles.

PubMed

Ma, Xingyi; Sim, Sang Jun

2013-03-21

Even though DNA-based nanosensors have been demonstrated for quantitative detection of analytes and diseases, hybridization events have never been numerically investigated for further understanding of DNA mediated interactions. Here, we developed a nanoscale platform with well-designed capture and detection gold nanoprobes to precisely evaluate the hybridization events. The capture gold nanoprobes were mono-laid on glass and the detection probes were fabricated via a novel competitive conjugation method. The two kinds of probes combined in a suitable orientation following the hybridization with the target. We found that hybridization efficiency was markedly dependent on electrostatic interactions between DNA strands, which can be tailored by adjusting the salt concentration of the incubation solution. Due to the much lower stability of the double helix formed by mismatches, the hybridization efficiencies of single mismatched (MMT) and perfectly matched DNA (PMT) were different. Therefore, we obtained an optimized salt concentration that allowed for discrimination of MMT from PMT without stringent control of temperature or pH. The results indicated this to be an ultrasensitive and precise nanosensor for the diagnosis of genetic diseases.

Characterization of single α-tracks by photoresist detection and AFM analysis-focus on biomedical science and technology

NASA Astrophysics Data System (ADS)

Falzone, Nadia; Myhra, Sverre; Chakalova, Radka; Hill, Mark A.; Thomson, James; Vallis, Katherine A.

2013-11-01

The interactions between energetic ions and biological and/or organic target materials have recently attracted theoretical and experimental attention, due to their implications for detector and device technologies, and for therapeutic applications. Most of the attention has focused on detection of the primary ionization tracks, and their effects, while recoil target atom tracks remain largely unexplored. Detection of tracks by a negative tone photoresist (SU-8), followed by standard development, in combination with analysis by atomic force microscopy, shows that both primary and recoil tracks are revealed as conical spikes, and can be characterized at high spatial resolution. The methodology has the potential to provide detailed information about single impact events, which may lead to more effective and informative detector technologies and advanced therapeutic procedures. In comparison with current characterization methods the advantageous features include: greater spatial resolution by an order of magnitude (20 nm) detection of single primary and associated recoil tracks; increased range of fluence (to 2.5 × 109 cm-2) sensitivity to impacts at grazing angle incidence; and better definition of the lateral interaction volume in target materials.

Fluorescence correlation spectroscopy as a method for assessment of interactions between phage displaying antibodies and soluble antigen

PubMed Central

Lagerkvist, Ann Catrin; Földes-Papp, Zeno; Persson, Mats A.A.; Rigler, Rudolf

2001-01-01

Phage display is widely used for expression of combinatorial libraries, not least for protein engineering purposes. Precise selection at the single molecule level will provide an improved tool for generating proteins with complex and distinct properties from large molecular libraries. To establish such an improved selection system, we here report the detection of specific interactions between phage with displayed antibody fragments and fluorescently labeled soluble antigen based on Fluorescence Correlation Spectroscopy (FCS). Our novel strategy comprises the use of two separate fluorochromes for detection of the phage–antigen complex, either with labeled antiphage antibody or using a labeled antigen. As a model system, we studied a human monoclonal antibody to the hepatitis-C virus (HCV) envelope protein E2 and its cognate antigen (rE2 or rE1/E2). We could thus assess the specific interactions and determine the fraction of specific versus background phage (26% specific phage). Aggregation of these particular antigens made it difficult to reliably utilize the full potential of cross-correlation studies using the two labels simultaneously. However, with true monomeric proteins, this will certainly be possible, offering a great advantage in a safer and highly specific detection system. PMID:11468349

A Colorimetric Microplate Assay for DNA-Binding Activity of His-Tagged MutS Protein.

PubMed

Banasik, Michał; Sachadyn, Paweł

2016-09-01

A simple microplate method was designed for rapid testing DNA-binding activity of proteins. The principle of the assay involves binding of tested DNA by his-tagged protein immobilized on a nickel-coated ELISA plate, following colorimetric detection of biotinylated DNA with avidin conjugated to horseradish peroxidase. The method was used to compare DNA mismatch binding activities of MutS proteins from three bacterial species. The assay required relatively low amounts of tested protein (approximately 0.5-10 pmol) and DNA (0.1-10 pmol) and a relatively short time of analysis (up to 60 min). The method is very simple to apply and convenient to test different buffer conditions of DNA-protein binding. Sensitive colorimetric detection enables naked eye observations and quantitation with an ELISA reader. The performance of the assay, which we believe is a distinguishing trait of the method, is based on two strong and specific molecular interactions: binding of a his-tagged protein to a nickel-coated microplate and binding of biotinylated DNA to avidin. In the reported experiments, the solution was used to optimize the conditions for DNA mismatch binding by MutS protein; however, the approach could be implemented to test nucleic acids interactions with any protein of interest.

Assessing compatibility of direct detection data: halo-independent global likelihood analyses

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

Gelmini, Graciela B.; Huh, Ji-Haeng; Witte, Samuel J.

2016-10-18

We present two different halo-independent methods to assess the compatibility of several direct dark matter detection data sets for a given dark matter model using a global likelihood consisting of at least one extended likelihood and an arbitrary number of Gaussian or Poisson likelihoods. In the first method we find the global best fit halo function (we prove that it is a unique piecewise constant function with a number of down steps smaller than or equal to a maximum number that we compute) and construct a two-sided pointwise confidence band at any desired confidence level, which can then be comparedmore » with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a “constrained parameter goodness-of-fit” test statistic, whose p-value we then use to define a “plausibility region” (e.g. where p≥10%). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. p<10%). We illustrate these methods by applying them to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic spin-independent isospin-conserving interactions or exothermic spin-independent isospin-violating interactions.« less

Label-Free Fluorescence Assay of S1 Nuclease and Hydroxyl Radicals Based on Water-Soluble Conjugated Polymers and WS₂ Nanosheets.

PubMed

Li, Junting; Zhao, Qi; Tang, Yanli

2016-06-13

We developed a new method for detecting S1 nuclease and hydroxyl radicals based on the use of water-soluble conjugated poly[9,9-bis(6,6-(N,N,N-trimethylammonium)-fluorene)-2,7-ylenevinylene-co-alt-2,5-dicyano-1,4-phenylene)] (PFVCN) and tungsten disulfide (WS₂) nanosheets. Cationic PFVCN is used as a signal reporter, and single-layer WS₂ is used as a quencher with a negatively charged surface. The ssDNA forms complexes with PFVCN due to much stronger electrostatic interactions between cationic PFVCN and anionic ssDNA, whereas PFVCN emits yellow fluorescence. When ssDNA is hydrolyzed by S1 nuclease or hydroxyl radicals into small fragments, the interactions between the fragmented DNA and PFVCN become weaker, resulting in PFVCN being adsorbed on the surface of WS₂ and the fluorescence being quenched through fluorescence resonance energy transfer. The new method based on PFVCN and WS₂ can sense S1 nuclease with a low detection limit of 5 × 10(-6) U/mL. Additionally, this method is cost-effective by using affordable WS₂ as an energy acceptor without the need for dye-labeled ssDNA. Furthermore, the method provides a new platform for the nuclease assay and reactive oxygen species, and provides promising applications for drug screening.

Laser-induced photo emission detection: data acquisition based on light intensity counting

NASA Astrophysics Data System (ADS)

Yulianto, N.; Yudasari, N.; Putri, K. Y.

2017-04-01

Laser Induced Breakdown Detection (LIBD) is one of the quantification techniques for colloids. There are two ways of detection in LIBD: optical detection and acoustic detection. LIBD is based on the detection of plasma emission due to the interaction between particle and laser beam. In this research, the changing of light intensity during plasma formations was detected by a photodiode sensor. A photo emission data acquisition system was built to collect and transform them into digital counts. The real-time system used data acquisition device National Instrument DAQ 6009 and LABVIEW software. The system has been tested on distilled water and tap water samples. The result showed 99.8% accuracy by using counting technique in comparison to the acoustic detection with sample rate of 10 Hz, thus the acquisition system can be applied as an alternative method to the existing LIBD acquisition system.

A convenient method for determination of quizalofop-p-ethyl based on the fluorescence quenching of eosin Y in the presence of Pd(II)

NASA Astrophysics Data System (ADS)

Wu, Huan; Zhao, Yanmei; Tan, Xuanping; Zeng, Xiaoqing; Guo, Yuan; Yang, Jidong

2017-03-01

A convenient fluorescence quenching method for determination of Quizalofop-p-ethyl(Qpe) was proposed in this paper. Eosin Y(EY) is a red dye with strong green fluorescence (λex/λem = 519/540 nm). The interaction between EY, Pd(II) and Qpe was investigated by fluorescence spectroscopy, resonance Rayleigh scattering(RRS) and UV-Vis absorption. Based on changes in spectrum, Pd(II) associated with Qpe giving a positively charged chelate firstly, then reacted with EY through electrostatic and hydrophobic interaction formed ternary chelate could be demonstrated. Under optimum conditions, the fluorescence intensity of EY could be quenched by Qpe in the presence of Pd(II) and the RRS intensity had a remarkable enhancement, which was directly proportional to the Qpe concentration within a certain concentration range, respectively. Based on the fluorescence quenching of EY-Pd(II) system by Qpe, a novel, convenient and specific method for Qpe determination was developed. To our knowledge, this is the first fluorescence method for determination of Qpe was reported. The detection limit for Qpe was 20.3 ng/mL and the quantitative determination range was 0.04-1.0 μg/mL. The method was highly sensitive and had larger detection range compared to other methods. The influence of coexisting substances was investigated with good anti-interference ability. The new analytical method has been applied to determine of Qpe in real samples with satisfactory results.

[Determination of hydroxyproline in liver tissue by hydrophilic interaction chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry].

PubMed

Liu, Wei; Qi, Shenglan; Xu, Ying; Xiao, Zhun; Fu, Yadong; Chen, Jiamei; Yang, Tao; Liu, Ping

2017-12-08

A method for the determination of hydroxyproline (Hyp) in liver tissue of mice by hydrophilic interaction chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry (HILIC-HRMS) was developed. The liver tissue samples of normal mice and liver fibrosis mice induced by carbon tetrachloride were hydrolyzed by concentrated hydrochloric acid. After filtrated and diluted by solution, the diluent was separated on an Hypersil GOLD HILIC column (100 mm×2.1 mm, 3 μm). Water-acetonitrile (28:72, v/v)were used as the mobile phases with isocratic elution. Finally, the target analytes were detected in positive model by HRMS equipped with an electrospray ionization source. The linear range of hydroxyproline was from 0.78 to 100.00 μg/L with the correlation coefficient ( R 2 ) of 0.9983. The limit of quantification was 0.78 μg/L. By detecting the spiked samples, the recoveries were in the range of 97.4%-100.9% with the relative standard deviations (RSDs) between 1.4% and 2.0%. In addition, comparison of the measurement results by this method and the chloramine T method was proceeded. It was found that the linear correlation between the two methods was very good, and the Pearson correlation coefficient was 0.927. And this method had simpler operation procedure and higher accuracy than chloramine T method. This method can be used for the quick determination of hydroxyproline in liver tissue samples.

High throughput protein production screening

DOEpatents

Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

2009-09-08

Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

An easy and fast adenosine 5'-diphosphate quantification procedure based on hydrophilic interaction liquid chromatography-high resolution tandem mass spectrometry for determination of the in vitro adenosine 5'-triphosphatase activity of the human breast cancer resistance protein ABCG2.

PubMed

Wagmann, Lea; Maurer, Hans H; Meyer, Markus R

2017-10-27

Interactions with the human breast cancer resistance protein (hBCRP) significantly influence the pharmacokinetic properties of a drug and can even lead to drug-drug interactions. As efflux pump from the ABC superfamily, hBCRP utilized energy gained by adenosine 5'-triphosphate (ATP) hydrolysis for the transmembrane movement of its substrates, while adenosine 5'-diphosphate (ADP) and inorganic phosphate were released. The ADP liberation can be used to detect interactions with the hBCRP ATPase. An ADP quantification method based on hydrophilic interaction liquid chromatography (HILIC) coupled to high resolution tandem mass spectrometry (HR-MS/MS) was developed and successfully validated in accordance to the criteria of the guideline on bioanalytical method validation by the European Medicines Agency. ATP and adenosine 5'-monophosphate were qualitatively included to prevent interferences. Furthermore, a setup consisting of six sample sets was evolved that allowed detection of hBCRP substrate or inhibitor properties of the test compound. The hBCRP substrate sulfasalazine and the hBCRP inhibitor orthovanadate were used as controls. To prove the applicability of the procedure, the effect of amprenavir, indinavir, nelfinavir, ritonavir, and saquinavir on the hBCRP ATPase activity was tested. Nelfinavir, ritonavir, and saquinavir were identified as hBCRP ATPase inhibitors and none of the five HIV protease inhibitors turned out to be an hBCRP substrate. These findings were in line with a pervious publication. Copyright © 2017 Elsevier B.V. All rights reserved.

An analysis of the gene interaction networks identifying the role of PARP1 in metastasis of non-small cell lung cancer.

PubMed

Chen, Kai; Li, Yajie; Xu, Hui; Zhang, Chunfeng; Li, Zhiqiang; Wang, Wei; Wang, Baofeng

2017-10-20

Though there were many researches about the effects of cancer cells on non-small cell lung cancer (NSCLC) currently, it has been rarely reported completed oncogene and its mechanism in tumors by far. Here, we used biological methods with known oncogene of NSCLC to find new oncogene and explore its functionary mechanism in NSCLC. The study firstly built NSCLC genetic interaction network based on bioinformatics methods and then combined shortest path algorithm with significance test to confirmed core genes that were closely involved with given genes; real-time qPCR was conducted to detect expression levels between patients with NSCLC and normal people; additionally, detection of PARP1's role in migration and invasion was performed by trans-well assays and wound-healing. Through gene interaction network, it was found that, core genes like PARP1, EGFR and ALK had a direct interaction. TCGA database showed that PARP1 presented strong expression in NSCLC and the expression level of metastatic NSCLC was significantly higher than that of non-metastatic NSCLC. Cell migration of NSCLC in accordance to the scratch test was suppressed by PARP1 silence but stimulated noticeably by PARP1 overexpression. According to Kaplan-meier survival curve, the higher PARP1 expression, the poorer patient survival rate and prognosis. Thus, PARP1 expression had a negative correction with patient survival rate and prognosis. New oncogene PARP1 was found from known NSCLC oncogene in terms of gene interaction network, demonstrating PARP1's impact on NSCLC cell migration.

A Modularity-Based Method Reveals Mixed Modules from Chemical-Gene Heterogeneous Network

PubMed Central

Song, Jianglong; Tang, Shihuan; Liu, Xi; Gao, Yibo; Yang, Hongjun; Lu, Peng

2015-01-01

For a multicomponent therapy, molecular network is essential to uncover its specific mode of action from a holistic perspective. The molecular system of a Traditional Chinese Medicine (TCM) formula can be represented by a 2-class heterogeneous network (2-HN), which typically includes chemical similarities, chemical-target interactions and gene interactions. An important premise of uncovering the molecular mechanism is to identify mixed modules from complex chemical-gene heterogeneous network of a TCM formula. We thus proposed a novel method (MixMod) based on mixed modularity to detect accurate mixed modules from 2-HNs. At first, we compared MixMod with Clauset-Newman-Moore algorithm (CNM), Markov Cluster algorithm (MCL), Infomap and Louvain on benchmark 2-HNs with known module structure. Results showed that MixMod was superior to other methods when 2-HNs had promiscuous module structure. Then these methods were tested on a real drug-target network, in which 88 disease clusters were regarded as real modules. MixMod could identify the most accurate mixed modules from the drug-target 2-HN (normalized mutual information 0.62 and classification accuracy 0.4524). In the end, MixMod was applied to the 2-HN of Buchang naoxintong capsule (BNC) and detected 49 mixed modules. By using enrichment analysis, we investigated five mixed modules that contained primary constituents of BNC intestinal absorption liquid. As a matter of fact, the findings of in vitro experiments using BNC intestinal absorption liquid were found to highly accord with previous analysis. Therefore, MixMod is an effective method to detect accurate mixed modules from chemical-gene heterogeneous networks and further uncover the molecular mechanism of multicomponent therapies, especially TCM formulae. PMID:25927435

Glutathione-capped CdTe nanocrystals as probe for the determination of fenbendazole

NASA Astrophysics Data System (ADS)

Li, Qin; Tan, Xuanping; Li, Jin; Pan, Li; Liu, Xiaorong

2015-04-01

Water-soluble glutathione (GSH)-capped CdTe quantum dots (QDs) were synthesized. In pH 7.1 PBS buffer solution, the interaction between GSH-capped CdTe QDs and fenbendazole (FBZ) was investigated by spectroscopic methods, including fluorescence spectroscopy, ultraviolet-visible absorption spectroscopy, and resonance Rayleigh scattering (RRS) spectroscopy. In GSH-capped CdTe QDs solution, the addition of FBZ results in the fluorescence quenching and RRS enhancement of GSH-capped CdTe QDs. And the quenching intensity (enhanced RRS intensity) was proportional to the concentration of FBZ in a certain range. Investigation of the interaction mechanism, proved that the fluorescence quenching and RRS enhancement of GSH-capped CdTe QDs by FBZ is the result of electrostatic attraction. Based on the quenching of fluorescence (enhancement of RRS) of GSH-capped CdTe QDs by FBZ, a novel, simple, rapid and specific method for FBZ determination was proposed. The detection limit for FBZ was 42 ng mL-1 (3.4 ng mL-1) and the quantitative determination range was 0-2.8 μg mL-1 with a correlation of 0.9985 (0.9979). The method has been applied to detect FBZ in real simples and with satisfactory results.

Dark matter candidates and methods for detecting them

NASA Technical Reports Server (NTRS)

Raffelt, G. G.

1992-01-01

A number of experiments employing Ge and Si ionization detectors have excluded large regions in the plane of masses and scattering cross-sections for weakly-interacting dark matter (DM) candidates. It is judged that, before a realistic detection experiment for supersymmetric DM candidates can be conducted, significant development efforts will have to be completed for suitable cryogenic or ionization detectors. Pilot experiments have demonstrated the feasibility of axion searches with microwave cavities, but these are at least two orders of magnitude too low in sensitivity.

Physics, Astrophysics and Cosmology with Gravitational Waves.

PubMed

Sathyaprakash, B S; Schutz, Bernard F

2009-01-01

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.

Positioning true coincidences that undergo inter-and intra-crystal scatter for a sub-mm resolution cadmium zinc telluride-based PET system

NASA Astrophysics Data System (ADS)

Abbaszadeh, Shiva; Chinn, Garry; Levin, Craig S.

2018-01-01

The kinematics of Compton scatter can be used to estimate the interaction sequence of inter-crystal scatter interactions in 3D position-sensitive cadmium zinc telluride (CZT) detectors. However, in the case of intra-crystal scatter in a ‘cross-strip’ CZT detector slab, multiple anode and cathode strips may be triggered, creating position ambiguity due to uncertainty in possible combinations of anode-cathode pairings. As a consequence, methods such as energy-weighted centroid are not applicable to position the interactions. In practice, since the event position is uncertain, these intra-crystal scatters events are discarded. In this work, we studied using Compton kinematics and a ‘direction difference angle’ to provide a method to correctly identify the anode-cathode pair corresponding to the first interaction position in an intra-crystal scatter event. GATE simulation studies of a NEMA NU4 image quality phantom in a small animal positron emission tomography under development composed of 192, 40~mm×40~mm×5 mm CZT crystals shows that 47% of total numbers of multiple-interaction photon events (MIPEs) are intra-crystal scatter with a 100 keV lower energy threshold per interaction. The sensitivity of the system increases from 0.6 to 4.10 (using 10 keV as system lower energy threshold) by including rather than discarding inter- and intra-crystal scatter. The contrast-to-noise ratio (CNR) also increases from 5.81+/-0.3 to 12.53+/-0.37 . It was shown that a higher energy threshold limits the capability of the system to detect MIPEs and reduces CNR. Results indicate a sensitivity increase (4.1 to 5.88) when raising the lower energy threshold (10 keV to 100 keV) for the case of only two-interaction events. In order to detect MIPEs accurately, a low noise system capable of a low energy threshold (10 keV) per interaction is desired.

Analyte sensing mediated by adapter/carrier molecules

DOEpatents

Bayley, Hagan; Braha, Orit; Gu, LiQun

2002-07-30

This invention relates to an improved method and system for sensing of one or more analytes. A host molecule, which serves as an adapter/carrier, is used to facilitate interaction between the analyte and the sensor element. A detectable signal is produced reflecting the identity and concentration of analyte present.

Mimicking multivalent protein-carbohydrate interactions for monitoring the glucosamine level in biological fluids and pharmaceutical tablets.

PubMed

Dey, Nilanjan; Bhattacharya, Santanu

2017-05-11

An easily synthesizable probe has been employed for dual mode sensing of glucosamine in pure water. The method was also applied for glucosamine estimation in blood serum samples and pharmaceutical tablets. Further, selective detection of glucosamine was also achieved using portable color strips.

Yoink: An interaction-based partitioning API.

PubMed

Zheng, Min; Waller, Mark P

2018-05-15

Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Intraoperative magnetic resonance imaging to update interactive navigation in neurosurgery: method and preliminary experience.

PubMed

Wirtz, C R; Bonsanto, M M; Knauth, M; Tronnier, V M; Albert, F K; Staubert, A; Kunze, S

1997-01-01

We report on the first successful intraoperative update of interactive image guidance based on an intraoperatively acquired magnetic resonance imaging (MRI) date set. To date, intraoperative imaging methods such as ultrasound, computerized tomography (CT), or MRI have not been successfully used to update interactive navigation. We developed a method of imaging patients intraoperatively with the surgical field exposed in an MRI scanner (Magnetom Open; Siemens Corp., Erlangen, Germany). In 12 patients, intraoperatively acquired 3D data sets were used for successful recalibration of neuronavigation, accounting for any anatomical changes caused by surgical manipulations. The MKM Microscope (Zeiss Corp., Oberkochen, Germany) was used as navigational system. With implantable fiducial markers, an accuracy of 0.84 +/- 0.4 mm for intraoperative reregistration was achieved. Residual tumor detected on MRI was consequently resected using navigation with the intraoperative data. No adverse effects were observed from intraoperative imaging or the use of navigation with intraoperative images, demonstrating the feasibility of recalibrating navigation with intraoperative MRI.

A High-Throughput Screening Method for Small-Molecule Inhibitors of the Aberrant Mutant SOD1 and Dynein Complex Interaction

PubMed Central

Tang, Xiaohu; Seyb, Kathleen I.; Huang, Mickey; Schuman, Eli R.; Shi, Ping; Zhu, Haining; Glicksman, Marcie A.

2013-01-01

Aberrant protein-protein interactions are attractive drug targets in a variety of neurodegenerative diseases due to the common pathology of accumulation of protein aggregates. In amyotrophic lateral sclerosis, mutations in SOD1 cause the formation of aggregates and inclusions that may sequester other proteins and disrupt cellular processes. It has been demonstrated that mutant SOD1, but not wild-type SOD1, interacts with the axonal transport motor dynein and that this interaction contributes to motor neuron cell death, suggesting that disrupting this interaction may be a potential therapeutic target. However, it can be challenging to configure a high-throughput screening (HTS)–compatible assay to detect inhibitors of a protein-protein interaction. Here we describe the development and challenges of an HTS for small-molecule inhibitors of the mutant SOD1-dynein interaction. We demonstrate that the interaction can be formed by coexpressing the A4V mutant SOD1 and dynein intermediate complex in cells and that this interaction can be disrupted by compounds added to the cell lysates. Finally, we show that some of the compounds identified from a pilot screen to inhibit the protein-protein interaction with this method specifically disrupt the interaction between the dynein complex and mtSOD1 but not the dynein complex itself when applied to live cells. PMID:22140121

Skew information in the XY model with staggered Dzyaloshinskii-Moriya interaction

NASA Astrophysics Data System (ADS)

Qiu, Liang; Quan, Dongxiao; Pan, Fei; Liu, Zhi

2017-06-01

We study the performance of the lower bound of skew information in the vicinity of transition point for the anisotropic spin-1/2 XY chain with staggered Dzyaloshinskii-Moriya interaction by use of quantum renormalization-group method. For a fixed value of the Dzyaloshinskii-Moriya interaction, there are two saturated values for the lower bound of skew information corresponding to the spin-fluid and Néel phases, respectively. The scaling exponent of the lower bound of skew information closely relates to the correlation length of the model and the Dzyaloshinskii-Moriya interaction shifts the factorization point. Our results show that the lower bound of skew information can be a good candidate to detect the critical point of XY spin chain with staggered Dzyaloshinskii-Moriya interaction.

Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

PubMed Central

Hasson, Uri; Frith, Chris D.

2016-01-01

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader–follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis PMID:27069044

Interactions of antibiotics and extracts of Helichrysum pedunculatum against bacteria implicated in wound infections.

PubMed

Aiyegoro, O A; Afolayan, A J; Okoh, A I

2010-03-01

The effect of combinations of the crude acetone and aqueous extracts of Helichrysum pedunculatum leaves and eight antibiotics was determined by means of checkerboard and time-kill methods. In the checkerboard method, synergy of 45.8% was observed, being independent of Gram reaction, with combinations in the aqueous extract yielding largely (18.8%) antagonistic interactions. The time-kill assay detected synergy (45.8%) that was also independent of Gram reaction with a potentiation of more than 3 orders of the bactericidal activity of the test antibiotics. The crude leaf extracts of H. pedunculatum could thus be considered to be potential source of a broad-spectrum antibiotic-resistance-modifying compounds.

Demonstration of protein-fragment complementation assay using purified firefly luciferase fragments

PubMed Central

2013-01-01

Background Human interactome is predicted to contain 150,000 to 300,000 protein-protein interactions, (PPIs). Protein-fragment complementation assay (PCA) is one of the most widely used methods to detect PPI, as well as Förster resonance energy transfer (FRET). To date, successful applications of firefly luciferase (Fluc)-based PCA have been reported in vivo, in cultured cells and in cell-free lysate, owing to its high sensitivity, high signal-to-background (S/B) ratio, and reversible response. Here we show the assay also works with purified proteins with unexpectedly rapid kinetics. Results Split Fluc fragments both fused with a rapamycin-dependently interacting protein pair were made and expressed in E. coli system, and purified to homogeneity. When the proteins were used for PCA to detect rapamycin-dependent PPI, they enabled a rapid detection (~1 s) of PPI with high S/B ratio. When Fn7-8 domains (7 nm in length) that was shown to abrogate GFP mutant-based FRET was inserted between split Fluc and FKBP12 as a rigid linker, it still showed some response, suggesting less limitation in interacting partner’s size. Finally, the stability of the probe was investigated. Preincubation of the probes at 37 degreeC up to 1 h showed marked decrease of the luminescent signal to 1.5%, showing the limited stability of this system. Conclusion Fluc PCA using purified components will enable a rapid and handy detection of PPIs with high S/B ratio, avoiding the effects of concomitant components. Although the system might not be suitable for large-scale screening due to its limited stability, it can detect an interaction over larger distance than by FRET. This would be the first demonstration of Fluc PCA in vitro, which has a distinct advantage over other PPI assays. Our system enables detection of direct PPIs without risk of perturbation by PPI mediators in the complex cellular milieu. PMID:23536995

In Vitro Interactions between Tacrolimus and Azoles against Candida albicans Determined by Different Methods▿

PubMed Central

Sun, Shujuan; Li, Yan; Guo, Qiongjie; Shi, Changwen; Yu, Jinlong; Ma, Lin

2008-01-01

Combination therapy could be of use for the treatment of fungal infections, especially those caused by drug-resistant fungi. However, the methods and approaches used for data generation and result interpretation need further optimizing. The fractional inhibitory concentration index (FICI) is the most commonly used method, but it has several drawbacks in characterizing antifungal drug interaction. Alternatively, some new methods can be used such as the ΔE model (difference between the predicted and measured fungal growth percentages) and the response surface approach, which uses the concentration-effect relationship over the whole concentration range instead of just the MIC. In the present study, in vitro interactions between tacrolimus (FK506) and three azoles—fluconazole (FLC), itraconazole (ITR), and voriconazole (VRC)-against Candida albicans were evaluated by the checkerboard microdilution method and time-killing test. The intensity of the interactions was determined by visual reading and the spectrophotometric method in a checkerboard assay, and the nature of the interactions was assessed by nonparametric models of FICI and ΔE. Colony counting and colorimetric viable detection methods (2,3-bis {2-methoxy-4-nitro-5-[(sulfenylamino) carbonyl]-2H-tetrazolium hydroxide} [XTT] reduction test) were used for evaluating the combination antifungal effects over time. Synergistic and indifferent effects were found for the combination of FK506 and azoles against azole-sensitive strains, while strong synergy was found against azole-resistant strains analyzed by FICI. The ΔE model gave more consistent results with FICI. The positive interactions were also confirmed by the time-killing test. Our findings suggest a potential role for combination therapy with calcineurin pathway inhibitors and azoles to augment activity against resistant C. albicans. PMID:18056277

Comparative Study of Three Methods for Affinity Measurements: Capillary Electrophoresis Coupled with UV Detection and Mass Spectrometry, and Direct Infusion Mass Spectrometry

NASA Astrophysics Data System (ADS)

Mironov, Gleb G.; Logie, Jennifer; Okhonin, Victor; Renaud, Justin B.; Mayer, Paul M.; Berezovski, Maxim V.

2012-07-01

We present affinity capillary electrophoresis and mass spectrometry (ACE-MS) as a comprehensive separation technique for label-free solution-based affinity analysis. The application of ACE-MS for measuring affinity constants between eight small molecule drugs [ibuprofen, s-flurbiprofen, diclofenac, phenylbutazone, naproxen, folic acid, resveratrol, and 4,4'-(propane-1,3-diyl) dibenzoic acid] and β-cyclodextrin is described. We couple on-line ACE with MS to combine the separation and kinetic capability of ACE together with the molecular weight and structural elucidation of MS in one system. To understand the full potential of ACE-MS, we compare it with two other methods: Direct infusion mass spectrometry (DIMS) and ACE with UV detection (ACE-UV). After the evaluation, DIMS provides less reliable equilibrium dissociation constants than separation-based ACE-UV and ACE-MS, and cannot be used solely for the study of noncovalent interactions. ACE-MS determines apparent dissociation constants for all reacting small molecules in a mixture, even in cases when drugs overlap with each other during separation. The ability of ACE-MS to interact, separate, and rapidly scan through m/z can facilitate the simultaneous affinity analysis of multiple interacting pairs, potentially leading to the high-throughput screening of drug candidates.

Spatio-temporal imaging of EGF-induced activation of protein kinase A by FRET in living cells

NASA Astrophysics Data System (ADS)

Wang, Jin Jun; Chen, Xiao-Chuan; Xing, Da

2004-07-01

Intracellular molecular interaction is important for the study of cell physiology, yet current relevant methods require fixation or microinjection and lack temporal or spatial resolution. We introduced a new method -- fluorescence resonance energy transfer (FRET) to detect molecular interaction in living cells. On the basis of FRET principle, A-kinase activity reporter (AKAR) protein was designed to consist of the fusions of cyan fluorescent protein (CFP), a phosphoamino acid binding domain, a consensus substrate for protein kinase-A (PKA), and yellow fluorescent protein (YFP). In this study, the designed pAKAR plasmid was used to transfect a human lung cancer cell line (ASTC-a-1). When the AKAR-transfected cells were treated by forskolin (Fsk), we were able to observe the efficient transfer of energy from excited CFP to YFP within the AKAR molecule by fluorescence microcopy, whereas no FRET was detected in the transfected cells without the treatment of Fsk. When the cells were treated by Epidermal growth factor (EGF), the change of FRET was observed at different subcellular locations, reflecting PKA activation inside the cells upon EGF stimulation. The successful design of a fluorescence reporter of PKA activation and its application demonstrated the superiority of this technology in the research of intracellular protein-protein interaction.

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

PubMed Central

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

2017-01-01

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

Hydrogen Sensors Using Nitride-Based Semiconductor Diodes: The Role of Metal/Semiconductor Interfaces

PubMed Central

Irokawa, Yoshihiro

2011-01-01

In this paper, I review my recent results in investigating hydrogen sensors using nitride-based semiconductor diodes, focusing on the interaction mechanism of hydrogen with the devices. Firstly, effects of interfacial modification in the devices on hydrogen detection sensitivity are discussed. Surface defects of GaN under Schottky electrodes do not play a critical role in hydrogen sensing characteristics. However, dielectric layers inserted in metal/semiconductor interfaces are found to cause dramatic changes in hydrogen sensing performance, implying that chemical selectivity to hydrogen could be realized. The capacitance-voltage (C–V) characteristics reveal that the work function change in the Schottky metal is not responsible mechanism for hydrogen sensitivity. The interface between the metal and the semiconductor plays a critical role in the interaction of hydrogen with semiconductor devises. Secondly, low-frequency C–V characterization is employed to investigate the interaction mechanism of hydrogen with diodes. As a result, it is suggested that the formation of a metal/semiconductor interfacial polarization could be attributed to hydrogen-related dipoles. In addition, using low-frequency C–V characterization leads to clear detection of 100 ppm hydrogen even at room temperature where it is hard to detect hydrogen by using conventional current-voltage (I–V) characterization, suggesting that low-frequency C–V method would be effective in detecting very low hydrogen concentrations. PMID:22346597

Orientation of airborne laser scanning point clouds with multi-view, multi-scale image blocks.

PubMed

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters.

Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks

PubMed Central

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569

Detection of nitrite based on fluorescent carbon dots by the hydrothermal method with folic acid

NASA Astrophysics Data System (ADS)

Lin, Haitao; Ding, Liyun; Zhang, Bingyu; Huang, Jun

2018-05-01

A fluorescent carbon dots probe for the detection of aqueous nitrite was fabricated by a one-pot hydrothermal method, and the transmission electron microscope, X-ray diffractometer, UV-Vis absorption spectrometer and fluorescence spectrophotometer were used to study the property of carbon dots. The fluorescent property of carbon dots influenced by the concentration of aqueous nitrite was studied. The interaction between the electron-donating functional groups and the electron-accepting nitrous acid could account for the quenching effect on carbon dots by adding aqueous nitrite. The products of the hydrolysis of aqueous nitrite performed a stronger quenching effect at lower pH. The relationship between the relative fluorescence intensity of carbon dots and the concentration of nitrite was described by the Stern-Volmer equation (I0/I - 1 = 0.046[Q]) with a fine linearity (R2 = 0.99). The carbon dots-based probe provides a convenient method for the detection of nitrite concentration.

iADRs: towards online adverse drug reaction analysis.

PubMed

Lin, Wen-Yang; Li, He-Yi; Du, Jhih-Wei; Feng, Wen-Yu; Lo, Chiao-Feng; Soo, Von-Wun

2012-12-01

Adverse Drug Reaction (ADR) is one of the most important issues in the assessment of drug safety. In fact, many adverse drug reactions are not discovered during limited pre-marketing clinical trials; instead, they are only observed after long term post-marketing surveillance of drug usage. In light of this, the detection of adverse drug reactions, as early as possible, is an important topic of research for the pharmaceutical industry. Recently, large numbers of adverse events and the development of data mining technology have motivated the development of statistical and data mining methods for the detection of ADRs. These stand-alone methods, with no integration into knowledge discovery systems, are tedious and inconvenient for users and the processes for exploration are time-consuming. This paper proposes an interactive system platform for the detection of ADRs. By integrating an ADR data warehouse and innovative data mining techniques, the proposed system not only supports OLAP style multidimensional analysis of ADRs, but also allows the interactive discovery of associations between drugs and symptoms, called a drug-ADR association rule, which can be further developed using other factors of interest to the user, such as demographic information. The experiments indicate that interesting and valuable drug-ADR association rules can be efficiently mined.

Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson's disease.

PubMed

Iakovakis, Dimitrios; Hadjidimitriou, Stelios; Charisis, Vasileios; Bostantzopoulou, Sevasti; Katsarou, Zoe; Hadjileontiadis, Leontios J

2018-05-16

Parkinson's disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients' quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject's status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC = 0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant features plausibly correlating with clinical scores of relevant PD motor symptoms. These findings suggest an improvement over similar approaches, thereby constituting a further step towards unobtrusive early PD detection from routine activities.

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

PubMed

Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

Similarity-based modeling in large-scale prediction of drug-drug interactions.

PubMed

Vilar, Santiago; Uriarte, Eugenio; Santana, Lourdes; Lorberbaum, Tal; Hripcsak, George; Friedman, Carol; Tatonetti, Nicholas P

2014-09-01

Drug-drug interactions (DDIs) are a major cause of adverse drug effects and a public health concern, as they increase hospital care expenses and reduce patients' quality of life. DDI detection is, therefore, an important objective in patient safety, one whose pursuit affects drug development and pharmacovigilance. In this article, we describe a protocol applicable on a large scale to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in established DDIs. The method integrates a reference standard database of known DDIs with drug similarity information extracted from different sources, such as 2D and 3D molecular structure, interaction profile, target and side-effect similarities. The method is interpretable in that it generates drug interaction candidates that are traceable to pharmacological or clinical effects. We describe a protocol with applications in patient safety and preclinical toxicity screening. The time frame to implement this protocol is 5-7 h, with additional time potentially necessary, depending on the complexity of the reference standard DDI database and the similarity measures implemented.

Pulse Double-Resonance EPR Techniques for the Study of Metallobiomolecules.

PubMed

Cox, Nicholas; Nalepa, Anna; Pandelia, Maria-Eirini; Lubitz, Wolfgang; Savitsky, Anton

2015-01-01

Electron paramagnetic resonance (EPR) spectroscopy exploits an intrinsic property of matter, namely the electron spin and its related magnetic moment. This can be oriented in a magnetic field and thus, in the classical limit, acts like a little bar magnet. Its moment will align either parallel or antiparallel to the field, giving rise to different energies (termed Zeeman splitting). Transitions between these two quantized states can be driven by incident microwave frequency radiation, analogous to NMR experiments, where radiofrequency radiation is used. However, the electron Zeeman interaction alone provides only limited information. Instead, much of the usefulness of EPR is derived from the fact that the electron spin also interacts with its local magnetic environment and thus can be used to probe structure via detection of nearby spins, e.g., NMR-active magnetic nuclei and/or other electron spin(s). The latter is exploited in spin labeling techniques, an exciting new area in the development of noncrystallographic protein structure determination. Although these interactions are often smaller than the linewidth of the EPR experiment, sophisticated pulse EPR methods allow their detection. A number of such techniques are well established today and can be broadly described as double-resonance methods, in which the electron spin is used as a reporter. Below we give a brief description of pulse EPR methods, particularly their implementation at higher magnetic fields, and how to best exploit them for studying metallobiomolecules. © 2015 Elsevier Inc. All rights reserved.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Multiple particle tracking in 3-D+t microscopy: method and application to the tracking of endocytosed quantum dots.

PubMed

Genovesio, Auguste; Liedl, Tim; Emiliani, Valentina; Parak, Wolfgang J; Coppey-Moisan, Maité; Olivo-Marin, Jean-Christophe

2006-05-01

We propose a method to detect and track multiple moving biological spot-like particles showing different kinds of dynamics in image sequences acquired through multidimensional fluorescence microscopy. It enables the extraction and analysis of information such as number, position, speed, movement, and diffusion phases of, e.g., endosomal particles. The method consists of several stages. After a detection stage performed by a three-dimensional (3-D) undecimated wavelet transform, we compute, for each detected spot, several predictions of its future state in the next frame. This is accomplished thanks to an interacting multiple model (IMM) algorithm which includes several models corresponding to different biologically realistic movement types. Tracks are constructed, thereafter, by a data association algorithm based on the maximization of the likelihood of each IMM. The last stage consists of updating the IMM filters in order to compute final estimations for the present image and to improve predictions for the next image. The performances of the method are validated on synthetic image data and used to characterize the 3-D movement of endocytic vesicles containing quantum dots.

Derivative spectrum chromatographic method for the determination of trimethoprim in honey samples using an on-line solid-phase extraction technique.

PubMed

Uchiyama, Kazuhisa; Kondo, Mari; Yokochi, Rika; Takeuchi, Yuri; Yamamoto, Atsushi; Inoue, Yoshinori

2011-07-01

A simple, selective and rapid analytical method for determination of trimethoprim (TMP) in honey samples was developed and validated. This method is based on a SPE technique followed by HPLC with photodiode array detection. After dilution and filtration, aliquots of 500 μL honey samples were directly injected to an on-line SPE HPLC system. TMP was extracted on an RP SPE column, and separated on a hydrophilic interaction chromatography column during HPLC analysis. At the first detection step, the noise level of the photodiode array data was reduced with two-dimensional equalizer filtering, and then the smoothed data were subjected to derivative spectrum chromatography. On the second-derivative chromatogram at 254 nm, the limit of detection and the limit of quantification of TMP in a honey sample were 5 and 10 ng/g, respectively. The proposed method showed high accuracy (60-103%) with adequate sensitivity for TMP monitoring in honey samples. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SPRi-based biosensing platforms for detection of specific DNA sequences using thiolate and dithiocarbamate assemblies

NASA Astrophysics Data System (ADS)

Drozd, Marcin; Pietrzak, Mariusz D.; Malinowska, Elżbieta

2018-05-01

The framework of presented study covers the development and examination of the analytical performance of surface plasmon resonance-based (SPR) DNA biosensors dedicated for a detection of model target oligonucleotide sequence. For this aim, various strategies of immobilization of DNA probes on gold transducers were tested. Besides the typical approaches: chemisorption of thiolated ssDNA (DNA-thiol) and physisorption of non-functionalized oligonucleotides, relatively new method based on chemisorption of dithiocarbamate-functionalized ssDNA (DNA-DTC) was applied for the first time for preparation of DNA-based SPR biosensor. The special emphasis was put on the correlation between the method of DNA immobilization and the composition of obtained receptor layer. The carried out studies focused on the examination of the capability of developed receptors layers to interact with both target DNA and DNA-functionalized AuNPs. It was found, that the detection limit of target DNA sequence (27 nb length) depends on the strategy of probe immobilization and backfilling method, and in the best case it amounted to 0,66 nM. Moreover, the application of ssDNA-functionalized gold nanoparticles (AuNPs) as plasmonic labels for secondary enhancement of SPR response is presented. The influence of spatial organization and surface density of a receptor layer on the ability to interact with DNA-functionalized AuNPs is discussed. Due to the best compatibility of receptors immobilized via DTC chemisorption: 1.47 ± 0.4 ·1012 molecules • cm-2 (with the calculated area occupied by single nanoparticle label of 132.7 nm2), DNA chemisorption based on DTCs is pointed as especially promising for DNA biosensors utilizing indirect detection in competitive assays.

SPRi-Based Biosensing Platforms for Detection of Specific DNA Sequences Using Thiolate and Dithiocarbamate Assemblies.

PubMed

Drozd, Marcin; Pietrzak, Mariusz D; Malinowska, Elżbieta

2018-01-01

The framework of presented study covers the development and examination of the analytical performance of surface plasmon resonance-based (SPR) DNA biosensors dedicated for a detection of model target oligonucleotide sequence. For this aim, various strategies of immobilization of DNA probes on gold transducers were tested. Besides the typical approaches: chemisorption of thiolated ssDNA (DNA-thiol) and physisorption of non-functionalized oligonucleotides, relatively new method based on chemisorption of dithiocarbamate-functionalized ssDNA (DNA-DTC) was applied for the first time for preparation of DNA-based SPR biosensor. The special emphasis was put on the correlation between the method of DNA immobilization and the composition of obtained receptor layer. The carried out studies focused on the examination of the capability of developed receptors layers to interact with both target DNA and DNA-functionalized AuNPs. It was found, that the detection limit of target DNA sequence (27 nb length) depends on the strategy of probe immobilization and backfilling method, and in the best case it amounted to 0.66 nM. Moreover, the application of ssDNA-functionalized gold nanoparticles (AuNPs) as plasmonic labels for secondary enhancement of SPR response is presented. The influence of spatial organization and surface density of a receptor layer on the ability to interact with DNA-functionalized AuNPs is discussed. Due to the best compatibility of receptors immobilized via DTC chemisorption: 1.47 ± 0.4 · 10 12 molecules · cm -2 (with the calculated area occupied by single nanoparticle label of ~132.7 nm 2 ), DNA chemisorption based on DTCs is pointed as especially promising for DNA biosensors utilizing indirect detection in competitive assays.

Sensitivity and specificity of PS/AA-modified nanoparticles used in malaria detection

PubMed Central

Thiramanas, Raweewan; Jangpatarapongsa, Kulachart; Asawapirom, Udom; Tangboriboonrat, Pramuan; Polpanich, Duangporn

2013-01-01

Summary Polystyrene (PS) nanoparticle (NP) copolymerized with acrylic acid (AA) and coloured monomer, i.e. 2,3,6,7-tetra(2,2′-bithiophene)-1,4,5,8-naphthalenetetracarboxylic-N,N′-di(2-methylallyl)-bisimide (ALN8T), was synthesized via the miniemulsion polymerization. Before applying for malaria antigen detection, the blue NP was conjugated with human polyclonal malaria IgG antibody (Ab) specific to Plasmodium falciparum. For the conjugation, three methods, i.e. physical adsorption, covalent coupling and affinity binding via streptavidin (SA) and biotin interaction, were employed. The optimum ratio of Ab to NPs used in each immobilization procedure and the latex agglutination test based on the reaction between Ab conjugated NPs and malaria patient plasma were investigated. All Ab–latex conjugates provided the high sensitivity for the detection of P. falciparum malaria plasma. The highest specificity to P. falciparum was obtained from using Ab–NPs conjugated via the SA–biotin interaction. PMID:23298152

The Face-to-Face Light Detection Paradigm: A New Methodology for Investigating Visuospatial Attention Across Different Face Regions in Live Face-to-Face Communication Settings.

PubMed

Thompson, Laura A; Malloy, Daniel M; Cone, John M; Hendrickson, David L

2010-01-01

We introduce a novel paradigm for studying the cognitive processes used by listeners within interactive settings. This paradigm places the talker and the listener in the same physical space, creating opportunities for investigations of attention and comprehension processes taking place during interactive discourse situations. An experiment was conducted to compare results from previous research using videotaped stimuli to those obtained within the live face-to-face task paradigm. A headworn apparatus is used to briefly display LEDs on the talker's face in four locations as the talker communicates with the participant. In addition to the primary task of comprehending speeches, participants make a secondary task light detection response. In the present experiment, the talker gave non-emotionally-expressive speeches that were used in past research with videotaped stimuli. Signal detection analysis was employed to determine which areas of the face received the greatest focus of attention. Results replicate previous findings using videotaped methods.

Evaluation of back scatter interferometry, a method for detecting protein binding in solution.

PubMed

Jepsen, S T; Jørgensen, T M; Zong, W; Trydal, T; Kristensen, S R; Sørensen, H S

2015-02-07

Back Scatter Interferometry (BSI) has been proposed to be a highly sensitive and versatile refractive index sensor usable for analytical detection of biomarker and protein interactions in solution. However the existing literature on BSI lacks a physical explanation of why protein interactions in general should contribute to the BSI signal. We have established a BSI system to investigate this subject in further detail. We contribute with a thorough analysis of the robustness of the sensor including unwanted contributions to the interferometric signal caused by temperature variation and dissolved gasses. We report a limit of the effective minimum detectability of refractive index at the 10(-7) level. Long term stability was examined by simultaneously monitoring the temperature inside the capillary revealing an average drift of 2.0 × 10(-7) per hour. Finally we show that measurements on protein A incubated with immunoglobulin G do not result in a signal that can be attributed to binding affinities as otherwise claimed in literature.

The Face-to-Face Light Detection Paradigm: A New Methodology for Investigating Visuospatial Attention Across Different Face Regions in Live Face-to-Face Communication Settings

PubMed Central

Thompson, Laura A.; Malloy, Daniel M.; Cone, John M.; Hendrickson, David L.

2009-01-01

We introduce a novel paradigm for studying the cognitive processes used by listeners within interactive settings. This paradigm places the talker and the listener in the same physical space, creating opportunities for investigations of attention and comprehension processes taking place during interactive discourse situations. An experiment was conducted to compare results from previous research using videotaped stimuli to those obtained within the live face-to-face task paradigm. A headworn apparatus is used to briefly display LEDs on the talker’s face in four locations as the talker communicates with the participant. In addition to the primary task of comprehending speeches, participants make a secondary task light detection response. In the present experiment, the talker gave non-emotionally-expressive speeches that were used in past research with videotaped stimuli. Signal detection analysis was employed to determine which areas of the face received the greatest focus of attention. Results replicate previous findings using videotaped methods. PMID:21113354

Image-based fall detection and classification of a user with a walking support system

NASA Astrophysics Data System (ADS)

Taghvaei, Sajjad; Kosuge, Kazuhiro

2017-10-01

The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems.We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user's depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called "RT Walker") by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user's motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.

SH2-PLA: a sensitive in-solution approach for quantification of modular domain binding by proximity ligation and real-time PCR.

PubMed

Thompson, Christopher M; Bloom, Lee R; Ogiue-Ikeda, Mari; Machida, Kazuya

2015-06-26

There is a great interest in studying phosphotyrosine dependent protein-protein interactions in tyrosine kinase pathways that play a critical role in many aspects of cellular function. We previously established SH2 profiling, a phosphoproteomic approach based on membrane binding assays that utilizes purified Src Homology 2 (SH2) domains as a molecular tool to profile the global tyrosine phosphorylation state of cells. However, in order to use this method to investigate SH2 binding sites on a specific target in cell lysate, additional procedures such as pull-down or immunoprecipitation which consume large amounts of sample are required. We have developed PLA-SH2, an alternative in-solution modular domain binding assay that takes advantage of Proximity Ligation Assay and real-time PCR. The SH2-PLA assay utilizes oligonucleotide-conjugated anti-GST and anti-EGFR antibodies recognizing a GST-SH2 probe and cellular EGFR, respectively. If the GST-SH2 and EGFR are in close proximity as a result of SH2-phosphotyrosine interactions, the two oligonucleotides are brought within a suitable distance for ligation to occur, allowing for efficient complex amplification via real-time PCR. The assay detected signal across at least 3 orders of magnitude of lysate input with a linear range spanning 1-2 orders and a low femtomole limit of detection for EGFR phosphotyrosine. SH2 binding kinetics determined by PLA-SH2 showed good agreement with established far-Western analyses for A431 and Cos1 cells stimulated with EGF at various times and doses. Further, we showed that PLA-SH2 can survey lung cancer tissues using 1 μl lysate without requiring phospho-enrichment. We showed for the first time that interactions between SH2 domain probes and EGFR in cell lysate can be determined in a microliter-scale assay using SH2-PLA. The obvious benefit of this method is that the low sample requirement allows detection of SH2 binding in samples which are difficult to analyze using traditional protein interaction assays. This feature along with short assay runtime makes this method a useful platform for the development of high throughput assays to determine modular domain-ligand interactions which could have wide-ranging applications in both basic and translational cancer research.

Spectrophotometric, colorimetric and visually detection of Pseudomonas aeruginosa ETA gene based gold nanoparticles DNA probe and endonuclease enzyme

NASA Astrophysics Data System (ADS)

Amini, Bahram; Kamali, Mehdi; Salouti, Mojtaba; Yaghmaei, Parichehreh

2018-06-01

Colorimetric DNA detection is preferred over other methods for clinical molecular diagnosis because it does not require expensive equipment. In the present study, the colorimetric method based on gold nanoparticles (GNPs) and endonuclease enzyme was used for the detection of P. aeruginosa ETA gene. Firstly, the primers and probe for P. aeruginosa exotoxin A (ETA) gene were designed and checked for specificity by the PCR method. Then, GNPs were synthesized using the citrate reduction method and conjugated with the prepared probe to develop the new nano-biosensor. Next, the extracted target DNA of the bacteria was added to GNP-probe complex to check its efficacy for P. aeruginosa ETA gene diagnosis. A decrease in absorbance was seen when GNP-probe-target DNA cleaved into the small fragments of BamHI endonuclease due to the weakened electrostatic interaction between GNPs and the shortened DNA. The right shift of the absorbance peak from 530 to 562 nm occurred after adding the endonuclease. It was measured using a UV-VIS absorption spectroscopy that indicates the existence of the P. aeruginosa ETA gene. Sensitivity was determined in the presence of different concentrations of target DNA of P. aeruginosa. The results obtained from the optimized conditions showed that the absorbance value has linear correlation with concentration of target DNA (R: 0.9850) in the range of 10-50 ng mL-1 with the limit detection of 9.899 ng mL-1. Thus, the specificity of the new method for detection of P. aeruginosa was established in comparison with other bacteria. Additionally, the designed assay was quantitatively applied to detect the P. aeruginosa ETA gene from 103 to 108 CFU mL-1 in real samples with a detection limit of 320 CFU mL-1.

Reconstituting protein interaction networks using parameter-dependent domain-domain interactions

PubMed Central

2013-01-01

Background We can describe protein-protein interactions (PPIs) as sets of distinct domain-domain interactions (DDIs) that mediate the physical interactions between proteins. Experimental data confirm that DDIs are more consistent than their corresponding PPIs, lending support to the notion that analyses of DDIs may improve our understanding of PPIs and lead to further insights into cellular function, disease, and evolution. However, currently available experimental DDI data cover only a small fraction of all existing PPIs and, in the absence of structural data, determining which particular DDI mediates any given PPI is a challenge. Results We present two contributions to the field of domain interaction analysis. First, we introduce a novel computational strategy to merge domain annotation data from multiple databases. We show that when we merged yeast domain annotations from six annotation databases we increased the average number of domains per protein from 1.05 to 2.44, bringing it closer to the estimated average value of 3. Second, we introduce a novel computational method, parameter-dependent DDI selection (PADDS), which, given a set of PPIs, extracts a small set of domain pairs that can reconstruct the original set of protein interactions, while attempting to minimize false positives. Based on a set of PPIs from multiple organisms, our method extracted 27% more experimentally detected DDIs than existing computational approaches. Conclusions We have provided a method to merge domain annotation data from multiple sources, ensuring large and consistent domain annotation for any given organism. Moreover, we provided a method to extract a small set of DDIs from the underlying set of PPIs and we showed that, in contrast to existing approaches, our method was not biased towards DDIs with low or high occurrence counts. Finally, we used these two methods to highlight the influence of the underlying annotation density on the characteristics of extracted DDIs. Although increased annotations greatly expanded the possible DDIs, the lack of knowledge of the true biological false positive interactions still prevents an unambiguous assignment of domain interactions responsible for all protein network interactions. Executable files and examples are given at: http://www.bhsai.org/downloads/padds/ PMID:23651452

Experimental investigation of three-wave interactions of capillary surface-waves

NASA Astrophysics Data System (ADS)

Berhanu, Michael; Cazaubiel, Annette; Deike, Luc; Jamin, Timothee; Falcon, Eric

2014-11-01

We report experiments studying the non-linear interaction between two crossing wave-trains of gravity-capillary surface waves generated in a closed laboratory tank. Using a capacitive wave gauge and Diffusive Light Photography method, we detect a third wave of smaller amplitude whose frequency and wavenumber are in agreement with the weakly non-linear triadic resonance interaction mechanism. By performing experiments in stationary and transient regimes and taking into account the viscous dissipation, we estimate directly the growth rate of the resonant mode in comparison with theory. These results confirm at least qualitatively and extend earlier experimental results obtained only for unidirectional wave train. Finally we discuss relevance of three-wave interaction mechanisms in recent experiment studying capillary wave turbulence.

Detection and characterization of nonspecific, sparsely-populated binding modes in the early stages of complexation

PubMed Central

Cardone, A.; Bornstein, A.; Pant, H. C.; Brady, M.; Sriram, R.; Hassan, S. A.

2015-01-01

A method is proposed to study protein-ligand binding in a system governed by specific and non-specific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultra-weak associations lead instead to broader distributions, a manifestation of non-specific, sparsely-populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (pre-relaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. PMID:25782918

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Imaging and Elastometry of Blood Clots Using Magnetomotive Optical Coherence Tomography and Labeled Platelets

PubMed Central

Oldenburg, Amy L.; Wu, Gongting; Spivak, Dmitry; Tsui, Frank; Wolberg, Alisa S.; Fischer, Thomas H.

2013-01-01

Improved methods for imaging and assessment of vascular defects are needed for directing treatment of cardiovascular pathologies. In this paper, we employ magnetomotive optical coherence tomography (MMOCT) as a platform both to detect and to measure the elasticity of blood clots. Detection is enabled through the use of rehydrated, lyophilized platelets loaded with superparamagnetic iron oxides (SPIO-RL platelets) that are functional infusion agents that adhere to sites of vascular endothelial damage. Evidence suggests that the sensitivity for detection is improved over threefold by magnetic interactions between SPIOs inside RL platelets. Using the same MMOCT system, we show how elastometry of simulated clots, using resonant acoustic spectroscopy, is correlated with the fibrin content of the clot. Both methods are based upon magnetic actuation and phase-sensitive optical monitoring of nanoscale displacements using MMOCT, underscoring its utility as a broad-based platform to detect and measure the molecular structure and composition of blood clots. PMID:23833549

Silver nanoparticles-based colorimetric array for the detection of Thiophanate-methyl

NASA Astrophysics Data System (ADS)

Zheng, Mingda; Wang, Yingying; Wang, Chenge; Wei, Wei; Ma, Shuang; Sun, Xiaohan; He, Jiang

2018-06-01

A simple and selective colorimetric sensor based on citrate capped silver nanoparticles (Cit-AgNPs) is proposed for the detection of Thiophanate-methyl (TM) with high sensitivity and selectivity. The method based on the color change of Cit-AgNPs from yellow to cherry red with the addition of TM to Cit-AgNPs that caused a red-shift on the surface plasmon resonance (SPR) band from 394 nm to 525 nm due to the hydrogen-bonding and substitution. The density functional theory (DFT) method was also calculated the interactions between the TM and citrate ions. Under the optimized conditions, a linear relationship between the absorption ratio (A525nm/A394nm) and TM concentration was found in the range of 2-100 μM with correlation coefficient (R2) of 0.988. The detection limit of TM was 0.12 μM by UV-vis spectrometer. Moreover, the applicability of colorimetric sensor is successfully verified by the detection of TM in environmental samples with good recoveries.

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

PubMed Central

Ritchie, Marylyn D.; Hahn, Lance W.; Roodi, Nady; Bailey, L. Renee; Dupont, William D.; Parl, Fritz F.; Moore, Jason H.

2001-01-01

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease. PMID:11404819

In vitro interactions between splenocytes and dansylamide dye-embedded nanoparticles detected by flow cytometry

PubMed Central

Nyland, Jennifer F.; Bai, Jennifer J. K.; Katz, Howard E.; Silbergeld, Ellen K.

2009-01-01

Engineered nanoparticles (NPs) possess a range of biological activity. In vitro methods for assessing toxicity and efficacy would be enhanced by simultaneous quantitative information on the behavior of NPs in culture systems and signals of cell response. We have developed a method for visualizing NPs within cells using standard flow cytometric techniques and uniquely designed spherical siloxane NPs with an embedded (covalently bound) dansylamide dye. This method allowed NP visualization without obscuring detection of relevant biomarkers of cell subtype, activation state, and other events relevant to assessing bioactivity. We determined that NPs penetrated cells and induced a range of biological signals consistent with activation and costimulation. These results indicate that NPs may affect cell function at concentrations below those inducing cytotoxicity or apoptosis and demonstrate a novel method to image both localization of NPs and cell-level effects. PMID:19523425

Fluorogenic Ag+–Tetrazolate Aggregation Enables Efficient Fluorescent Biological Silver Staining

PubMed Central

Xie, Sheng; Wong, Alex Y. H.; Kwok, Ryan T. K.; Li, Ying; Su, Huifang; Lam, Jacky W. Y.

2018-01-01

Abstract Silver staining, which exploits the special bioaffinity and the chromogenic reduction of silver ions, is an indispensable visualization method in biology. It is a most popular method for in‐gel protein detection. However, it is limited by run‐to‐run variability, background staining, inability for protein quantification, and limited compatibility with mass spectroscopic (MS) analysis; limitations that are largely attributed to the tricky chromogenic visualization. Herein, we reported a novel water‐soluble fluorogenic Ag+ probe, the sensing mechanism of which is based on an aggregation‐induced emission (AIE) process driven by tetrazolate‐Ag+ interactions. The fluorogenic sensing can substitute the chromogenic reaction, leading to a new fluorescence silver staining method. This new staining method offers sensitive detection of total proteins in polyacrylamide gels with a broad linear dynamic range and robust operations that rival the silver nitrate stain and the best fluorescent stains. PMID:29575702

Remote sensing and avian influenza: A review of image processing methods for extracting key variables affecting avian influenza virus survival in water from Earth Observation satellites

NASA Astrophysics Data System (ADS)

Tran, Annelise; Goutard, Flavie; Chamaillé, Lise; Baghdadi, Nicolas; Lo Seen, Danny

2010-02-01

Recent studies have highlighted the potential role of water in the transmission of avian influenza (AI) viruses and the existence of often interacting variables that determine the survival rate of these viruses in water; the two main variables are temperature and salinity. Remote sensing has been used to map and monitor water bodies for several decades. In this paper, we review satellite image analysis methods used for water detection and characterization, focusing on the main variables that influence AI virus survival in water. Optical and radar imagery are useful for detecting water bodies at different spatial and temporal scales. Methods to monitor the temperature of large water surfaces are also available. Current methods for estimating other relevant water variables such as salinity, pH, turbidity and water depth are not presently considered to be effective.

TEAM: efficient two-locus epistasis tests in human genome-wide association study.

PubMed

Zhang, Xiang; Huang, Shunping; Zou, Fei; Wang, Wei

2010-06-15

As a promising tool for identifying genetic markers underlying phenotypic differences, genome-wide association study (GWAS) has been extensively investigated in recent years. In GWAS, detecting epistasis (or gene-gene interaction) is preferable over single locus study since many diseases are known to be complex traits. A brute force search is infeasible for epistasis detection in the genome-wide scale because of the intensive computational burden. Existing epistasis detection algorithms are designed for dataset consisting of homozygous markers and small sample size. In human study, however, the genotype may be heterozygous, and number of individuals can be up to thousands. Thus, existing methods are not readily applicable to human datasets. In this article, we propose an efficient algorithm, TEAM, which significantly speeds up epistasis detection for human GWAS. Our algorithm is exhaustive, i.e. it does not ignore any epistatic interaction. Utilizing the minimum spanning tree structure, the algorithm incrementally updates the contingency tables for epistatic tests without scanning all individuals. Our algorithm has broader applicability and is more efficient than existing methods for large sample study. It supports any statistical test that is based on contingency tables, and enables both family-wise error rate and false discovery rate controlling. Extensive experiments show that our algorithm only needs to examine a small portion of the individuals to update the contingency tables, and it achieves at least an order of magnitude speed up over the brute force approach.

Functional and Genomic Analyses of Alpha-Solenoid Proteins

PubMed Central

Fournier, David; Palidwor, Gareth A.; Shcherbinin, Sergey; Szengel, Angelika; Schaefer, Martin H.; Perez-Iratxeta, Carol; Andrade-Navarro, Miguel A.

2013-01-01

Alpha-solenoids are flexible protein structural domains formed by ensembles of alpha-helical repeats (Armadillo and HEAT repeats among others). While homology can be used to detect many of these repeats, some alpha-solenoids have very little sequence homology to proteins of known structure and we expect that many remain undetected. We previously developed a method for detection of alpha-helical repeats based on a neural network trained on a dataset of protein structures. Here we improved the detection algorithm and updated the training dataset using recently solved structures of alpha-solenoids. Unexpectedly, we identified occurrences of alpha-solenoids in solved protein structures that escaped attention, for example within the core of the catalytic subunit of PI3KC. Our results expand the current set of known alpha-solenoids. Application of our tool to the protein universe allowed us to detect their significant enrichment in proteins interacting with many proteins, confirming that alpha-solenoids are generally involved in protein-protein interactions. We then studied the taxonomic distribution of alpha-solenoids to discuss an evolutionary scenario for the emergence of this type of domain, speculating that alpha-solenoids have emerged in multiple taxa in independent events by convergent evolution. We observe a higher rate of alpha-solenoids in eukaryotic genomes and in some prokaryotic families, such as Cyanobacteria and Planctomycetes, which could be associated to increased cellular complexity. The method is available at http://cbdm.mdc-berlin.de/~ard2/. PMID:24278209

Quantification of Ligand Binding to G-Protein Coupled Receptors on Cell Membranes by Ellipsometry

PubMed Central

Kriechbaumer, Verena; Nabok, Alexei; Widdowson, Robert; Smith, David P.; Abell, Ben M.

2012-01-01

G-protein-coupled receptors (GPCRs) are prime drug targets and targeted by approximately 60% of current therapeutic drugs such as β-blockers, antipsychotics and analgesics. However, no biophysical methods are available to quantify their interactions with ligand binding in a native environment. Here, we use ellipsometry to quantify specific interactions of receptors within native cell membranes. As a model system, the GPCR-ligand CXCL12α and its receptor CXCR4 are used. Human-derived Ishikawa cells were deposited onto gold coated slides via Langmuir-Schaefer film deposition and interactions between the receptor CXCR4 on these cells and its ligand CXCL12α were detected via total internal reflection ellipsometry (TIRE). This interaction could be inhibited by application of the CXCR4-binding drug AMD3100. Advantages of this approach are that it allows measurement of interactions in a lipid environment without the need for labelling, protein purification or reconstitution of membrane proteins. This technique is potentially applicable to a wide variety of cell types and their membrane receptors, providing a novel method to determine ligand or drug interactions targeting GPCRs and other membrane proteins. PMID:23049983

Life-table methods for detecting age-risk factor interactions in long-term follow-up studies.

PubMed

Logue, E E; Wing, S

1986-01-01

Methodological investigation has suggested that age-risk factor interactions should be more evident in age of experience life tables than in follow-up time tables due to the mixing of ages of experience over follow-up time in groups defined by age at initial examination. To illustrate the two approaches, age modification of the effect of total cholesterol on ischemic heart disease mortality in two long-term follow-up studies was investigated. Follow-up time life table analysis of 116 deaths over 20 years in one study was more consistent with a uniform relative risk due to cholesterol, while age of experience life table analysis was more consistent with a monotonic negative age interaction. In a second follow-up study (160 deaths over 24 years), there was no evidence of a monotonic negative age-cholesterol interaction by either method. It was concluded that age-specific life table analysis should be used when age-risk factor interactions are considered, but that both approaches yield almost identical results in absence of age interaction. The identification of the more appropriate life-table analysis should be ultimately guided by the nature of the age or time phenomena of scientific interest.

Antimicrobial activity of Eucalyptus camaldulensis essential oils and their interactions with conventional antimicrobial agents against multi-drug resistant Acinetobacter baumannii.

PubMed

Knezevic, Petar; Aleksic, Verica; Simin, Natasa; Svircev, Emilija; Petrovic, Aleksandra; Mimica-Dukic, Neda

2016-02-03

Traditional herbal medicine has become an important issue on the global scale during the past decade. Among drugs of natural origin, special place belongs to essential oils, known as strong antimicrobial agents that can be used to combat antibiotic-resistant bacteria. Eucalyptus camaldulensis leaves are traditional herbal remedy used for various purposes, including treatment of infections. The aim of this study was to determine antimicrobial potential of two E. camaldulensis essential oils against multi-drug resistant (MDR) Acinetobacter baumannii wound isolates and to examine possible interactions of essential oils with conventional antimicrobial agents. Chemical composition of essential oils was determined by gas chromatography-mass spectrometry analysis (GC-MS). MIC values of essential oils against A. baumannii strains were estimated by modified broth microdilution method. The components responsible for antimicrobial activity were detected by bioautographic analysis. The potential synergy between the essential oils and antibiotics (ciprofloxacin, gentamicin and polymyxin B) was examined by checkerboard method and time kill curve. The dominant components of both essential oils were spatulenol, cryptone, p-cimene, 1,8-cineole, terpinen-4-ol and β-pinene. The detected MICs for the E. camaldulensis essential oils were in range from 0.5 to 2 μl mL(-1). The bioautographic assay confirmed antibacterial activity of polar terpene compounds. In combination with conventional antibiotics (ciprofloxacin, gentamicin and polymyxin B), the examined essential oils showed synergistic antibacterial effect in most of the cases, while in some even re-sensitized MDR A. baumannii strains. The synergistic interaction was confirmed by time-kill curves for E. camaldulensis essential oil and polymyxin B combination which reduced bacterial count under detection limit very fast, i.e. after 6h of incubation. The detected anti-A. baumannii activity of E. camaldulensis essential oils justifies traditional use of this plant. The proven E. camaldulensis essential oil synergistic interactions with conventional antibiotics could lead to the development of new treatment strategies of infections caused by MDR A. baumannii strains in the term of antibiotic dose reduction. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Shearlet-based edge detection: flame fronts and tidal flats

NASA Astrophysics Data System (ADS)

King, Emily J.; Reisenhofer, Rafael; Kiefer, Johannes; Lim, Wang-Q.; Li, Zhen; Heygster, Georg

2015-09-01

Shearlets are wavelet-like systems which are better suited for handling geometric features in multi-dimensional data than traditional wavelets. A novel method for edge and line detection which is in the spirit of phase congruency but is based on a complex shearlet transform will be presented. This approach to detection yields an approximate tangent direction of detected discontinuities as a byproduct of the computation, which then yields local curvature estimates. Two applications of the edge detection method will be discussed. First, the tracking and classification of flame fronts is a critical component of research in technical thermodynamics. Quite often, the flame fronts are transient or weak and the images are noisy. The standard methods used in the field for the detection of flame fronts do not handle such data well. Fortunately, using the shearlet-based edge measure yields good results as well as an accurate approximation of local curvature. Furthermore, a modification of the method will yield line detection, which is important for certain imaging modalities. Second, the Wadden tidal flats are a biodiverse region along the North Sea coast. One approach to surveying the delicate region and tracking the topographical changes is to use pre-existing Synthetic Aperture Radar (SAR) images. Unfortunately, SAR data suffers from multiplicative noise as well as sensitivity to environmental factors. The first large-scale mapping project of that type showed good results but only with a tremendous amount of manual interaction because there are many edges in the data which are not boundaries of the tidal flats but are edges of features like fields or islands. Preliminary results will be presented.

Antibody modified gold nanoparticles for fast and selective, colorimetric T7 bacteriophage detection.

PubMed

Lesniewski, Adam; Los, Marcin; Jonsson-Niedziółka, Martin; Krajewska, Anna; Szot, Katarzyna; Los, Joanna M; Niedziolka-Jonsson, Joanna

2014-04-16

Herein, we report a colorimetric immunosensor for T7 bacteriophage based on gold nanoparticles modified with covalently bonded anti-T7 antibodies. The new immunosensor allows for a fast, simple, and selective detection of T7 virus. T7 virions form immunological complexes with the antibody modified gold nanoparticles which causes them to aggregate. The aggregation can be observed with the naked eye as a color change from red to purple, as well as with a UV-vis spectrophotometer. The aggregate formation was confirmed with SEM imaging. Sensor selectivity against the M13 bacteriophage was demonstrated. The limit of detection (LOD) is 1.08 × 10(10) PFU/mL (18 pM) T7. The new method was compared with a traditional plaque test. In contrast to biological tests the colorimetric method allows for detection of all T7 phages, not only those biologically active. This includes phage ghosts and fragments of virions. T7 virus has been chosen as a model organism for adenoviruses. The described method has several advantages over the traditional ones. It is much faster than a standard plaque test. It is more robust since no bacteria-virus interactions are utilized in the detection process. Since antibodies are available for a large variety of pathogenic viruses, the described concept is very flexible and can be adapted to detect many different viruses, not only bacteriophages. Contrary to the classical immunoassays, it is a one-step detection method, and no additional amplification, e.g., enzymatic, is needed to read the result.

Low cost sensing technology for type 2 diabetes monitoring

NASA Astrophysics Data System (ADS)

Sarswat, Prashant; Free, Michael

2015-03-01

Alpha-hydroxybutyrate (2-hydroxybutyrate or α-HB) is becoming more widely recognized as an important metabolic biomarker that has been shown to be highly correlated with prediabetes and other metabolic diseases. In 2012 there were 86 million Americans with prediabetes, many of whom are not aware they have prediabetes, but could be diagnosed and treated to prevent type 2 diabetes if a simple, low-cost, convenient test were available. We have developed new, low-cost, accurate α-HB detection methods that can be used for the detection and monitoring of diseases such as prediabetes, type 2 diabetes, β-cell dysfunction, and early hyperglycemia. The new sensing method utilizes a diol recognition moiety, additives and a photoinitiator to detect α-HB at levels near 1 micro g/l in the presence of serum compounds such as lactic acid, sodium pyruvate, and glucose. The objective of this research is to improve the understanding of the interactions that enhance α-HB detection to enable additional improvements in α-HB detection as well as improvements in other biosensor applications.

Carbene footprinting accurately maps binding sites in protein-ligand and protein-protein interactions

NASA Astrophysics Data System (ADS)

Manzi, Lucio; Barrow, Andrew S.; Scott, Daniel; Layfield, Robert; Wright, Timothy G.; Moses, John E.; Oldham, Neil J.

2016-11-01

Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation.

Quantitative Detection of Nucleoside Analogues by Multi-enzyme Biosensors using Time-Resolved Kinetic Measurements.

PubMed

Muthu, Pravin; Lutz, Stefan

2016-04-05

Fast, simple and cost-effective methods for detecting and quantifying pharmaceutical agents in patients are highly sought after to replace equipment and labor-intensive analytical procedures. The development of new diagnostic technology including portable detection devices also enables point-of-care by non-specialists in resource-limited environments. We have focused on the detection and dose monitoring of nucleoside analogues used in viral and cancer therapies. Using deoxyribonucleoside kinases (dNKs) as biosensors, our chemometric model compares observed time-resolved kinetics of unknown analytes to known substrate interactions across multiple enzymes. The resulting dataset can simultaneously identify and quantify multiple nucleosides and nucleoside analogues in complex sample mixtures. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interferometric biosensing platform for multiplexed digital detection of viral pathogens and biomarkers

NASA Astrophysics Data System (ADS)

Daaboul, George

Label-free optical biosensors have been established as proven tools for monitoring specific biomolecular interactions. However, compact and robust embodiments of such instruments have yet to be introduced in order to provide sensitive, quantitative, and high-throughput biosensing for low-cost research and clinical applications. Here we present the interferometric reflectance-imaging sensor (IRIS). IRIS allows sensitive label free analysis using an inexpensive and durable multi-color LED illumination source on a silicon based surface. IRIS monitors biomolecular interaction through measurement of biomass addition to the sensor's surface. We demonstrate the capability of this system to dynamically monitor antigen---antibody interactions with a noise floor of 5.2 pg/mm 2 and DNA single mismatch detection under isothermal melting conditions in an array format. Ensemble detection of binding events using IRIS did not provide the sensitivity needed for detection of infectious disease and biomarkers at clinically relevant concentrations. Therefore, a new approach was adapted to the IRIS platform that allowed the detection and identification of individual nanoparticles on the sensor's surface. The new detection method was termed single-particle IRIS (SP-IRIS). We developed two detection modalities for SP-IRIS. The first modality is when the target is a nanoparticle such as a virus. We verified that SP-IRIS can accurately detect and size individual viral particles. Then we demonstrated that single nanoparticle counting and sizing methodology on SP-IRIS leads to a specific and sensitive virus sensor that can be multiplexed. Finally, we developed an assay for the detection of Ebola and Marburg. A detection limit of 3 x 103 PFU/ml was demonstrated for vesicular stomatitis virus (VSV) pseudotyped with Ebola or Marburg virus glycoprotein. We have demonstrated that virus detection can be done in human whole blood directly without the need for sample preparation. The second modality of SP-IRIS we developed was single molecule counting of biomarkers utilizing a sandwich assay with detection probes labeled with gold nanoparticles. We demonstrated the use of single molecule counting in a nucleic acid assay for melanoma biomarker detection. We showed that a single molecule counting assay can lead to detection limits in the attomolar range. The improved sensitivity of IRIS utilizing single nanoparticle detection holds promise for a simple and low-cost technology for rapid virus detection and multiplexed molecular screening for clinical applications.