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Sample records for sequential features subcellular

Prediction of rat protein subcellular localization with pseudo amino acid composition based on multiple sequential features.

PubMed

Shi, Ruijia; Xu, Cunshuan

2011-06-01

The study of rat proteins is an indispensable task in experimental medicine and drug development. The function of a rat protein is closely related to its subcellular location. Based on the above concept, we construct the benchmark rat proteins dataset and develop a combined approach for predicting the subcellular localization of rat proteins. From protein primary sequence, the multiple sequential features are obtained by using of discrete Fourier analysis, position conservation scoring function and increment of diversity, and these sequential features are selected as input parameters of the support vector machine. By the jackknife test, the overall success rate of prediction is 95.6% on the rat proteins dataset. Our method are performed on the apoptosis proteins dataset and the Gram-negative bacterial proteins dataset with the jackknife test, the overall success rates are 89.9% and 96.4%, respectively. The above results indicate that our proposed method is quite promising and may play a complementary role to the existing predictors in this area.
Enhancing membrane protein subcellular localization prediction by parallel fusion of multi-view features.

PubMed

Yu, Dongjun; Wu, Xiaowei; Shen, Hongbin; Yang, Jian; Tang, Zhenmin; Qi, Yong; Yang, Jingyu

2012-12-01

Membrane proteins are encoded by ~ 30% in the genome and function importantly in the living organisms. Previous studies have revealed that membrane proteins' structures and functions show obvious cell organelle-specific properties. Hence, it is highly desired to predict membrane protein's subcellular location from the primary sequence considering the extreme difficulties of membrane protein wet-lab studies. Although many models have been developed for predicting protein subcellular locations, only a few are specific to membrane proteins. Existing prediction approaches were constructed based on statistical machine learning algorithms with serial combination of multi-view features, i.e., different feature vectors are simply serially combined to form a super feature vector. However, such simple combination of features will simultaneously increase the information redundancy that could, in turn, deteriorate the final prediction accuracy. That's why it was often found that prediction success rates in the serial super space were even lower than those in a single-view space. The purpose of this paper is investigation of a proper method for fusing multiple multi-view protein sequential features for subcellular location predictions. Instead of serial strategy, we propose a novel parallel framework for fusing multiple membrane protein multi-view attributes that will represent protein samples in complex spaces. We also proposed generalized principle component analysis (GPCA) for feature reduction purpose in the complex geometry. All the experimental results through different machine learning algorithms on benchmark membrane protein subcellular localization datasets demonstrate that the newly proposed parallel strategy outperforms the traditional serial approach. We also demonstrate the efficacy of the parallel strategy on a soluble protein subcellular localization dataset indicating the parallel technique is flexible to suite for other computational biology problems. The software and datasets are available at: http://www.csbio.sjtu.edu.cn/bioinf/mpsp.
PREAL: prediction of allergenic protein by maximum Relevance Minimum Redundancy (mRMR) feature selection

PubMed Central

2013-01-01

Background Assessment of potential allergenicity of protein is necessary whenever transgenic proteins are introduced into the food chain. Bioinformatics approaches in allergen prediction have evolved appreciably in recent years to increase sophistication and performance. However, what are the critical features for protein's allergenicity have been not fully investigated yet. Results We presented a more comprehensive model in 128 features space for allergenic proteins prediction by integrating various properties of proteins, such as biochemical and physicochemical properties, sequential features and subcellular locations. The overall accuracy in the cross-validation reached 93.42% to 100% with our new method. Maximum Relevance Minimum Redundancy (mRMR) method and Incremental Feature Selection (IFS) procedure were applied to obtain which features are essential for allergenicity. Results of the performance comparisons showed the superior of our method to the existing methods used widely. More importantly, it was observed that the features of subcellular locations and amino acid composition played major roles in determining the allergenicity of proteins, particularly extracellular/cell surface and vacuole of the subcellular locations for wheat and soybean. To facilitate the allergen prediction, we implemented our computational method in a web application, which can be available at http://gmobl.sjtu.edu.cn/PREAL/index.php. Conclusions Our new approach could improve the accuracy of allergen prediction. And the findings may provide novel insights for the mechanism of allergies. PMID:24565053
Physiological and structural differences in spatially distinct subpopulations of cardiac mitochondria: influence of cardiac pathologies

PubMed Central

Thapa, Dharendra; Shepherd, Danielle L.

2014-01-01

Cardiac tissue contains discrete pools of mitochondria that are characterized by their subcellular spatial arrangement. Subsarcolemmal mitochondria (SSM) exist below the cell membrane, interfibrillar mitochondria (IFM) reside in rows between the myofibrils, and perinuclear mitochondria are situated at the nuclear poles. Microstructural imaging of heart tissue coupled with the development of differential isolation techniques designed to sequentially separate spatially distinct mitochondrial subpopulations have revealed differences in morphological features including shape, absolute size, and internal cristae arrangement. These findings have been complemented by functional studies indicating differences in biochemical parameters and, potentially, functional roles for the ATP generated, based upon subcellular location. Consequently, mitochondrial subpopulations appear to be influenced differently during cardiac pathologies including ischemia/reperfusion, heart failure, aging, exercise, and diabetes mellitus. These influences may be the result of specific structural and functional disparities between mitochondrial subpopulations such that the stress elicited by a given cardiac insult differentially impacts subcellular locales and the mitochondria contained within. The goal of this review is to highlight some of the inherent structural and functional differences that exist between spatially distinct cardiac mitochondrial subpopulations as well as provide an overview of the differential impact of various cardiac pathologies on spatially distinct mitochondrial subpopulations. As an outcome, we will instill a basis for incorporating subcellular spatial location when evaluating the impact of cardiac pathologies on the mitochondrion. Incorporation of subcellular spatial location may offer the greatest potential for delineating the influence of cardiac pathology on this critical organelle. PMID:24778166
Accurate prediction of subcellular location of apoptosis proteins combining Chou's PseAAC and PsePSSM based on wavelet denoising.

PubMed

Yu, Bin; Li, Shan; Qiu, Wen-Ying; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-12-08

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research.
Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

PubMed Central

Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-01-01

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research. PMID:29296195
MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins

PubMed Central

Li, Hui; Wang, Rong; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area. PMID:28744305
MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

PubMed

Wang, Xiao; Li, Hui; Wang, Rong; Zhang, Qiuwen; Zhang, Weiwei; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area.
Many local pattern texture features: which is better for image-based multilabel human protein subcellular localization classification?

PubMed

Yang, Fan; Xu, Ying-Ying; Shen, Hong-Bin

2014-01-01

Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilabel subcellular image samples. We prepared a large multilabel immunohistochemistry (IHC) image benchmark from the Human Protein Atlas database and tested the performance of different local texture features, including completed local binary pattern, local tetra pattern, and the standard local binary pattern feature. According to our experimental results from binary relevance multilabel machine learning models, the completed local binary pattern, and local tetra pattern are more discriminative for describing IHC images when compared to the traditional local binary pattern descriptor. The combination of these two novel local pattern features and the conventional global texture features is also studied. The enhanced performance of final binary relevance classification model trained on the combined feature space demonstrates that different features are complementary to each other and thus capable of improving the accuracy of classification.
Protein location prediction using atomic composition and global features of the amino acid sequence

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

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less
Protein localization as a principal feature of the etiology and comorbidity of genetic diseases

PubMed Central

Park, Solip; Yang, Jae-Seong; Shin, Young-Eun; Park, Juyong; Jang, Sung Key; Kim, Sanguk

2011-01-01

Proteins targeting the same subcellular localization tend to participate in mutual protein–protein interactions (PPIs) and are often functionally associated. Here, we investigated the relationship between disease-associated proteins and their subcellular localizations, based on the assumption that protein pairs associated with phenotypically similar diseases are more likely to be connected via subcellular localization. The spatial constraints from subcellular localization significantly strengthened the disease associations of the proteins connected by subcellular localizations. In particular, certain disease types were more prevalent in specific subcellular localizations. We analyzed the enrichment of disease phenotypes within subcellular localizations, and found that there exists a significant correlation between disease classes and subcellular localizations. Furthermore, we found that two diseases displayed high comorbidity when disease-associated proteins were connected via subcellular localization. We newly explained 7584 disease pairs by using the context of protein subcellular localization, which had not been identified using shared genes or PPIs only. Our result establishes a direct correlation between protein subcellular localization and disease association, and helps to understand the mechanism of human disease progression. PMID:21613983
Subcellular mechanism of Escherichia coli inactivation during electrochemical disinfection with boron-doped diamond anode: A comparative study of three electrolytes.

PubMed

Long, Yujiao; Ni, Jinren; Wang, Zuhui

2015-11-01

Although the identification of effective oxidant species has been extensively studied, yet the subcellular mechanism of bacterial inactivation has never been clearly elucidated in electrochemical disinfection processes. In this study, subcellular mechanism of Escherichia coli inactivation during electrochemical disinfection was revealed in terms of comprehensive factors such as cell morphology, total organic components, K(+) leakage, membrane permeability, lipid peroxidation, membrane potential, membrane proteins, intracellular enzyme, cellular ATP level and DNA. The electrolysis was conducted with boron-doped diamond anode in three electrolytes including chloride, sulfate and phosphate. Results demonstrated that cell inactivation was mainly attributed to damage to the intracellular enzymatic systems in chloride solution. In sulfate solution, certain essential membrane proteins like the K(+) ion transport systems were eliminated. Thus, the pronounced K(+) leakage from cytosol resulted in gradual collapse of the membrane potential, which would hinder the subcellular localization of cell division-related proteins as well as ATP synthesis and thereby lead to the bacterial inactivation. Remarkable lipid peroxidation was observed, while the intracellular damage was negligible. In phosphate solution, the cells sequentially underwent overall destruction as a whole cell with no captured intermediate state, during which the organic components of the cells were mostly subjected to mineralization. This study provided a thorough insight into the bacterial inactivation mechanism on the subcellular level. Copyright © 2015 Elsevier Ltd. All rights reserved.
Compressed learning and its applications to subcellular localization.

PubMed

Zheng, Zhong-Long; Guo, Li; Jia, Jiong; Xie, Chen-Mao; Zeng, Wen-Cai; Yang, Jie

2011-09-01

One of the main challenges faced by biological applications is to predict protein subcellular localization in automatic fashion accurately. To achieve this in these applications, a wide variety of machine learning methods have been proposed in recent years. Most of them focus on finding the optimal classification scheme and less of them take the simplifying the complexity of biological systems into account. Traditionally, such bio-data are analyzed by first performing a feature selection before classification. Motivated by CS (Compressed Sensing) theory, we propose the methodology which performs compressed learning with a sparseness criterion such that feature selection and dimension reduction are merged into one analysis. The proposed methodology decreases the complexity of biological system, while increases protein subcellular localization accuracy. Experimental results are quite encouraging, indicating that the aforementioned sparse methods are quite promising in dealing with complicated biological problems, such as predicting the subcellular localization of Gram-negative bacterial proteins.
Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

PubMed

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.
SUBCELLULAR PHARMACOKINETICS AND ITS POTENTIAL FOR LIBRARY FOCUSING (R826652)

EPA Science Inventory

Abstract
Subcellular pharmacokinetics (SP) optimizes biology-related factors in the design of libraries for high throughput screening by defining comparatively narrow ranges of properties (lipophilicity, amphiphilicity, acidity, reactivity, 3D-structural features) of t...
Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

PubMed

Zhou, Hang; Yang, Yang; Shen, Hong-Bin

2017-03-15

Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Multilabel learning via random label selection for protein subcellular multilocations prediction.

PubMed

Wang, Xiao; Li, Guo-Zheng

2013-01-01

Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multilocation proteins to multiple proteins with single location, which does not take correlations among different subcellular locations into account. In this paper, a novel method named random label selection (RALS) (multilabel learning via RALS), which extends the simple binary relevance (BR) method, is proposed to learn from multilocation proteins in an effective and efficient way. RALS does not explicitly find the correlations among labels, but rather implicitly attempts to learn the label correlations from data by augmenting original feature space with randomly selected labels as its additional input features. Through the fivefold cross-validation test on a benchmark data set, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark data sets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multilocations of proteins. The prediction web server is available at >http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.
Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins

PubMed Central

Handfield, Louis-François; Chong, Yolanda T.; Simmons, Jibril; Andrews, Brenda J.; Moses, Alan M.

2013-01-01

Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images. PMID:23785265
Imaging trace element distributions in single organelles and subcellular features

NASA Astrophysics Data System (ADS)

Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

2016-02-01

The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. It could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.
Design and evaluation of a microfluidic system for inhibition studies of yeast cell signaling

NASA Astrophysics Data System (ADS)

Hamngren, Charlotte; Dinér, Peter; Grøtli, Morten; Goksör, Mattias; Adiels, Caroline B.

2012-10-01

In cell signaling, different perturbations lead to different responses and using traditional biological techniques that result in averaged data may obscure important cell-to-cell variations. The aim of this study was to develop and evaluate a four-inlet microfluidic system that enables single-cell analysis by investigating the effect on Hog1 localization post a selective Hog1 inhibitor treatment during osmotic stress. Optical tweezers was used to position yeast cells in an array of desired size and density inside the microfluidic system. By changing the flow rates through the inlet channels, controlled and rapid introduction of two different perturbations over the cell array was enabled. The placement of the cells was determined by diffusion rates flow simulations. The system was evaluated by monitoring the subcellular localization of a fluorescently tagged kinase of the yeast "High Osmolarity Glycerol" (HOG) pathway, Hog1-GFP. By sequential treatment of the yeast cells with a selective Hog1 kinase inhibitor and sorbitol, the subcellular localization of Hog1-GFP was analysed on a single-cell level. The results showed impaired Hog1-GFP nuclear localization, providing evidence of a congenial design. The setup made it possible to remove and add an agent within 2 seconds, which is valuable for investigating the dynamic signal transduction pathways and cannot be done using traditional methods. We are confident that the features of the four-inlet microfluidic system will be a valuable tool and hence contribute significantly to unravel the mechanisms of the HOG pathway and similar dynamic signal transduction pathways.

HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2014-01-01

Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.
Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

PubMed

Saini, Harsh; Raicar, Gaurav; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

2015-12-07

Protein subcellular localization is an important topic in proteomics since it is related to a protein׳s overall function, helps in the understanding of metabolic pathways, and in drug design and discovery. In this paper, a basic approximation technique from natural language processing called the linear interpolation smoothing model is applied for predicting protein subcellular localizations. The proposed approach extracts features from syntactical information in protein sequences to build probabilistic profiles using dependency models, which are used in linear interpolation to determine how likely is a sequence to belong to a particular subcellular location. This technique builds a statistical model based on maximum likelihood. It is able to deal effectively with high dimensionality that hinders other traditional classifiers such as Support Vector Machines or k-Nearest Neighbours without sacrificing performance. This approach has been evaluated by predicting subcellular localizations of Gram positive and Gram negative bacterial proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.
How a (sub)Cellular Coincidence Detection Mechanism Featuring Layer-5 Pyramidal Cells May Help Produce Various Visual Phenomena.

PubMed

Bachmann, Talis

2015-01-01

Perceptual phenomena such as spatio-temporal illusions and masking are typically explained by psychological (cognitive) processing theories or large-scale neural theories involving inter-areal connectivity and neural circuits comprising of hundreds or more interconnected single cells. Subcellular mechanisms are hardly used for such purpose. Here, a mechanistic theoretical view is presented on how a subcellular brain mechanism of integration of presynaptic signals that arrive at different compartments of layer-5 pyramidal neurons could explain a couple of spatiotemporal visual-phenomenal effects unfolding along very brief time intervals within the range of the sub-second temporal scale.
Imaging trace element distributions in single organelles and subcellular features

DOE PAGES

Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; ...

2016-02-25

The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro-and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (whichmore » some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. In conclusion, it could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.« less
A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.
Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.
Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.
Automated Interpretation of Subcellular Patterns in Fluorescence Microscope Images for Location Proteomics

PubMed Central

Chen, Xiang; Velliste, Meel; Murphy, Robert F.

2010-01-01

Proteomics, the large scale identification and characterization of many or all proteins expressed in a given cell type, has become a major area of biological research. In addition to information on protein sequence, structure and expression levels, knowledge of a protein’s subcellular location is essential to a complete understanding of its functions. Currently subcellular location patterns are routinely determined by visual inspection of fluorescence microscope images. We review here research aimed at creating systems for automated, systematic determination of location. These employ numerical feature extraction from images, feature reduction to identify the most useful features, and various supervised learning (classification) and unsupervised learning (clustering) methods. These methods have been shown to perform significantly better than human interpretation of the same images. When coupled with technologies for tagging large numbers of proteins and high-throughput microscope systems, the computational methods reviewed here enable the new subfield of location proteomics. This subfield will make critical contributions in two related areas. First, it will provide structured, high-resolution information on location to enable Systems Biology efforts to simulate cell behavior from the gene level on up. Second, it will provide tools for Cytomics projects aimed at characterizing the behaviors of all cell types before, during and after the onset of various diseases. PMID:16752421
Sparse regressions for predicting and interpreting subcellular localization of multi-label proteins.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2016-02-24

Predicting protein subcellular localization is indispensable for inferring protein functions. Recent studies have been focusing on predicting not only single-location proteins, but also multi-location proteins. Almost all of the high performing predictors proposed recently use gene ontology (GO) terms to construct feature vectors for classification. Despite their high performance, their prediction decisions are difficult to interpret because of the large number of GO terms involved. This paper proposes using sparse regressions to exploit GO information for both predicting and interpreting subcellular localization of single- and multi-location proteins. Specifically, we compared two multi-label sparse regression algorithms, namely multi-label LASSO (mLASSO) and multi-label elastic net (mEN), for large-scale predictions of protein subcellular localization. Both algorithms can yield sparse and interpretable solutions. By using the one-vs-rest strategy, mLASSO and mEN identified 87 and 429 out of more than 8,000 GO terms, respectively, which play essential roles in determining subcellular localization. More interestingly, many of the GO terms selected by mEN are from the biological process and molecular function categories, suggesting that the GO terms of these categories also play vital roles in the prediction. With these essential GO terms, not only where a protein locates can be decided, but also why it resides there can be revealed. Experimental results show that the output of both mEN and mLASSO are interpretable and they perform significantly better than existing state-of-the-art predictors. Moreover, mEN selects more features and performs better than mLASSO on a stringent human benchmark dataset. For readers' convenience, an online server called SpaPredictor for both mLASSO and mEN is available at http://bioinfo.eie.polyu.edu.hk/SpaPredictorServer/.
Subcellular localization of full-length human myeloid leukemia factor 1 (MLF1) is independent of 14-3-3 proteins.

PubMed

Molzan, Manuela; Ottmann, Christian

2013-03-01

Myeloid leukemia factor 1 (MLF1) is associated with the development of leukemic diseases such as acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, information on the physiological function of MLF1 is limited and mostly derived from studies identifying MLF1 interaction partners like CSN3, MLF1IP, MADM, Manp and the 14-3-3 proteins. The 14-3-3-binding site surrounding S34 is one of the only known functional features of the MLF1 sequence, along with one nuclear export sequence (NES) and two nuclear localization sequences (NLS). It was recently shown that the subcellular localization of mouse MLF1 is dependent on 14-3-3 proteins. Based on these findings, we investigated whether the subcellular localization of human MLF1 was also directly 14-3-3-dependent. Live cell imaging with GFP-fused human MLF1 was used to study the effects of mutations and deletions on its subcellular localization. Surprisingly, we found that the subcellular localization of full-length human MLF1 is 14-3-3-independent, and is probably regulated by other as-yet-unknown proteins.
Imaging cells and sub-cellular structures with ultrahigh resolution full-field X-ray microscopy.

PubMed

Chien, C C; Tseng, P Y; Chen, H H; Hua, T E; Chen, S T; Chen, Y Y; Leng, W H; Wang, C H; Hwu, Y; Yin, G C; Liang, K S; Chen, F R; Chu, Y S; Yeh, H I; Yang, Y C; Yang, C S; Zhang, G L; Je, J H; Margaritondo, G

2013-01-01

Our experimental results demonstrate that full-field hard-X-ray microscopy is finally able to investigate the internal structure of cells in tissues. This result was made possible by three main factors: the use of a coherent (synchrotron) source of X-rays, the exploitation of contrast mechanisms based on the real part of the refractive index and the magnification provided by high-resolution Fresnel zone-plate objectives. We specifically obtained high-quality microradiographs of human and mouse cells with 29 nm Rayleigh spatial resolution and verified that tomographic reconstruction could be implemented with a final resolution level suitable for subcellular features. We also demonstrated that a phase retrieval method based on a wave propagation algorithm could yield good subcellular images starting from a series of defocused microradiographs. The concluding discussion compares cellular and subcellular hard-X-ray microradiology with other techniques and evaluates its potential impact on biomedical research. Copyright © 2012 Elsevier Inc. All rights reserved.
Multiscale Investigation from Subcellular to Tissue Scale of Onion Epidermal Plant Cell Wall Mechanical Properties

NASA Astrophysics Data System (ADS)

Zamil, Mohammad Shafayet

The physical and mechanical properties of cell walls, their shape, how they are arranged and interact with each other determine the architecture of plant organs and how they mechanically respond to different environmental and loading conditions. Due to the distinctive hierarchy from subcellular to tissue scale, plant materials can exhibit remarkably different mechanical properties. To date, how the subcellular scale arrangement and the mechanical properties of plant cell wall structural constituents give rise to macro or tissue scale mechanical responses is not yet well understood. Although the tissue scale plant cell wall samples are easy to prepare and put to different types of mechanical tests, the hierarchical features that emerge when moving towards a higher scale make it complicated to link the macro scale results to micro or subcellular scale structural components. On the other hand, the microscale size of cell brings formidable challenges to prepare and grip samples and carry mechanical tests under tensile loading at subcellular scale. This study attempted to develop a set of test protocols based on microelectromechanical system (MEMS) tensile testing devices for characterizing plant cell wall materials at different length scales. For the ease of sample preparation and well established database of the composition and conformation of its structural constituents, onion epidermal cell wall profile was chosen as the study material. Based on the results and findings of multiscale mechanical characterization, a framework of architecture-based finite element method (FEM) computational model was developed. The computational model laid the foundation of bridging the subcellular or microscale to the tissue or macroscale mechanical properties. This study suggests that there are important insights of cell wall mechanics and structural features that can only be investigated by carrying tensile characterization of samples not confounded by extracellular parameters. To the best of our knowledge, the plant cell wall at subcellular scale was never characterized under tensile loading. By coupling the structure based multiscale modeling and mechanical characterizations at different length scales, an attempt was made to provide novel insights towards understanding the mechanics and architecture of cell wall. This study also suggests that a multiscale investigation is essential for garnering fundamental insights into the hierarchical deformation of biological systems.
Quantification of non-coding RNA target localization diversity and its application in cancers.

PubMed

Cheng, Lixin; Leung, Kwong-Sak

2018-04-01

Subcellular localization is pivotal for RNAs and proteins to implement biological functions. The localization diversity of protein interactions has been studied as a crucial feature of proteins, considering that the protein-protein interactions take place in various subcellular locations. Nevertheless, the localization diversity of non-coding RNA (ncRNA) target proteins has not been systematically studied, especially its characteristics in cancers. In this study, we provide a new algorithm, non-coding RNA target localization coefficient (ncTALENT), to quantify the target localization diversity of ncRNAs based on the ncRNA-protein interaction and protein subcellular localization data. ncTALENT can be used to calculate the target localization coefficient of ncRNAs and measure how diversely their targets are distributed among the subcellular locations in various scenarios. We focus our study on long non-coding RNAs (lncRNAs), and our observations reveal that the target localization diversity is a primary characteristic of lncRNAs in different biotypes. Moreover, we found that lncRNAs in multiple cancers, differentially expressed cancer lncRNAs, and lncRNAs with multiple cancer target proteins are prone to have high target localization diversity. Furthermore, the analysis of gastric cancer helps us to obtain a better understanding that the target localization diversity of lncRNAs is an important feature closely related to clinical prognosis. Overall, we systematically studied the target localization diversity of the lncRNAs and uncovered its association with cancer.
Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

PubMed

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Möller, Steffen; Hartmann, Enno; Kalies, Kai-Uwe; Suganthan, P N; Martinetz, Thomas

2010-12-01

Apoptosis is an essential process for controlling tissue homeostasis by regulating a physiological balance between cell proliferation and cell death. The subcellular locations of proteins performing the cell death are determined by mostly independent cellular mechanisms. The regular bioinformatics tools to predict the subcellular locations of such apoptotic proteins do often fail. This work proposes a model for the sorting of proteins that are involved in apoptosis, allowing us to both the prediction of their subcellular locations as well as the molecular properties that contributed to it. We report a novel hybrid Genetic Algorithm (GA)/Support Vector Machine (SVM) approach to predict apoptotic protein sequences using 119 sequence derived properties like frequency of amino acid groups, secondary structure, and physicochemical properties. GA is used for selecting a near-optimal subset of informative features that is most relevant for the classification. Jackknife cross-validation is applied to test the predictive capability of the proposed method on 317 apoptosis proteins. Our method achieved 85.80% accuracy using all 119 features and 89.91% accuracy for 25 features selected by GA. Our models were examined by a test dataset of 98 apoptosis proteins and obtained an overall accuracy of 90.34%. The results show that the proposed approach is promising; it is able to select small subsets of features and still improves the classification accuracy. Our model can contribute to the understanding of programmed cell death and drug discovery. The software and dataset are available at http://www.inb.uni-luebeck.de/tools-demos/apoptosis/GASVM.
Sequential Modulations in a Combined Horizontal and Vertical Simon Task: Is There ERP Evidence for Feature Integration Effects?

PubMed Central

Hoppe, Katharina; Küper, Kristina; Wascher, Edmund

2017-01-01

In the Simon task, participants respond faster when the task-irrelevant stimulus position and the response position are corresponding, for example on the same side, compared to when they have a non-corresponding relation. Interestingly, this Simon effect is reduced after non-corresponding trials. Such sequential effects can be explained in terms of a more focused processing of the relevant stimulus dimension due to increased cognitive control, which transfers from the previous non-corresponding trial (conflict adaptation effects). Alternatively, sequential modulations of the Simon effect can also be due to the degree of trial-to-trial repetitions and alternations of task features, which is confounded with the correspondence sequence (feature integration effects). In the present study, we used a spatially two-dimensional Simon task with vertical response keys to examine the contribution of adaptive cognitive control and feature integration processes to the sequential modulation of the Simon effect. The two-dimensional Simon task creates correspondences in the vertical as well as in the horizontal dimension. A trial-by-trial alternation of the spatial dimension, for example from a vertical to a horizontal stimulus presentation, generates a subset containing no complete repetitions of task features, but only complete alternations and partial repetitions, which are equally distributed over all correspondence sequences. In line with the assumed feature integration effects, we found sequential modulations of the Simon effect only when the spatial dimension repeated. At least for the horizontal dimension, this pattern was confirmed by the parietal P3b, an event-related potential that is assumed to reflect stimulus–response link processes. Contrary to conflict adaptation effects, cognitive control, measured by the fronto-central N2 component of the EEG, was not sequentially modulated. Overall, our data provide behavioral as well as electrophysiological evidence for feature integration effects contributing to sequential modulations of the Simon effect. PMID:28713305
Sequential Modulations in a Combined Horizontal and Vertical Simon Task: Is There ERP Evidence for Feature Integration Effects?

PubMed

Hoppe, Katharina; Küper, Kristina; Wascher, Edmund

2017-01-01

In the Simon task, participants respond faster when the task-irrelevant stimulus position and the response position are corresponding, for example on the same side, compared to when they have a non-corresponding relation. Interestingly, this Simon effect is reduced after non-corresponding trials. Such sequential effects can be explained in terms of a more focused processing of the relevant stimulus dimension due to increased cognitive control, which transfers from the previous non-corresponding trial (conflict adaptation effects). Alternatively, sequential modulations of the Simon effect can also be due to the degree of trial-to-trial repetitions and alternations of task features, which is confounded with the correspondence sequence (feature integration effects). In the present study, we used a spatially two-dimensional Simon task with vertical response keys to examine the contribution of adaptive cognitive control and feature integration processes to the sequential modulation of the Simon effect. The two-dimensional Simon task creates correspondences in the vertical as well as in the horizontal dimension. A trial-by-trial alternation of the spatial dimension, for example from a vertical to a horizontal stimulus presentation, generates a subset containing no complete repetitions of task features, but only complete alternations and partial repetitions, which are equally distributed over all correspondence sequences. In line with the assumed feature integration effects, we found sequential modulations of the Simon effect only when the spatial dimension repeated. At least for the horizontal dimension, this pattern was confirmed by the parietal P3b, an event-related potential that is assumed to reflect stimulus-response link processes. Contrary to conflict adaptation effects, cognitive control, measured by the fronto-central N2 component of the EEG, was not sequentially modulated. Overall, our data provide behavioral as well as electrophysiological evidence for feature integration effects contributing to sequential modulations of the Simon effect.
Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.
Proteome-wide Subcellular Topologies of E. coli Polypeptides Database (STEPdb)*

PubMed Central

Orfanoudaki, Georgia; Economou, Anastassios

2014-01-01

Cell compartmentalization serves both the isolation and the specialization of cell functions. After synthesis in the cytoplasm, over a third of all proteins are targeted to other subcellular compartments. Knowing how proteins are distributed within the cell and how they interact is a prerequisite for understanding it as a whole. Surface and secreted proteins are important pathogenicity determinants. Here we present the STEP database (STEPdb) that contains a comprehensive characterization of subcellular localization and topology of the complete proteome of Escherichia coli. Two widely used E. coli proteomes (K-12 and BL21) are presented organized into thirteen subcellular classes. STEPdb exploits the wealth of genetic, proteomic, biochemical, and functional information on protein localization, secretion, and targeting in E. coli, one of the best understood model organisms. Subcellular annotations were derived from a combination of bioinformatics prediction, proteomic, biochemical, functional, topological data and extensive literature re-examination that were refined through manual curation. Strong experimental support for the location of 1553 out of 4303 proteins was based on 426 articles and some experimental indications for another 526. Annotations were provided for another 320 proteins based on firm bioinformatic predictions. STEPdb is the first database that contains an extensive set of peripheral IM proteins (PIM proteins) and includes their graphical visualization into complexes, cellular functions, and interactions. It also summarizes all currently known protein export machineries of E. coli K-12 and pairs them, where available, with the secretory proteins that use them. It catalogs the Sec- and TAT-utilizing secretomes and summarizes their topological features such as signal peptides and transmembrane regions, transmembrane topologies and orientations. It also catalogs physicochemical and structural features that influence topology such as abundance, solubility, disorder, heat resistance, and structural domain families. Finally, STEPdb incorporates prediction tools for topology (TMHMM, SignalP, and Phobius) and disorder (IUPred) and implements the BLAST2STEP that performs protein homology searches against the STEPdb. PMID:25210196
Compensation of missing wedge effects with sequential statistical reconstruction in electron tomography.

PubMed

Paavolainen, Lassi; Acar, Erman; Tuna, Uygar; Peltonen, Sari; Moriya, Toshio; Soonsawad, Pan; Marjomäki, Varpu; Cheng, R Holland; Ruotsalainen, Ulla

2014-01-01

Electron tomography (ET) of biological samples is used to study the organization and the structure of the whole cell and subcellular complexes in great detail. However, projections cannot be acquired over full tilt angle range with biological samples in electron microscopy. ET image reconstruction can be considered an ill-posed problem because of this missing information. This results in artifacts, seen as the loss of three-dimensional (3D) resolution in the reconstructed images. The goal of this study was to achieve isotropic resolution with a statistical reconstruction method, sequential maximum a posteriori expectation maximization (sMAP-EM), using no prior morphological knowledge about the specimen. The missing wedge effects on sMAP-EM were examined with a synthetic cell phantom to assess the effects of noise. An experimental dataset of a multivesicular body was evaluated with a number of gold particles. An ellipsoid fitting based method was developed to realize the quantitative measures elongation and contrast in an automated, objective, and reliable way. The method statistically evaluates the sub-volumes containing gold particles randomly located in various parts of the whole volume, thus giving information about the robustness of the volume reconstruction. The quantitative results were also compared with reconstructions made with widely-used weighted backprojection and simultaneous iterative reconstruction technique methods. The results showed that the proposed sMAP-EM method significantly suppresses the effects of the missing information producing isotropic resolution. Furthermore, this method improves the contrast ratio, enhancing the applicability of further automatic and semi-automatic analysis. These improvements in ET reconstruction by sMAP-EM enable analysis of subcellular structures with higher three-dimensional resolution and contrast than conventional methods.
Euk-mPLoc: a fusion classifier for large-scale eukaryotic protein subcellular location prediction by incorporating multiple sites.

PubMed

Chou, Kuo-Chen; Shen, Hong-Bin

2007-05-01

One of the critical challenges in predicting protein subcellular localization is how to deal with the case of multiple location sites. Unfortunately, so far, no efforts have been made in this regard except for the one focused on the proteins in budding yeast only. For most existing predictors, the multiple-site proteins are either excluded from consideration or assumed even not existing. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. For instance, according to the Swiss-Prot database (version 50.7, released 19-Sept-2006), among the 33,925 eukaryotic protein entries that have experimentally observed subcellular location annotations, 2715 have multiple location sites, meaning about 8% bearing the multiplex feature. Proteins with multiple locations or dynamic feature of this kind are particularly interesting because they may have some very special biological functions intriguing to investigators in both basic research and drug discovery. Meanwhile, according to the same Swiss-Prot database, the number of total eukaryotic protein entries (except those annotated with "fragment" or those with less than 50 amino acids) is 90,909, meaning a gap of (90,909-33,925) = 56,984 entries for which no knowledge is available about their subcellular locations. Although one can use the computational approach to predict the desired information for the blank, so far, all the existing methods for predicting eukaryotic protein subcellular localization are limited in the case of single location site only. To overcome such a barrier, a new ensemble classifier, named Euk-mPLoc, was developed that can be used to deal with the case of multiple location sites as well. Euk-mPLoc is freely accessible to the public as a Web server at http://202.120.37.186/bioinf/euk-multi. Meanwhile, to support the people working in the relevant areas, Euk-mPLoc has been used to identify all eukaryotic protein entries in the Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The large-scale results thus obtained have been deposited at the same Web site via a downloadable file prepared with Microsoft Excel and named "Tab_Euk-mPLoc.xls". Furthermore, to include new entries of eukaryotic proteins and reflect the continuous development of Euk-mPLoc in both the coverage scope and prediction accuracy, we will timely update the downloadable file as well as the predictor, and keep users informed by publishing a short note in the Journal and making an announcement in the Web Page.

Learning Behavior Characterization with Multi-Feature, Hierarchical Activity Sequences

ERIC Educational Resources Information Center

Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam

2015-01-01

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…
Using the concept of Chou's pseudo amino acid composition to predict apoptosis proteins subcellular location: an approach by approximate entropy.

PubMed

Jiang, Xiaoying; Wei, Rong; Zhang, Tongliang; Gu, Quan

2008-01-01

The function of protein is closely correlated with it subcellular location. Prediction of subcellular location of apoptosis proteins is an important research area in post-genetic era because the knowledge of apoptosis proteins is useful to understand the mechanism of programmed cell death. Compared with the conventional amino acid composition (AAC), the Pseudo Amino Acid composition (PseAA) as originally introduced by Chou can incorporate much more information of a protein sequence so as to remarkably enhance the power of using a discrete model to predict various attributes of a protein. In this study, a novel approach is presented to predict apoptosis protein solely from sequence based on the concept of Chou's PseAA composition. The concept of approximate entropy (ApEn), which is a parameter denoting complexity of time series, is used to construct PseAA composition as additional features. Fuzzy K-nearest neighbor (FKNN) classifier is selected as prediction engine. Particle swarm optimization (PSO) algorithm is adopted for optimizing the weight factors which are important in PseAA composition. Two datasets are used to validate the performance of the proposed approach, which incorporate six subcellular location and four subcellular locations, respectively. The results obtained by jackknife test are quite encouraging. It indicates that the ApEn of protein sequence could represent effectively the information of apoptosis proteins subcellular locations. It can at least play a complimentary role to many of the existing methods, and might become potentially useful tool for protein function prediction. The software in Matlab is available freely by contacting the corresponding author.
Dynamic neuroanatomy at subcellular resolution in the zebrafish.

PubMed

Faucherre, Adèle; López-Schier, Hernán

2014-01-01

Genetic means to visualize and manipulate neuronal circuits in the intact animal have revolutionized neurobiology. "Dynamic neuroanatomy" defines a range of approaches aimed at quantifying the architecture or subcellular organization of neurons over time during their development, regeneration, or degeneration. A general feature of these approaches is their reliance on the optical isolation of defined neurons in toto by genetically expressing markers in one or few cells. Here we use the afferent neurons of the lateral line as an example to describe a simple method for the dynamic neuroanatomical study of axon terminals in the zebrafish by laser-scanning confocal microscopy.
SubCellProt: predicting protein subcellular localization using machine learning approaches.

PubMed

Garg, Prabha; Sharma, Virag; Chaudhari, Pradeep; Roy, Nilanjan

2009-01-01

High-throughput genome sequencing projects continue to churn out enormous amounts of raw sequence data. However, most of this raw sequence data is unannotated and, hence, not very useful. Among the various approaches to decipher the function of a protein, one is to determine its localization. Experimental approaches for proteome annotation including determination of a protein's subcellular localizations are very costly and labor intensive. Besides the available experimental methods, in silico methods present alternative approaches to accomplish this task. Here, we present two machine learning approaches for prediction of the subcellular localization of a protein from the primary sequence information. Two machine learning algorithms, k Nearest Neighbor (k-NN) and Probabilistic Neural Network (PNN) were used to classify an unknown protein into one of the 11 subcellular localizations. The final prediction is made on the basis of a consensus of the predictions made by two algorithms and a probability is assigned to it. The results indicate that the primary sequence derived features like amino acid composition, sequence order and physicochemical properties can be used to assign subcellular localization with a fair degree of accuracy. Moreover, with the enhanced accuracy of our approach and the definition of a prediction domain, this method can be used for proteome annotation in a high throughput manner. SubCellProt is available at www.databases.niper.ac.in/SubCellProt.
Protein subcellular localization prediction using artificial intelligence technology.

PubMed

Nair, Rajesh; Rost, Burkhard

2008-01-01

Proteins perform many important tasks in living organisms, such as catalysis of biochemical reactions, transport of nutrients, and recognition and transmission of signals. The plethora of aspects of the role of any particular protein is referred to as its "function." One aspect of protein function that has been the target of intensive research by computational biologists is its subcellular localization. Proteins must be localized in the same subcellular compartment to cooperate toward a common physiological function. Aberrant subcellular localization of proteins can result in several diseases, including kidney stones, cancer, and Alzheimer's disease. To date, sequence homology remains the most widely used method for inferring the function of a protein. However, the application of advanced artificial intelligence (AI)-based techniques in recent years has resulted in significant improvements in our ability to predict the subcellular localization of a protein. The prediction accuracy has risen steadily over the years, in large part due to the application of AI-based methods such as hidden Markov models (HMMs), neural networks (NNs), and support vector machines (SVMs), although the availability of larger experimental datasets has also played a role. Automatic methods that mine textual information from the biological literature and molecular biology databases have considerably sped up the process of annotation for proteins for which some information regarding function is available in the literature. State-of-the-art methods based on NNs and HMMs can predict the presence of N-terminal sorting signals extremely accurately. Ab initio methods that predict subcellular localization for any protein sequence using only the native amino acid sequence and features predicted from the native sequence have shown the most remarkable improvements. The prediction accuracy of these methods has increased by over 30% in the past decade. The accuracy of these methods is now on par with high-throughput methods for predicting localization, and they are beginning to play an important role in directing experimental research. In this chapter, we review some of the most important methods for the prediction of subcellular localization.
Integrated femtosecond stimulated Raman scattering and two-photon fluorescence imaging of subcellular lipid and vesicular structures

NASA Astrophysics Data System (ADS)

Li, Xuesong; Lam, Wen Jiun; Cao, Zhe; Hao, Yan; Sun, Qiqi; He, Sicong; Mak, Ho Yi; Qu, Jianan Y.

2015-11-01

The primary goal of this study is to demonstrate that stimulated Raman scattering (SRS) as a new imaging modality can be integrated into a femtosecond (fs) nonlinear optical (NLO) microscope system. The fs sources of high pulse peak power are routinely used in multimodal nonlinear microscopy to enable efficient excitation of multiple NLO signals. However, with fs excitations, the SRS imaging of subcellular lipid and vesicular structures encounters significant interference from proteins due to poor spectral resolution and a lack of chemical specificity, respectively. We developed a unique NLO microscope of fs excitation that enables rapid acquisition of SRS and multiple two-photon excited fluorescence (TPEF) signals. In the in vivo imaging of transgenic C. elegans animals, we discovered that by cross-filtering false positive lipid signals based on the TPEF signals from tryptophan-bearing endogenous proteins and lysosome-related organelles, the imaging system produced highly accurate assignment of SRS signals to lipid. Furthermore, we demonstrated that the multimodal NLO microscope system could sequentially image lipid structure/content and organelles, such as mitochondria, lysosomes, and the endoplasmic reticulum, which are intricately linked to lipid metabolism.
In-situ coupling between kinase activities and protein dynamics within single focal adhesions

NASA Astrophysics Data System (ADS)

Wu, Yiqian; Zhang, Kaiwen; Seong, Jihye; Fan, Jason; Chien, Shu; Wang, Yingxiao; Lu, Shaoying

2016-07-01

The dynamic activation of oncogenic kinases and regulation of focal adhesions (FAs) are crucial molecular events modulating cell adhesion in cancer metastasis. However, it remains unclear how these events are temporally coordinated at single FA sites. Therefore, we targeted fluorescence resonance energy transfer (FRET)-based biosensors toward subcellular FAs to report local molecular events during cancer cell adhesion. Employing single FA tracking and cross-correlation analysis, we quantified the dynamic coupling characteristics between biochemical kinase activities and structural FA within single FAs. We show that kinase activations and FA assembly are strongly and sequentially correlated, with the concurrent FA assembly and Src activation leading focal adhesion kinase (FAK) activation by 42.6 ± 12.6 sec. Strikingly, the temporal coupling between kinase activation and individual FA assembly reflects the fate of FAs at later stages. The FAs with a tight coupling tend to grow and mature, while the less coupled FAs likely disassemble. During FA disassembly, however, kinase activations lead the disassembly, with FAK being activated earlier than Src. Therefore, by integrating subcellularly targeted FRET biosensors and computational analysis, our study reveals intricate interplays between Src and FAK in regulating the dynamic life of single FAs in cancer cells.
Caveolae structure and function

PubMed Central

Thomas, Candice M; Smart, Eric J

2008-01-01

Abstract Studies on the structure and function of caveolae have revealed how this versatile subcellular organelle can influence numerous signalling pathways. This brief review will discuss a few of the key features of caveolae as it relates to signalling and disease processes. PMID:18315571
Extinction and Renewal of Pavlovian Modulation in Human Sequential Feature Positive Discrimination Learning

ERIC Educational Resources Information Center

Baeyens, Frank; Vansteenwegen, Debora; Beckers, Tom; Hermans, Dirk; Kerkhof, Ineke; De Ceulaer, Annick

2005-01-01

Using a conditioned suppression task, we investigated extinction and renewal of Pavlovian modulation in human sequential Feature Positive (FP) discrimination learning. In Experiment 1, in context a participants were first trained on two FP discriminations, X[right arrow]A+/A- and Y[right arrow]B+/B-. Extinction treatment was administered in the…
Simultaneous and Sequential Feature Negative Discriminations: Elemental Learning and Occasion Setting in Human Pavlovian Conditioning

ERIC Educational Resources Information Center

Baeyens, Frank; Vervliet, Bram; Vansteenwegen, Debora; Beckers, Tom; Hermans, Dirk; Eelen, Paul

2004-01-01

Using a conditioned suppression task, we investigated simultaneous (XA-/A+) vs. sequential (X [right arrow] A-/A+) Feature Negative (FN) discrimination learning in humans. We expected the simultaneous discrimination to result in X (or alternatively the XA configuration) becoming an inhibitor acting directly on the US, and the sequential…
iPHLoc-ES: Identification of bacteriophage protein locations using evolutionary and structural features.

PubMed

Shatabda, Swakkhar; Saha, Sanjay; Sharma, Alok; Dehzangi, Abdollah

2017-12-21

Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria and can be used in phage based therapy. The functioning of Bacteriophage in the host bacteria depends on its location in those host cells. It is very important to know the subcellular location of the phage proteins in a host cell in order to understand their working mechanism. In this paper, we propose iPHLoc-ES, a prediction method for subcellular localization of bacteriophage proteins. We aim to solve two problems: discriminating between host located and non-host located phage proteins and discriminating between the locations of host located protein in a host cell (membrane or cytoplasm). To do this, we extract sets of evolutionary and structural features of phage protein and employ Support Vector Machine (SVM) as our classifier. We also use recursive feature elimination (RFE) to reduce the number of features for effective prediction. On standard dataset using standard evaluation criteria, our method significantly outperforms the state-of-the-art predictor. iPHLoc-ES is readily available to use as a standalone tool from: https://github.com/swakkhar/iPHLoc-ES/ and as a web application from: http://brl.uiu.ac.bd/iPHLoc-ES/. Copyright © 2017 Elsevier Ltd. All rights reserved.
A novel approach to analyze lysosomal dysfunctions through subcellular proteomics and lipidomics: the case of NPC1 deficiency

NASA Astrophysics Data System (ADS)

Tharkeshwar, Arun Kumar; Trekker, Jesse; Vermeire, Wendy; Pauwels, Jarne; Sannerud, Ragna; Priestman, David A.; Te Vruchte, Danielle; Vints, Katlijn; Baatsen, Pieter; Decuypere, Jean-Paul; Lu, Huiqi; Martin, Shaun; Vangheluwe, Peter; Swinnen, Johannes V.; Lagae, Liesbet; Impens, Francis; Platt, Frances M.; Gevaert, Kris; Annaert, Wim

2017-01-01

Superparamagnetic iron oxide nanoparticles (SPIONs) have mainly been used as cellular carriers for genes and therapeutic products, while their use in subcellular organelle isolation remains underexploited. We engineered SPIONs targeting distinct subcellular compartments. Dimercaptosuccinic acid-coated SPIONs are internalized and accumulate in late endosomes/lysosomes, while aminolipid-SPIONs reside at the plasma membrane. These features allowed us to establish standardized magnetic isolation procedures for these membrane compartments with a yield and purity permitting proteomic and lipidomic profiling. We validated our approach by comparing the biomolecular compositions of lysosomes and plasma membranes isolated from wild-type and Niemann-Pick disease type C1 (NPC1) deficient cells. While the accumulation of cholesterol and glycosphingolipids is seen as a primary hallmark of NPC1 deficiency, our lipidomics analysis revealed the buildup of several species of glycerophospholipids and other storage lipids in selectively late endosomes/lysosomes of NPC1-KO cells. While the plasma membrane proteome remained largely invariable, we observed pronounced alterations in several proteins linked to autophagy and lysosomal catabolism reflecting vesicular transport obstruction and defective lysosomal turnover resulting from NPC1 deficiency. Thus the use of SPIONs provides a major advancement in fingerprinting subcellular compartments, with an increased potential to identify disease-related alterations in their biomolecular compositions.
Identification and Characterization of Cell Wall Proteins of a Toxic Dinoflagellate Alexandrium catenella Using 2-D DIGE and MALDI TOF-TOF Mass Spectrometry

PubMed Central

Wang, Da-Zhi; Dong, Hong-Po; Li, Cheng; Xie, Zhang-Xian; Lin, Lin; Hong, Hua-Sheng

2011-01-01

The cell wall is an important subcellular component of dinoflagellate cells with regard to various aspects of cell surface-associated ecophysiology, but the full range of cell wall proteins (CWPs) and their functions remain to be elucidated. This study identified and characterized CWPs of a toxic dinoflagellate, Alexandrium catenella, using a combination of 2D fluorescence difference gel electrophoresis (DIGE) and MALDI TOF-TOF mass spectrometry approaches. Using sequential extraction and temperature shock methods, sequentially extracted CWPs and protoplast proteins, respectively, were separated from A. catenella. From the comparison between sequentially extracted CWPs labeled with Cy3 and protoplast proteins labeled with Cy5, 120 CWPs were confidently identified in the 2D DIGE gel. These proteins gave positive identification of protein orthologues in the protein database using de novo sequence analysis and homology-based search. The majority of the prominent CWPs identified were hypothetical or putative proteins with unknown function or no annotation, while cell wall modification enzymes, cell wall structural proteins, transporter/binding proteins, and signaling and defense proteins were tentatively identified in agreement with the expected role of the extracellular matrix in cell physiology. This work represents the first attempt to investigate dinoflagellate CWPs and provides a potential tool for future comprehensive characterization of dinoflagellate CWPs and elucidation of their physiological functions. PMID:21904561
StruLocPred: structure-based protein subcellular localisation prediction using multi-class support vector machine.

PubMed

Zhou, Wengang; Dickerson, Julie A

2012-01-01

Knowledge of protein subcellular locations can help decipher a protein's biological function. This work proposes new features: sequence-based: Hybrid Amino Acid Pair (HAAP) and two structure-based: Secondary Structural Element Composition (SSEC) and solvent accessibility state frequency. A multi-class Support Vector Machine is developed to predict the locations. Testing on two established data sets yields better prediction accuracies than the best available systems. Comparisons with existing methods show comparable results to ESLPred2. When StruLocPred is applied to the entire Arabidopsis proteome, over 77% of proteins with known locations match the prediction results. An implementation of this system is at http://wgzhou.ece. iastate.edu/StruLocPred/.
mLASSO-Hum: A LASSO-based interpretable human-protein subcellular localization predictor.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2015-10-07

Knowing the subcellular compartments of human proteins is essential to shed light on the mechanisms of a broad range of human diseases. In computational methods for protein subcellular localization, knowledge-based methods (especially gene ontology (GO) based methods) are known to perform better than sequence-based methods. However, existing GO-based predictors often lack interpretability and suffer from overfitting due to the high dimensionality of feature vectors. To address these problems, this paper proposes an interpretable multi-label predictor, namely mLASSO-Hum, which can yield sparse and interpretable solutions for large-scale prediction of human protein subcellular localization. By using the one-vs-rest LASSO-based classifiers, 87 out of more than 8000 GO terms are found to play more significant roles in determining the subcellular localization. Based on these 87 essential GO terms, we can decide not only where a protein resides within a cell, but also why it is located there. To further exploit information from the remaining GO terms, a method based on the GO hierarchical information derived from the depth distance of GO terms is proposed. Experimental results show that mLASSO-Hum performs significantly better than state-of-the-art predictors. We also found that in addition to the GO terms from the cellular component category, GO terms from the other two categories also play important roles in the final classification decisions. For readers' convenience, the mLASSO-Hum server is available online at http://bioinfo.eie.polyu.edu.hk/mLASSOHumServer/. Copyright © 2015 Elsevier Ltd. All rights reserved.
Hum-mPLoc: an ensemble classifier for large-scale human protein subcellular location prediction by incorporating samples with multiple sites.

PubMed

Shen, Hong-Bin; Chou, Kuo-Chen

2007-04-20

Proteins may simultaneously exist at, or move between, two or more different subcellular locations. Proteins with multiple locations or dynamic feature of this kind are particularly interesting because they may have some very special biological functions intriguing to investigators in both basic research and drug discovery. For instance, among the 6408 human protein entries that have experimentally observed subcellular location annotations in the Swiss-Prot database (version 50.7, released 19-Sept-2006), 973 ( approximately 15%) have multiple location sites. The number of total human protein entries (except those annotated with "fragment" or those with less than 50 amino acids) in the same database is 14,370, meaning a gap of (14,370-6408)=7962 entries for which no knowledge is available about their subcellular locations. Although one can use the computational approach to predict the desired information for the gap, so far all the existing methods for predicting human protein subcellular localization are limited in the case of single location site only. To overcome such a barrier, a new ensemble classifier, named Hum-mPLoc, was developed that can be used to deal with the case of multiple location sites as well. Hum-mPLoc is freely accessible to the public as a web server at http://202.120.37.186/bioinf/hum-multi. Meanwhile, for the convenience of people working in the relevant areas, Hum-mPLoc has been used to identify all human protein entries in the Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The large-scale results thus obtained have been deposited in a downloadable file prepared with Microsoft Excel and named "Tab_Hum-mPLoc.xls". This file is available at the same website and will be updated twice a year to include new entries of human proteins and reflect the continuous development of Hum-mPLoc.
Feature Selection based on Machine Learning in MRIs for Hippocampal Segmentation

NASA Astrophysics Data System (ADS)

Tangaro, Sabina; Amoroso, Nicola; Brescia, Massimo; Cavuoti, Stefano; Chincarini, Andrea; Errico, Rosangela; Paolo, Inglese; Longo, Giuseppe; Maglietta, Rosalia; Tateo, Andrea; Riccio, Giuseppe; Bellotti, Roberto

2015-01-01

Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic resonance imaging (MRI) scans can show these variations and therefore can be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust, and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach; for each voxel a number of local features were calculated. In this paper, we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) sequential forward selection and (iii) sequential backward elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 feature for each voxel (sequential backward elimination) we obtained comparable state-of-the-art performances with respect to the standard tool FreeSurfer.
[Chromosomal proteins: histones and acid proteins].

PubMed

Salvini, M; Gabrielli, F

1976-01-01

Experimental data about the chemistry and the biology of chromosomal proteins are reviewed. Paragraphs include: aminoacid sequential data and post-translational covalent modications of histones, histone chemical differences in different tissues of the same species and in homologous organs of different species, histone synthesis subcellular localization and its association with DNA synthesis, histone synthesis transcriptional and translational control, histone synthesis during meiosis, oogenesis and early embryogenesis. The possible role of histones as controllers of gene expression is discussed and a model of primary structure of chromatine is proposed. The "acidic proteins" data concern the high tissue eterogenity of these proteins and their role in the steroid-hormon-controlled gene expression. The possible role of acidic proteins as general controllers of gene expression in eucariotic cells is discussed.
Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.

PubMed

He, Jianjun; Gu, Hong; Liu, Wenqi

2012-01-01

It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches.
The perceptual processing capacity of summary statistics between and within feature dimensions

PubMed Central

Attarha, Mouna; Moore, Cathleen M.

2015-01-01

The simultaneous–sequential method was used to test the processing capacity of statistical summary representations both within and between feature dimensions. Sixteen gratings varied with respect to their size and orientation. In Experiment 1, the gratings were equally divided into four separate smaller sets, one of which with a mean size that was larger or smaller than the other three sets, and one of which with a mean orientation that was tilted more leftward or rightward. The task was to report the mean size and orientation of the oddball sets. This therefore required four summary representations for size and another four for orientation. The sets were presented at the same time in the simultaneous condition or across two temporal frames in the sequential condition. Experiment 1 showed evidence of a sequential advantage, suggesting that the system may be limited with respect to establishing multiple within-feature summaries. Experiment 2 eliminates the possibility that some aspect of the task, other than averaging, was contributing to this observed limitation. In Experiment 3, the same 16 gratings appeared as one large superset, and therefore the task only required one summary representation for size and another one for orientation. Equal simultaneous–sequential performance indicated that between-feature summaries are capacity free. These findings challenge the view that within-feature summaries drive a global sense of visual continuity across areas of the peripheral visual field, and suggest a shift in focus to seeking an understanding of how between-feature summaries in one area of the environment control behavior. PMID:26360153

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

PubMed

Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-03-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein functions and how these functions were acquired in cells from different organisms or species. A public web interface of PLAST is available at http://plast.bii.a-star.edu.sg.
Quantitative Protein Localization Signatures Reveal an Association between Spatial and Functional Divergences of Proteins

PubMed Central

Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-01-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein functions and how these functions were acquired in cells from different organisms or species. A public web interface of PLAST is available at http://plast.bii.a-star.edu.sg. PMID:24603469
Novel Reporter for Faithful Monitoring of ERK2 Dynamics in Living Cells and Model Organisms

PubMed Central

Sipieter, François; Cappe, Benjamin; Gonzalez Pisfil, Mariano; Spriet, Corentin; Bodart, Jean-François; Cailliau-Maggio, Katia; Vandenabeele, Peter; Héliot, Laurent; Riquet, Franck B.

2015-01-01

Uncoupling of ERK1/2 phosphorylation from subcellular localization is essential towards the understanding of molecular mechanisms that control ERK1/2-mediated cell-fate decision. ERK1/2 non-catalytic functions and discoveries of new specific anchors responsible of the subcellular compartmentalization of ERK1/2 signaling pathway have been proposed as regulation mechanisms for which dynamic monitoring of ERK1/2 localization is necessary. However, studying the spatiotemporal features of ERK2, for instance, in different cellular processes in living cells and tissues requires a tool that can faithfully report on its subcellular distribution. We developed a novel molecular tool, ERK2-LOC, based on the T2A-mediated coexpression of strictly equimolar levels of eGFP-ERK2 and MEK1, to faithfully visualize ERK2 localization patterns. MEK1 and eGFP-ERK2 were expressed reliably and functionally both in vitro and in single living cells. We then assessed the subcellular distribution and mobility of ERK2-LOC using fluorescence microscopy in non-stimulated conditions and after activation/inhibition of the MAPK/ERK1/2 signaling pathway. Finally, we used our coexpression system in Xenopus laevis embryos during the early stages of development. This is the first report on MEK1/ERK2 T2A-mediated coexpression in living embryos, and we show that there is a strong correlation between the spatiotemporal subcellular distribution of ERK2-LOC and the phosphorylation patterns of ERK1/2. Our approach can be used to study the spatiotemporal localization of ERK2 and its dynamics in a variety of processes in living cells and embryonic tissues. PMID:26517832
Sequential feature selection for detecting buried objects using forward looking ground penetrating radar

NASA Astrophysics Data System (ADS)

Shaw, Darren; Stone, Kevin; Ho, K. C.; Keller, James M.; Luke, Robert H.; Burns, Brian P.

2016-05-01

Forward looking ground penetrating radar (FLGPR) has the benefit of detecting objects at a significant standoff distance. The FLGPR signal is radiated over a large surface area and the radar signal return is often weak. Improving detection, especially for buried in road targets, while maintaining an acceptable false alarm rate remains to be a challenging task. Various kinds of features have been developed over the years to increase the FLGPR detection performance. This paper focuses on investigating the use of as many features as possible for detecting buried targets and uses the sequential feature selection technique to automatically choose the features that contribute most for improving performance. Experimental results using data collected at a government test site are presented.
Sequential evolution of bacterial morphology by co-option of a developmental regulator.

PubMed

Jiang, Chao; Brown, Pamela J B; Ducret, Adrien; Brun, Yves V

2014-02-27

What mechanisms underlie the transitions responsible for the diverse shapes observed in the living world? Although bacteria exhibit a myriad of morphologies, the mechanisms responsible for the evolution of bacterial cell shape are not understood. We investigated morphological diversity in a group of bacteria that synthesize an appendage-like extension of the cell envelope called the stalk. The location and number of stalks varies among species, as exemplified by three distinct subcellular positions of stalks within a rod-shaped cell body: polar in the genus Caulobacter and subpolar or bilateral in the genus Asticcacaulis. Here we show that a developmental regulator of Caulobacter crescentus, SpmX, is co-opted in the genus Asticcacaulis to specify stalk synthesis either at the subpolar or bilateral positions. We also show that stepwise evolution of a specific region of SpmX led to the gain of a new function and localization of this protein, which drove the sequential transition in stalk positioning. Our results indicate that changes in protein function, co-option and modularity are key elements in the evolution of bacterial morphology. Therefore, similar evolutionary principles of morphological transitions apply to both single-celled prokaryotes and multicellular eukaryotes.
High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu-Chieh; Böhm, Konrad J; Tuckermann, Jan; Ploubidou, Aspasia

2016-07-01

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.
Analyzing multicomponent receptive fields from neural responses to natural stimuli

PubMed Central

Rowekamp, Ryan; Sharpee, Tatyana O

2011-01-01

The challenge of building increasingly better models of neural responses to natural stimuli is to accurately estimate the multiple stimulus features that may jointly affect the neural spike probability. The selectivity for combinations of features is thought to be crucial for achieving classical properties of neural responses such as contrast invariance. The joint search for these multiple stimulus features is difficult because estimating spike probability as a multidimensional function of stimulus projections onto candidate relevant dimensions is subject to the curse of dimensionality. An attractive alternative is to search for relevant dimensions sequentially, as in projection pursuit regression. Here we demonstrate using analytic arguments and simulations of model cells that different types of sequential search strategies exhibit systematic biases when used with natural stimuli. Simulations show that joint optimization is feasible for up to three dimensions with current algorithms. When applied to the responses of V1 neurons to natural scenes, models based on three jointly optimized dimensions had better predictive power in a majority of cases compared to dimensions optimized sequentially, with different sequential methods yielding comparable results. Thus, although the curse of dimensionality remains, at least several relevant dimensions can be estimated by joint information maximization. PMID:21780916
Sequential fuzzy diagnosis method for motor roller bearing in variable operating conditions based on vibration analysis.

PubMed

Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi

2013-06-21

A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well.
Sequential Fuzzy Diagnosis Method for Motor Roller Bearing in Variable Operating Conditions Based on Vibration Analysis

PubMed Central

Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi

2013-01-01

A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well. PMID:23793021
UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection

PubMed Central

Sadeque, Farig; Xu, Dongfang; Bethard, Steven

2017-01-01

The 2017 CLEF eRisk pilot task focuses on automatically detecting depression as early as possible from a users’ posts to Reddit. In this paper we present the techniques employed for the University of Arizona team’s participation in this early risk detection shared task. We leveraged external information beyond the small training set, including a preexisting depression lexicon and concepts from the Unified Medical Language System as features. For prediction, we used both sequential (recurrent neural network) and non-sequential (support vector machine) models. Our models perform decently on the test data, and the recurrent neural models perform better than the non-sequential support vector machines while using the same feature sets. PMID:29075167
Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration

PubMed Central

Luan, Lan; Wei, Xiaoling; Zhao, Zhengtuo; Siegel, Jennifer J.; Potnis, Ojas; Tuppen, Catherine A; Lin, Shengqing; Kazmi, Shams; Fowler, Robert A.; Holloway, Stewart; Dunn, Andrew K.; Chitwood, Raymond A.; Xie, Chong

2017-01-01

Implanted brain electrodes construct the only means to electrically interface with individual neurons in vivo, but their recording efficacy and biocompatibility pose limitations on scientific and clinical applications. We showed that nanoelectronic thread (NET) electrodes with subcellular dimensions, ultraflexibility, and cellular surgical footprints form reliable, glial scar–free neural integration. We demonstrated that NET electrodes reliably detected and tracked individual units for months; their impedance, noise level, single-unit recording yield, and the signal amplitude remained stable during long-term implantation. In vivo two-photon imaging and postmortem histological analysis revealed seamless, subcellular integration of NET probes with the local cellular and vasculature networks, featuring fully recovered capillaries with an intact blood-brain barrier and complete absence of chronic neuronal degradation and glial scar. PMID:28246640
Extraction protocol and liquid chromatography/tandem mass spectrometry method for determining micelle-entrapped paclitaxel at the cellular and subcellular levels: Application to a cellular uptake and distribution study.

PubMed

Zheng, Nan; Lian, Bin; Du, Wenwen; Xu, Guobing; Ji, Jiafu

2018-01-01

Paclitaxel-loaded polymeric micelles (PTX-PM) are commonly used as tumor-targeted nanocarriers and display outstanding antitumor features in clinic, but its accumulation and distribution in vitro are lack of investigation. It is probably due to the complex micellar system and its low concentration at the cellular or subcellular levels. In this study, we developed an improved extraction method, which was a combination of mechanical disruption and liquid-liquid extraction (LLE), to extract the total PTX from micelles in the cell lysate and subcellular compartments. An ultra-performance liquid chromatography tandem mass spectroscopy (UPLC-MS/MS) method was optimized to detect the low concentration of PTX at cellular and subcellular levels simultaneously, using docetaxel as internal standard (IS). The method was proved to release PTX totally from micelles (≥95.93%) with a consistent and reproducible extraction recovery (≥75.04%). Good linearity was obtained at concentrations ranging from 0.2 to 20ng/mL. The relative error (RE%) for accuracy varied from 0.68 to 7.56%, and the intra- and inter-precision (relative standard deviation, RSD%) was less than 8.64% and 13.14%, respectively. This method was fully validated and successfully applied to the cellular uptake and distribution study of PTX-loaded PLGA-PEG micelles in human breast cancer cells (MCF-7). Copyright © 2017 Elsevier B.V. All rights reserved.
Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.
Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.
Classification of epileptic EEG signals based on simple random sampling and sequential feature selection.

PubMed

Ghayab, Hadi Ratham Al; Li, Yan; Abdulla, Shahab; Diykh, Mohammed; Wan, Xiangkui

2016-06-01

Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on. This paper presents a new method which extracts and selects features from multi-channel EEG signals. This research focuses on three main points. Firstly, simple random sampling (SRS) technique is used to extract features from the time domain of EEG signals. Secondly, the sequential feature selection (SFS) algorithm is applied to select the key features and to reduce the dimensionality of the data. Finally, the selected features are forwarded to a least square support vector machine (LS_SVM) classifier to classify the EEG signals. The LS_SVM classifier classified the features which are extracted and selected from the SRS and the SFS. The experimental results show that the method achieves 99.90, 99.80 and 100 % for classification accuracy, sensitivity and specificity, respectively.
Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells.

PubMed

Shen, Hong-Bin; Chou, Kuo-Chen

2007-02-15

Viruses can reproduce their progenies only within a host cell, and their actions depend both on its destructive tendencies toward a specific host cell and on environmental conditions. Therefore, knowledge of the subcellular localization of viral proteins in a host cell or virus-infected cell is very useful for in-depth studying of their functions and mechanisms as well as designing antiviral drugs. An analysis on the Swiss-Prot database (version 50.0, released on May 30, 2006) indicates that only 23.5% of viral protein entries are annotated for their subcellular locations in this regard. As for the gene ontology database, the corresponding percentage is 23.8%. Such a gap calls for the development of high throughput tools for timely annotating the localization of viral proteins within host and virus-infected cells. In this article, a predictor called "Virus-PLoc" has been developed that is featured by fusing many basic classifiers with each engineered according to the K-nearest neighbor rule. The overall jackknife success rate obtained by Virus-PLoc in identifying the subcellular compartments of viral proteins was 80% for a benchmark dataset in which none of proteins has more than 25% sequence identity to any other in a same location site. Virus-PLoc will be freely available as a web-server at http://202.120.37.186/bioinf/virus for the public usage. Furthermore, Virus-PLoc has been used to provide large-scale predictions of all viral protein entries in Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The results thus obtained have been deposited in a downloadable file prepared with Microsoft Excel and named "Tab_Virus-PLoc.xls." This file is available at the same website and will be updated twice a year to include the new entries of viral proteins and reflect the continuous development of Virus-PLoc. 2006 Wiley Periodicals, Inc.
Analysis and Synthesis of Adaptive Neural Elements and Assembles

DTIC Science & Technology

1993-09-30

of an Aplysia sensory neuron was developed that reflects the subcellular processes underlying activity-dependent neuromodulation . This single- Page -3... neuromodulation learning rule could simulate some higher-order features of classical conditioning, such second-order conditioning and blocking. During the...reporting period, simulations were used to test the hypothesis that activity-dependent neuromodulation could also support operant conditioning. A
Association of mammographic image feature change and an increasing risk trend of developing breast cancer: an assessment

NASA Astrophysics Data System (ADS)

Tan, Maxine; Leader, Joseph K.; Liu, Hong; Zheng, Bin

2015-03-01

We recently investigated a new mammographic image feature based risk factor to predict near-term breast cancer risk after a woman has a negative mammographic screening. We hypothesized that unlike the conventional epidemiology-based long-term (or lifetime) risk factors, the mammographic image feature based risk factor value will increase as the time lag between the negative and positive mammography screening decreases. The purpose of this study is to test this hypothesis. From a large and diverse full-field digital mammography (FFDM) image database with 1278 cases, we collected all available sequential FFDM examinations for each case including the "current" and 1 to 3 most recently "prior" examinations. All "prior" examinations were interpreted negative, and "current" ones were either malignant or recalled negative/benign. We computed 92 global mammographic texture and density based features, and included three clinical risk factors (woman's age, family history and subjective breast density BIRADS ratings). On this initial feature set, we applied a fast and accurate Sequential Forward Floating Selection (SFFS) feature selection algorithm to reduce feature dimensionality. The features computed on both mammographic views were individually/ separately trained using two artificial neural network (ANN) classifiers. The classification scores of the two ANNs were then merged with a sequential ANN. The results show that the maximum adjusted odds ratios were 5.59, 7.98, and 15.77 for using the 3rd, 2nd, and 1st "prior" FFDM examinations, respectively, which demonstrates a higher association of mammographic image feature change and an increasing risk trend of developing breast cancer in the near-term after a negative screening.
Stationary Anonymous Sequential Games with Undiscounted Rewards.

PubMed

Więcek, Piotr; Altman, Eitan

Stationary anonymous sequential games with undiscounted rewards are a special class of games that combine features from both population games (infinitely many players) with stochastic games. We extend the theory for these games to the cases of total expected reward as well as to the expected average reward. We show that in the anonymous sequential game equilibria correspond to the limits of those of related finite population games as the number of players grows to infinity. We provide examples to illustrate our results.
Sheet-scanned dual-axis confocal microscopy using Richardson-Lucy deconvolution.

PubMed

Wang, D; Meza, D; Wang, Y; Gao, L; Liu, J T C

2014-09-15

We have previously developed a line-scanned dual-axis confocal (LS-DAC) microscope with subcellular resolution suitable for high-frame-rate diagnostic imaging at shallow depths. Due to the loss of confocality along one dimension, the contrast (signal-to-background ratio) of a LS-DAC microscope is deteriorated compared to a point-scanned DAC microscope. However, by using a sCMOS camera for detection, a short oblique light-sheet is imaged at each scanned position. Therefore, by scanning the light sheet in only one dimension, a thin 3D volume is imaged. Both sequential two-dimensional deconvolution and three-dimensional deconvolution are performed on the thin image volume to improve the resolution and contrast of one en face confocal image section at the center of the volume, a technique we call sheet-scanned dual-axis confocal (SS-DAC) microscopy.

One-Pot/Sequential Native Chemical Ligation Using Photocaged Crypto-thioester.

PubMed

Aihara, Keisuke; Yamaoka, Kosuke; Naruse, Naoto; Inokuma, Tsubasa; Shigenaga, Akira; Otaka, Akira

2016-02-05

A practical and efficient methodology for the chemical synthesis of peptides/proteins using a one-pot/sequential ligation is described. It features the use of photocleavable S-protection on an N-sulfanylethylaniline moiety. Removal of the S-protecting ligated materials under UV irradiation provides a readily usable mixture for subsequent native chemical ligation.
Real time on-chip sequential adaptive principal component analysis for data feature extraction and image compression

NASA Technical Reports Server (NTRS)

Duong, T. A.

2004-01-01

In this paper, we present a new, simple, and optimized hardware architecture sequential learning technique for adaptive Principle Component Analysis (PCA) which will help optimize the hardware implementation in VLSI and to overcome the difficulties of the traditional gradient descent in learning convergence and hardware implementation.
Three-dimensional Organization of Layered Apical Cytoskeletal Networks Associated with Mouse Airway Tissue Development

NASA Astrophysics Data System (ADS)

Tateishi, Kazuhiro; Nishida, Tomoki; Inoue, Kanako; Tsukita, Sachiko

2017-03-01

The cytoskeleton is an essential cellular component that enables various sophisticated functions of epithelial cells by forming specialized subcellular compartments. However, the functional and structural roles of cytoskeletons in subcellular compartmentalization are still not fully understood. Here we identified a novel network structure consisting of actin filaments, intermediate filaments, and microtubules directly beneath the apical membrane in mouse airway multiciliated cells and in cultured epithelial cells. Three-dimensional imaging by ultra-high voltage electron microscopy and immunofluorescence revealed that the morphological features of each network depended on the cell type and were spatiotemporally integrated in association with tissue development. Detailed analyses using Odf2 mutant mice, which lack ciliary basal feet and apical microtubules, suggested a novel contribution of the intermediate filaments to coordinated ciliary beating. These findings provide a new perspective for viewing epithelial cell differentiation and tissue morphogenesis through the structure and function of apical cytoskeletal networks.
Measurement of subcellular texture by optical Gabor-like filtering with a digital micromirror device

PubMed Central

Pasternack, Robert M.; Qian, Zhen; Zheng, Jing-Yi; Metaxas, Dimitris N.; White, Eileen; Boustany, Nada N.

2010-01-01

We demonstrate an optical Fourier processing method to quantify object texture arising from subcellular feature orientation within unstained living cells. Using a digital micromirror device as a Fourier spatial filter, we measured cellular responses to two-dimensional optical Gabor-like filters optimized to sense orientation of nonspherical particles, such as mitochondria, with a width around 0.45 μm. Our method showed significantly rounder structures within apoptosis-defective cells lacking the proapoptotic mitochondrial effectors Bax and Bak, when compared with Bax/Bak expressing cells functional for apoptosis, consistent with reported differences in mitochondrial shape in these cells. By decoupling spatial frequency resolution from image resolution, this method enables rapid analysis of nonspherical submicrometer scatterers in an under-sampled large field of view and yields spatially localized morphometric parameters that improve the quantitative assessment of biological function. PMID:18830354
Multi-scale Imaging of Cellular and Sub-cellular Structures using Scanning Probe Recognition Microscopy.

NASA Astrophysics Data System (ADS)

Chen, Q.; Rice, A. F.

2005-03-01

Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).
Plant subcellular proteomics: Application for exploring optimal cell function in soybean.

PubMed

Wang, Xin; Komatsu, Setsuko

2016-06-30

Plants have evolved complicated responses to developmental changes and stressful environmental conditions. Subcellular proteomics has the potential to elucidate localized cellular responses and investigate communications among subcellular compartments during plant development and in response to biotic and abiotic stresses. Soybean, which is a valuable legume crop rich in protein and vegetable oil, can grow in several climatic zones; however, the growth and yield of soybean are markedly decreased under stresses. To date, numerous proteomic studies have been performed in soybean to examine the specific protein profiles of cell wall, plasma membrane, nucleus, mitochondrion, chloroplast, and endoplasmic reticulum. In this review, methods for the purification and purity assessment of subcellular organelles from soybean are summarized. In addition, the findings from subcellular proteomic analyses of soybean during development and under stresses, particularly flooding stress, are presented and the proteins regulated among subcellular compartments are discussed. Continued advances in subcellular proteomics are expected to greatly contribute to the understanding of the responses and interactions that occur within and among subcellular compartments during development and under stressful environmental conditions. Subcellular proteomics has the potential to investigate the cellular events and interactions among subcellular compartments in response to development and stresses in plants. Soybean could grow in several climatic zones; however, the growth and yield of soybean are markedly decreased under stresses. Numerous proteomics of cell wall, plasma membrane, nucleus, mitochondrion, chloroplast, and endoplasmic reticulum was carried out to investigate the respecting proteins and their functions in soybean during development or under stresses. In this review, methods of subcellular-organelle enrichment and purity assessment are summarized. In addition, previous findings of subcellular proteomics are presented, and functional proteins regulated among different subcellular are discussed. Subcellular proteomics contributes greatly to uncovering responses and interactions among subcellular compartments during development and under stressful environmental conditions in soybean. Copyright © 2016 Elsevier B.V. All rights reserved.
Subcellular Localization Screening of Colletotrichum higginsianum Effector Candidates Identifies Fungal Proteins Targeted to Plant Peroxisomes, Golgi Bodies, and Microtubules.

PubMed

Robin, Guillaume P; Kleemann, Jochen; Neumann, Ulla; Cabre, Lisa; Dallery, Jean-Félix; Lapalu, Nicolas; O'Connell, Richard J

2018-01-01

The genome of the hemibiotrophic anthracnose fungus, Colletotrichum higginsianum , encodes a large inventory of putative secreted effector proteins that are sequentially expressed at different stages of plant infection, namely appressorium-mediated penetration, biotrophy and necrotrophy. However, the destinations to which these proteins are addressed inside plant cells are unknown. In the present study, we selected 61 putative effector genes that are highly induced in appressoria and/or biotrophic hyphae. We then used Agrobacterium -mediated transformation to transiently express them as N -terminal fusions with fluorescent proteins in cells of Nicotiana benthamiana for imaging by confocal microscopy. Plant compartments labeled by the fusion proteins in N. benthamiana were validated by co-localization with specific organelle markers, by transient expression of the proteins in the true host plant, Arabidopsis thaliana , and by transmission electron microscopy-immunogold labeling. Among those proteins for which specific subcellular localizations could be verified, nine were imported into plant nuclei, three were imported into the matrix of peroxisomes, three decorated cortical microtubule arrays and one labeled Golgi stacks. Two peroxisome-targeted proteins harbored canonical C -terminal tripeptide signals for peroxisome import via the PTS1 (peroxisomal targeting signal 1) pathway, and we showed that these signals are essential for their peroxisome localization. Our findings provide valuable information about which host processes are potentially manipulated by this pathogen, and also reveal plant peroxisomes, microtubules, and Golgi as novel targets for fungal effectors.
A Pocock Approach to Sequential Meta-Analysis of Clinical Trials

ERIC Educational Resources Information Center

Shuster, Jonathan J.; Neu, Josef

2013-01-01

Three recent papers have provided sequential methods for meta-analysis of two-treatment randomized clinical trials. This paper provides an alternate approach that has three desirable features. First, when carried out prospectively (i.e., we only have the results up to the time of our current analysis), we do not require knowledge of the…
Extending the Simultaneous-Sequential Paradigm to Measure Perceptual Capacity for Features and Words

ERIC Educational Resources Information Center

Scharff, Alec; Palmer, John; Moore, Cathleen M.

2011-01-01

In perception, divided attention refers to conditions in which multiple stimuli are relevant to an observer. To measure the effect of divided attention in terms of perceptual capacity, we introduce an extension of the simultaneous-sequential paradigm. The extension makes predictions for fixed-capacity models as well as for unlimited-capacity…
The Role of Semantic Transfer in Clitic Drop among Simultaneous and Sequential Chinese-Spanish Bilinguals

ERIC Educational Resources Information Center

Cuza, Alejandro; Perez-Leroux, Ana Teresa; Sanchez, Liliana

2013-01-01

This study examines the acquisition of the featural constraints on clitic and null distribution in Spanish among simultaneous and sequential Chinese-Spanish bilinguals from Peru. A truth value judgment task targeted the referential meaning of null objects in a negation context. Objects were elicited via two clitic elicitation tasks that targeted…
Trial-to-Trial Modulations of the Simon Effect in Conditions of Attentional Limitations : Evidence from Dual Tasks

ERIC Educational Resources Information Center

Fischer, Rico; Plessow, Franziska; Kunde, Wilfried; Kiesel, Andrea

2010-01-01

Interference effects are reduced after trials including response conflict. This sequential modulation has often been attributed to a top-down mediated adaptive control mechanism and/or to feature repetition mechanisms. In the present study we tested whether mechanisms responsible for such sequential modulations are subject to attentional…
Gold-catalyzed sequential annulations towards 3,4-fused bi/tri-cyclic furans involving a [3+2+2]-cycloaddition.

PubMed

Liu, Suna; Yang, Pu; Peng, Shiyong; Zhu, Chenghao; Cao, Shengyu; Li, Jian; Sun, Jiangtao

2017-01-17

A gold-catalyzed sequential annulation reaction to prepare 3,4-fused bicyclic furan compounds has been realized by employing 2-(1-alkynyl)-2-alken-1-ones and 1,3,5-triazines as the starting materials under mild reaction conditions. This protocol features multiple bond formation in a single operation with the incorporation of two nitrogen and two carbon atoms into the final products. A mechanistic investigation reveals that the sequential annulations involved an unprecedented stepwise [3+2+2]-cycloaddition.
Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition.

PubMed

Tamura, Takeyuki; Akutsu, Tatsuya

2007-11-30

Subcellular location prediction of proteins is an important and well-studied problem in bioinformatics. This is a problem of predicting which part in a cell a given protein is transported to, where an amino acid sequence of the protein is given as an input. This problem is becoming more important since information on subcellular location is helpful for annotation of proteins and genes and the number of complete genomes is rapidly increasing. Since existing predictors are based on various heuristics, it is important to develop a simple method with high prediction accuracies. In this paper, we propose a novel and general predicting method by combining techniques for sequence alignment and feature vectors based on amino acid composition. We implemented this method with support vector machines on plant data sets extracted from the TargetP database. Through fivefold cross validation tests, the obtained overall accuracies and average MCC were 0.9096 and 0.8655 respectively. We also applied our method to other datasets including that of WoLF PSORT. Although there is a predictor which uses the information of gene ontology and yields higher accuracy than ours, our accuracies are higher than existing predictors which use only sequence information. Since such information as gene ontology can be obtained only for known proteins, our predictor is considered to be useful for subcellular location prediction of newly-discovered proteins. Furthermore, the idea of combination of alignment and amino acid frequency is novel and general so that it may be applied to other problems in bioinformatics. Our method for plant is also implemented as a web-system and available on http://sunflower.kuicr.kyoto-u.ac.jp/~tamura/slpfa.html.
Live imaging of companion cells and sieve elements in Arabidopsis leaves.

PubMed

Cayla, Thibaud; Batailler, Brigitte; Le Hir, Rozenn; Revers, Frédéric; Anstead, James A; Thompson, Gary A; Grandjean, Olivier; Dinant, Sylvie

2015-01-01

The phloem is a complex tissue composed of highly specialized cells with unique subcellular structures and a compact organization that is challenging to study in vivo at cellular resolution. We used confocal scanning laser microscopy and subcellular fluorescent markers in companion cells and sieve elements, for live imaging of the phloem in Arabidopsis leaves. This approach provided a simple framework for identifying phloem cell types unambiguously. It highlighted the compactness of the meshed network of organelles within companion cells. By contrast, within the sieve elements, unknown bodies were observed in association with the PP2-A1:GFP, GFP:RTM1 and RTM2:GFP markers at the cell periphery. The phloem lectin PP2-A1:GFP marker was found in the parietal ground matrix. Its location differed from that of the P-protein filaments, which were visualized with SEOR1:GFP and SEOR2:GFP. PP2-A1:GFP surrounded two types of bodies, one of which was identified as mitochondria. This location suggested that it was embedded within the sieve element clamps, specific structures that may fix the organelles to each another or to the plasma membrane in the sieve tubes. GFP:RTM1 was associated with a class of larger bodies, potentially corresponding to plastids. PP2-A1:GFP was soluble in the cytosol of immature sieve elements. The changes in its subcellular localization during differentiation provide an in vivo blueprint for monitoring this process. The subcellular features obtained with these companion cell and sieve element markers can be used as landmarks for exploring the organization and dynamics of phloem cells in vivo.
Imaging cellular and subcellular structure of human brain tissue using micro computed tomography

NASA Astrophysics Data System (ADS)

Khimchenko, Anna; Bikis, Christos; Schweighauser, Gabriel; Hench, Jürgen; Joita-Pacureanu, Alexandra-Teodora; Thalmann, Peter; Deyhle, Hans; Osmani, Bekim; Chicherova, Natalia; Hieber, Simone E.; Cloetens, Peter; Müller-Gerbl, Magdalena; Schulz, Georg; Müller, Bert

2017-09-01

Brain tissues have been an attractive subject for investigations in neuropathology, neuroscience, and neurobiol- ogy. Nevertheless, existing imaging methodologies have intrinsic limitations in three-dimensional (3D) label-free visualisation of extended tissue samples down to (sub)cellular level. For a long time, these morphological features were visualised by electron or light microscopies. In addition to being time-consuming, microscopic investigation includes specimen fixation, embedding, sectioning, staining, and imaging with the associated artefacts. More- over, optical microscopy remains hampered by a fundamental limit in the spatial resolution that is imposed by the diffraction of visible light wavefront. In contrast, various tomography approaches do not require a complex specimen preparation and can now reach a true (sub)cellular resolution. Even laboratory-based micro computed tomography in the absorption-contrast mode of formalin-fixed paraffin-embedded (FFPE) human cerebellum yields an image contrast comparable to conventional histological sections. Data of a superior image quality was obtained by means of synchrotron radiation-based single-distance X-ray phase-contrast tomography enabling the visualisation of non-stained Purkinje cells down to the subcellular level and automated cell counting. The question arises, whether the data quality of the hard X-ray tomography can be superior to optical microscopy. Herein, we discuss the label-free investigation of the human brain ultramorphology be means of synchrotron radiation-based hard X-ray magnified phase-contrast in-line tomography at the nano-imaging beamline ID16A (ESRF, Grenoble, France). As an example, we present images of FFPE human cerebellum block. Hard X-ray tomography can provide detailed information on human tissues in health and disease with a spatial resolution below the optical limit, improving understanding of the neuro-degenerative diseases.
Live Imaging of Companion Cells and Sieve Elements in Arabidopsis Leaves

PubMed Central

Cayla, Thibaud; Batailler, Brigitte; Le Hir, Rozenn; Revers, Frédéric; Anstead, James A.; Thompson, Gary A.; Grandjean, Olivier; Dinant, Sylvie

2015-01-01

The phloem is a complex tissue composed of highly specialized cells with unique subcellular structures and a compact organization that is challenging to study in vivo at cellular resolution. We used confocal scanning laser microscopy and subcellular fluorescent markers in companion cells and sieve elements, for live imaging of the phloem in Arabidopsis leaves. This approach provided a simple framework for identifying phloem cell types unambiguously. It highlighted the compactness of the meshed network of organelles within companion cells. By contrast, within the sieve elements, unknown bodies were observed in association with the PP2-A1:GFP, GFP:RTM1 and RTM2:GFP markers at the cell periphery. The phloem lectin PP2-A1:GFP marker was found in the parietal ground matrix. Its location differed from that of the P-protein filaments, which were visualized with SEOR1:GFP and SEOR2:GFP. PP2-A1:GFP surrounded two types of bodies, one of which was identified as mitochondria. This location suggested that it was embedded within the sieve element clamps, specific structures that may fix the organelles to each another or to the plasma membrane in the sieve tubes. GFP:RTM1 was associated with a class of larger bodies, potentially corresponding to plastids. PP2-A1:GFP was soluble in the cytosol of immature sieve elements. The changes in its subcellular localization during differentiation provide an in vivo blueprint for monitoring this process. The subcellular features obtained with these companion cell and sieve element markers can be used as landmarks for exploring the organization and dynamics of phloem cells in vivo. PMID:25714357
Conflict Background Triggered Congruency Sequence Effects in Graphic Judgment Task

PubMed Central

Zhao, Liang; Wang, Yonghui

2013-01-01

Congruency sequence effects refer to the reduction of congruency effects when following an incongruent trial than following a congruent trial. The conflict monitoring account, one of the most influential contributions to this effect, assumes that the sequential modulations are evoked by response conflict. The present study aimed at exploring the congruency sequence effects in the absence of response conflict. We found congruency sequence effects occurred in graphic judgment task, in which the conflict stimuli acted as irrelevant information. The findings reveal that processing task-irrelevant conflict stimulus features could also induce sequential modulations of interference. The results do not support the interpretation of conflict monitoring and favor a feature integration account that the congruency sequence effects are attributed to the repetitions of stimulus and response features. PMID:23372766
EnLightenment: High resolution smartphone microscopy as an educational and public engagement platform.

PubMed

Wicks, Laura C; Cairns, Gemma S; Melnyk, Jacob; Bryce, Scott; Duncan, Rory R; Dalgarno, Paul A

2017-01-01

We developed a simple, cost-effective smartphone microscopy platform for use in educational and public engagement programs. We demonstrated its effectiveness, and potential for citizen science through a national imaging initiative, EnLightenment . The cost effectiveness of the instrument allowed for the program to deliver over 500 microscopes to more than 100 secondary schools throughout Scotland, targeting 1000's of 12-14 year olds. Through careful, quantified, selection of a high power, low-cost objective lens, our smartphone microscope has an imaging resolution of microns, with a working distance of 3 mm. It is therefore capable of imaging single cells and sub-cellular features, and retains usability for young children. The microscopes were designed in kit form and provided an interdisciplinary educational tool. By providing full lesson plans and support material, we developed a framework to explore optical design, microscope performance, engineering challenges on construction and real-world applications in life sciences, biological imaging, marine biology, art, and technology. A national online imaging competition framed EnLightenment ; with over 500 high quality images submitted of diverse content, spanning multiple disciplines. With examples of cellular and sub-cellular features clearly identifiable in some submissions, we show how young public can use these instruments for research-level imaging applications, and the potential of the instrument for citizen science programs.
Subcellular preservation in giant ostracod sperm from an early Miocene cave deposit in Australia

PubMed Central

Matzke-Karasz, Renate; Neil, John V.; Smith, Robin J.; Symonová, Radka; Mořkovský, Libor; Archer, Michael; Hand, Suzanne J.; Cloetens, Peter; Tafforeau, Paul

2014-01-01

Cypridoidean ostracods are one of a number of animal taxa that reproduce with giant sperm, up to 10 000 µm in length, but they are the only group to have aflagellate, filamentous giant sperm. The evolution and function of this highly unusual feature of reproduction with giant sperm are currently unknown. The hypothesis of long-term evolutionary persistence of this kind of reproduction has never been tested. We here report giant sperm discovered by propagation phase contrast X-ray synchrotron micro- and nanotomography, preserved in five Miocene ostracod specimens from Queensland, Australia. The specimens belong to the species Heterocypris collaris Matzke-Karasz et al. 2013 (one male and three females) and Newnhamia mckenziana Matzke-Karasz et al. 2013 (one female). The sperm are not only the oldest petrified gametes on record, but include three-dimensional subcellular preservation. We provide direct evidence that giant sperm have been a feature of this taxon for at least 16 Myr and provide an additional criterion (i.e. longevity) to test hypotheses relating to origin and function of giant sperm in the animal kingdom. We further argue that the highly resistant, most probably chitinous coats of giant ostracod sperm may play a role in delaying decay processes, favouring early mineralization of soft tissue. PMID:24827442
The bandwidth of consolidation into visual short-term memory (VSTM) depends on the visual feature

PubMed Central

Miller, James R.; Becker, Mark W.; Liu, Taosheng

2014-01-01

We investigated the nature of the bandwidth limit in the consolidation of visual information into visual short-term memory. In the first two experiments, we examined whether previous results showing differential consolidation bandwidth for color and orientation resulted from methodological differences by testing the consolidation of color information with methods used in prior orientation experiments. We briefly presented two color patches with masks, either sequentially or simultaneously, followed by a location cue indicating the target. Participants identified the target color via button-press (Experiment 1) or by clicking a location on a color wheel (Experiment 2). Although these methods have previously demonstrated that two orientations are consolidated in a strictly serial fashion, here we found equivalent performance in the sequential and simultaneous conditions, suggesting that two colors can be consolidated in parallel. To investigate whether this difference resulted from different consolidation mechanisms or a common mechanism with different features consuming different amounts of bandwidth, Experiment 3 presented a color patch and an oriented grating either sequentially or simultaneously. We found a lower performance in the simultaneous than the sequential condition, with orientation showing a larger impairment than color. These results suggest that consolidation of both features share common mechanisms. However, it seems that color requires less information to be encoded than orientation. As a result two colors can be consolidated in parallel without exceeding the bandwidth limit, whereas two orientations or an orientation and a color exceed the bandwidth and appear to be consolidated serially. PMID:25317065

Efficient feature subset selection with probabilistic distance criteria. [pattern recognition

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

Recursive expressions are derived for efficiently computing the commonly used probabilistic distance measures as a change in the criteria both when a feature is added to and when a feature is deleted from the current feature subset. A combinatorial algorithm for generating all possible r feature combinations from a given set of s features in (s/r) steps with a change of a single feature at each step is presented. These expressions can also be used for both forward and backward sequential feature selection.
Live-Cell Imaging of F-Actin Dynamics During Fertilization in Arabidopsis thaliana.

PubMed

Susaki, Daichi; Maruyama, Daisuke; Yelagandula, Ramesh; Berger, Frederic; Kawashima, Tomokazu

2017-01-01

Fertilization comprises a complex series of cellular processes leading to the fusion of a male and female gamete. Many studies have been carried out to investigate each step of fertilization in plants; however, our comprehensive understanding of all the sequential events during fertilization is still limited. This is largely due to difficulty in investigating events in the female gametophyte, which is deeply embedded in the maternal tissue. Recent advances in confocal microcopy assisted by fluorescent marker lines have contributed to visualizing subcellular dynamics in real time during fertilization in vivo. In this chapter, we describe a method focusing on the investigation of F-actin dynamics in the central cell during male gamete nuclear migration. This method also allows the study of a wide range of early sexual reproduction events, from pollen tube guidance to the early stage of seed development.
Monensin inhibits intracellular dissociation of asialoglycoproteins from their receptor

PubMed Central

1983-01-01

Treatment of short-term monolayer cultures of rat hepatocytes with the proton ionophore, monensin, abolishes asialoglycoprotein degradation, despite little effect of the drug on either surface binding of ligand or internalization of prebound ligand. Centrifuging cell homogenates on Percoll density gradients indicates that, as a result of monensin treatment, ligand does not enter lysosomes but sediments instead in a lower density subcellular fraction that is likely an endocytic vesicle. Analyzing the degree of receptor association of intracellular ligand revealed that monensin prevents the dissociation of the receptor-ligand complex that normally occurs subsequent to endocytosis. The weak base, chloroquine, also blocks this intracellular dissociation. Evidence from sequential substitution experiments is presented, indicating that monensin and chloroquine act at the same point in the sequence of events leading to ligand dissociation. These data are discussed in terms of a pH-mediated dissociation of the receptor-ligand complex within a prelysosomal endocytic vesicle. PMID:6304116
Sequential infiltration synthesis for advanced lithography

DOEpatents

Darling, Seth B.; Elam, Jeffrey W.; Tseng, Yu-Chih; Peng, Qing

2015-03-17

A plasma etch resist material modified by an inorganic protective component via sequential infiltration synthesis (SIS) and methods of preparing the modified resist material. The modified resist material is characterized by an improved resistance to a plasma etching or related process relative to the unmodified resist material, thereby allowing formation of patterned features into a substrate material, which may be high-aspect ratio features. The SIS process forms the protective component within the bulk resist material through a plurality of alternating exposures to gas phase precursors which infiltrate the resist material. The plasma etch resist material may be initially patterned using photolithography, electron-beam lithography or a block copolymer self-assembly process.
Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

NASA Astrophysics Data System (ADS)

Liang, Yu-Li

Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory detection rate by using facial features and skin color model. To harness all the features in the scene, we further developed another system using multiple types of local descriptors along with Bag-of-Visual Word framework. In addition, an investigation of new contour feature in detecting obscene content is presented.
Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.
Sequential two-photon double ionization of noble gases by circularly polarized XUV radiation

NASA Astrophysics Data System (ADS)

Gryzlova, E. V.; Grum-Grzhimailo, A. N.; Kuzmina, E. I.; Strakhova, S. I.

2014-10-01

Photoelectron angular distributions (PADs) and angular correlations between two emitted electrons in sequential two-photon double ionization (2PDI) of atoms by circularly polarized radiation are studied theoretically. In particular, the sequential 2PDI of the valence n{{p}6} shell in noble gas atoms (neon, argon, krypton) is analyzed, accounting for the first-order corrections to the dipole approximation. Due to different selection rules in ionization transitions, the circular polarization of photons causes some new features of the cross sections, PADs and angular correlation functions in comparison with the case of linearly polarized photons.
Predict subcellular locations of singleplex and multiplex proteins by semi-supervised learning and dimension-reducing general mode of Chou's PseAAC.

PubMed

Pacharawongsakda, Eakasit; Theeramunkong, Thanaruk

2013-12-01

Predicting protein subcellular location is one of major challenges in Bioinformatics area since such knowledge helps us understand protein functions and enables us to select the targeted proteins during drug discovery process. While many computational techniques have been proposed to improve predictive performance for protein subcellular location, they have several shortcomings. In this work, we propose a method to solve three main issues in such techniques; i) manipulation of multiplex proteins which may exist or move between multiple cellular compartments, ii) handling of high dimensionality in input and output spaces and iii) requirement of sufficient labeled data for model training. Towards these issues, this work presents a new computational method for predicting proteins which have either single or multiple locations. The proposed technique, namely iFLAST-CORE, incorporates the dimensionality reduction in the feature and label spaces with co-training paradigm for semi-supervised multi-label classification. For this purpose, the Singular Value Decomposition (SVD) is applied to transform the high-dimensional feature space and label space into the lower-dimensional spaces. After that, due to limitation of labeled data, the co-training regression makes use of unlabeled data by predicting the target values in the lower-dimensional spaces of unlabeled data. In the last step, the component of SVD is used to project labels in the lower-dimensional space back to those in the original space and an adaptive threshold is used to map a numeric value to a binary value for label determination. A set of experiments on viral proteins and gram-negative bacterial proteins evidence that our proposed method improve the classification performance in terms of various evaluation metrics such as Aiming (or Precision), Coverage (or Recall) and macro F-measure, compared to the traditional method that uses only labeled data.
Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR

PubMed Central

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms. PMID:28979308
Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

PubMed

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms.
Two birds, one stone: dual targeting of the cancer cell surface and subcellular mitochondria by the galectin-3-binding peptide G3-C12

PubMed Central

Sun, Wei; Li, Lian; Li, Li-jia; Yang, Qing-qing; Zhang, Zhi-rong; Huang, Yuan

2017-01-01

Active tumor-targeting approaches using specific ligands have drawn considerable attention over the years. However, a single ligand often fails to simultaneously target the cancer cell surface and subcellular organelles, which limits the maximum therapeutic efficacy of delivered drugs. We describe a polymeric delivery system modified with the G3-C12 peptide for sequential dual targeting. In this study, galectin-3-targeted G3-C12 peptide was conjugated onto the N-(2-hydroxypropyl) methacrylamide (HPMA) copolymer for the delivery of D(KLAKLAK)2 (KLA) peptide. G3-C12-HPMA-KLA exhibited increased receptor-mediated internalization into galectin-3-overexpressing PC-3 cells. Furthermore, G3-C12 peptide also directed HPMA-KLA conjugates to mitochondria. This occurred because the apoptosis signal triggered the accumulation of galectin-3 in mitochondria, and the G3-C12 peptide that specifically bound to galectin-3 was trafficked along with its receptor intracellularly. As a result, G3-C12-HPMA-KLA disrupted the mitochondrial membrane, increased the generation of reactive oxygen species (ROS) and induced cytochrome c release, which ultimately resulted in enhanced cytotoxicity. An in vivo study revealed that the G3-C12 peptide significantly enhanced the tumor accumulation of the KLA conjugate. In addition, G3-C12-HPMA-KLA exhibited the best therapeutic efficacy and greatly improved the animal survival rate. Our work demonstrates that G3-C12 is a promising ligand with dual-targeting functionality. PMID:28065935
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue

PubMed Central

Gerdes, Michael J.; Sevinsky, Christopher J.; Sood, Anup; Adak, Sudeshna; Bello, Musodiq O.; Bordwell, Alexander; Can, Ali; Corwin, Alex; Dinn, Sean; Filkins, Robert J.; Hollman, Denise; Kamath, Vidya; Kaanumalle, Sireesha; Kenny, Kevin; Larsen, Melinda; Lazare, Michael; Lowes, Christina; McCulloch, Colin C.; McDonough, Elizabeth; Pang, Zhengyu; Rittscher, Jens; Santamaria-Pang, Alberto; Sarachan, Brion D.; Seel, Maximilian L.; Seppo, Antti; Shaikh, Kashan; Sui, Yunxia; Zhang, Jingyu; Ginty, Fiona

2013-01-01

Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffin-embedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity, and cluster analysis of divergent signaling through ERK1/2, S6 kinase 1, and 4E binding protein 1 provides insights into the spatial organization of mechanistic target of rapamycin and MAPK signal transduction. Our results suggest MxIF should be broadly applicable to problems in the fields of basic biological research, drug discovery and development, and clinical diagnostics. PMID:23818604
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue.

PubMed

Gerdes, Michael J; Sevinsky, Christopher J; Sood, Anup; Adak, Sudeshna; Bello, Musodiq O; Bordwell, Alexander; Can, Ali; Corwin, Alex; Dinn, Sean; Filkins, Robert J; Hollman, Denise; Kamath, Vidya; Kaanumalle, Sireesha; Kenny, Kevin; Larsen, Melinda; Lazare, Michael; Li, Qing; Lowes, Christina; McCulloch, Colin C; McDonough, Elizabeth; Montalto, Michael C; Pang, Zhengyu; Rittscher, Jens; Santamaria-Pang, Alberto; Sarachan, Brion D; Seel, Maximilian L; Seppo, Antti; Shaikh, Kashan; Sui, Yunxia; Zhang, Jingyu; Ginty, Fiona

2013-07-16

Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffin-embedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity, and cluster analysis of divergent signaling through ERK1/2, S6 kinase 1, and 4E binding protein 1 provides insights into the spatial organization of mechanistic target of rapamycin and MAPK signal transduction. Our results suggest MxIF should be broadly applicable to problems in the fields of basic biological research, drug discovery and development, and clinical diagnostics.
Sequential infiltration synthesis for advanced lithography

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

Darling, Seth B.; Elam, Jeffrey W.; Tseng, Yu-Chih

A plasma etch resist material modified by an inorganic protective component via sequential infiltration synthesis (SIS) and methods of preparing the modified resist material. The modified resist material is characterized by an improved resistance to a plasma etching or related process relative to the unmodified resist material, thereby allowing formation of patterned features into a substrate material, which may be high-aspect ratio features. The SIS process forms the protective component within the bulk resist material through a plurality of alternating exposures to gas phase precursors which infiltrate the resist material. The plasma etch resist material may be initially patterned usingmore » photolithography, electron-beam lithography or a block copolymer self-assembly process.« less
A Comparison of Two Instructional Methods for Teaching Logo to Learning Disabled and Nonlearning Disabled Children.

ERIC Educational Resources Information Center

Mathinos, Debra A.; Leonard, Ann Scheier

The study examines the use of LOGO, a computer language, with 19 learning disabled (LD) and 19 non-LD students in grades 4-6. Ss were randomly assigned to one of two instructional groups: sequential or whole-task, each with 10 LD and 10 non-LD students. The sequential method features a carefully ordered plan for teaching LOGO commands; the…
MSFC Skylab airlock module, volume 1. [systems design and performance

NASA Technical Reports Server (NTRS)

1974-01-01

The history and development of the Skylab Airlock Module and Payload Shroud is presented from initial concept through final design. A summary is given of the Airlock features and systems. System design and performance are presented for the Spent Stage Experiment Support Module, structure and mechanical systems, mass properties, thermal and environmental control systems, EVA/IVA suite system, electrical power system, sequential system, sequential system, and instrumentation system.
Neuromuscular disease classification system

NASA Astrophysics Data System (ADS)

Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

2013-06-01

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.
Intrinsic fluorescence excitation-emission matrix spectral features of cottonseed protein fractions and the effects of denaturants

USDA-ARS?s Scientific Manuscript database

To better understand the functional and physicochemical properties of cottonseed protein, we investigated the intrinsic fluorescence excitation-emission matrix (EEM) spectral features of cottonseed protein isolate (CSPI) and sequentially extracted water (CSPw) and alkali (CSPa) protein fractions, an...
Adaptive sequential Bayesian classification using Page's test

NASA Astrophysics Data System (ADS)

Lynch, Robert S., Jr.; Willett, Peter K.

2002-03-01

In this paper, the previously introduced Mean-Field Bayesian Data Reduction Algorithm is extended for adaptive sequential hypothesis testing utilizing Page's test. In general, Page's test is well understood as a method of detecting a permanent change in distribution associated with a sequence of observations. However, the relationship between detecting a change in distribution utilizing Page's test with that of classification and feature fusion is not well understood. Thus, the contribution of this work is based on developing a method of classifying an unlabeled vector of fused features (i.e., detect a change to an active statistical state) as quickly as possible given an acceptable mean time between false alerts. In this case, the developed classification test can be thought of as equivalent to performing a sequential probability ratio test repeatedly until a class is decided, with the lower log-threshold of each test being set to zero and the upper log-threshold being determined by the expected distance between false alerts. It is of interest to estimate the delay (or, related stopping time) to a classification decision (the number of time samples it takes to classify the target), and the mean time between false alerts, as a function of feature selection and fusion by the Mean-Field Bayesian Data Reduction Algorithm. Results are demonstrated by plotting the delay to declaring the target class versus the mean time between false alerts, and are shown using both different numbers of simulated training data and different numbers of relevant features for each class.
EnLightenment: High resolution smartphone microscopy as an educational and public engagement platform

PubMed Central

Wicks, Laura C.; Cairns, Gemma S.; Melnyk, Jacob; Bryce, Scott; Duncan, Rory R.; Dalgarno, Paul A.

2018-01-01

We developed a simple, cost-effective smartphone microscopy platform for use in educational and public engagement programs. We demonstrated its effectiveness, and potential for citizen science through a national imaging initiative, EnLightenment. The cost effectiveness of the instrument allowed for the program to deliver over 500 microscopes to more than 100 secondary schools throughout Scotland, targeting 1000’s of 12-14 year olds. Through careful, quantified, selection of a high power, low-cost objective lens, our smartphone microscope has an imaging resolution of microns, with a working distance of 3 mm. It is therefore capable of imaging single cells and sub-cellular features, and retains usability for young children. The microscopes were designed in kit form and provided an interdisciplinary educational tool. By providing full lesson plans and support material, we developed a framework to explore optical design, microscope performance, engineering challenges on construction and real-world applications in life sciences, biological imaging, marine biology, art, and technology. A national online imaging competition framed EnLightenment ; with over 500 high quality images submitted of diverse content, spanning multiple disciplines. With examples of cellular and sub-cellular features clearly identifiable in some submissions, we show how young public can use these instruments for research-level imaging applications, and the potential of the instrument for citizen science programs. PMID:29623296

HMPAS: Human Membrane Protein Analysis System

PubMed Central

2013-01-01

Background Membrane proteins perform essential roles in diverse cellular functions and are regarded as major pharmaceutical targets. The significance of membrane proteins has led to the developing dozens of resources related with membrane proteins. However, most of these resources are built for specific well-known membrane protein groups, making it difficult to find common and specific features of various membrane protein groups. Methods We collected human membrane proteins from the dispersed resources and predicted novel membrane protein candidates by using ortholog information and our membrane protein classifiers. The membrane proteins were classified according to the type of interaction with the membrane, subcellular localization, and molecular function. We also made new feature dataset to characterize the membrane proteins in various aspects including membrane protein topology, domain, biological process, disease, and drug. Moreover, protein structure and ICD-10-CM based integrated disease and drug information was newly included. To analyze the comprehensive information of membrane proteins, we implemented analysis tools to identify novel sequence and functional features of the classified membrane protein groups and to extract features from protein sequences. Results We constructed HMPAS with 28,509 collected known membrane proteins and 8,076 newly predicted candidates. This system provides integrated information of human membrane proteins individually and in groups organized by 45 subcellular locations and 1,401 molecular functions. As a case study, we identified associations between the membrane proteins and diseases and present that membrane proteins are promising targets for diseases related with nervous system and circulatory system. A web-based interface of this system was constructed to facilitate researchers not only to retrieve organized information of individual proteins but also to use the tools to analyze the membrane proteins. Conclusions HMPAS provides comprehensive information about human membrane proteins including specific features of certain membrane protein groups. In this system, user can acquire the information of individual proteins and specified groups focused on their conserved sequence features, involved cellular processes, and diseases. HMPAS may contribute as a valuable resource for the inference of novel cellular mechanisms and pharmaceutical targets associated with the human membrane proteins. HMPAS is freely available at http://fcode.kaist.ac.kr/hmpas. PMID:24564858
Subcellular Redox Signaling.

PubMed

Zhu, Liping; Lu, Yankai; Zhang, Jiwei; Hu, Qinghua

2017-01-01

Oxidative and antioxidative system of cells and tissues maintains a balanced state under physiological conditions. A disruption in this balance of redox status has been associated with numerous pathological processes. Reactive oxygen species (ROS) as a major redox signaling generates in a spatiotemporally dependent manner. Subcellular organelles such as mitochondria, endoplasmic reticulum, plasma membrane and nuclei contribute to the production of ROS. In addition to downstream effects of ROS signaling regulated by average ROS changes in cytoplasm, whether subcelluar ROS mediate biological effect(s) has drawn greater attentions. With the advance in redox-sensitive probes targeted to different subcellular compartments, the investigation of subcellular ROS signaling and its associated cellular function has become feasible. In this review, we discuss the subcellular ROS signaling, with particular focus on mechanisms of subcellular ROS production and its downstream effects.
The sequential structure of brain activation predicts skill.

PubMed

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

2016-01-29

In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Visual Working Memory Is Independent of the Cortical Spacing Between Memoranda.

PubMed

Harrison, William J; Bays, Paul M

2018-03-21

The sensory recruitment hypothesis states that visual short-term memory is maintained in the same visual cortical areas that initially encode a stimulus' features. Although it is well established that the distance between features in visual cortex determines their visibility, a limitation known as crowding, it is unknown whether short-term memory is similarly constrained by the cortical spacing of memory items. Here, we investigated whether the cortical spacing between sequentially presented memoranda affects the fidelity of memory in humans (of both sexes). In a first experiment, we varied cortical spacing by taking advantage of the log-scaling of visual cortex with eccentricity, presenting memoranda in peripheral vision sequentially along either the radial or tangential visual axis with respect to the fovea. In a second experiment, we presented memoranda sequentially either within or beyond the critical spacing of visual crowding, a distance within which visual features cannot be perceptually distinguished due to their nearby cortical representations. In both experiments and across multiple measures, we found strong evidence that the ability to maintain visual features in memory is unaffected by cortical spacing. These results indicate that the neural architecture underpinning working memory has properties inconsistent with the known behavior of sensory neurons in visual cortex. Instead, the dissociation between perceptual and memory representations supports a role of higher cortical areas such as posterior parietal or prefrontal regions or may involve an as yet unspecified mechanism in visual cortex in which stimulus features are bound to their temporal order. SIGNIFICANCE STATEMENT Although much is known about the resolution with which we can remember visual objects, the cortical representation of items held in short-term memory remains contentious. A popular hypothesis suggests that memory of visual features is maintained via the recruitment of the same neural architecture in sensory cortex that encodes stimuli. We investigated this claim by manipulating the spacing in visual cortex between sequentially presented memoranda such that some items shared cortical representations more than others while preventing perceptual interference between stimuli. We found clear evidence that short-term memory is independent of the intracortical spacing of memoranda, revealing a dissociation between perceptual and memory representations. Our data indicate that working memory relies on different neural mechanisms from sensory perception. Copyright © 2018 Harrison and Bays.
Identification, characterization and subcellular localization of TcPDE1, a novel cAMP-specific phosphodiesterase from Trypanosoma cruzi.

PubMed Central

D'Angelo, Maximiliano A; Sanguineti, Santiago; Reece, Jeffrey M; Birnbaumer, Lutz; Torres, Héctor N; Flawiá, Mirtha M

2004-01-01

Compartmentalization of cAMP phosphodiesterases plays a key role in the regulation of cAMP signalling in mammals. In the present paper, we report the characterization and subcellular localization of TcPDE1, the first cAMP-specific phosphodiesterase to be identified from Trypanosoma cruzi. TcPDE1 is part of a small gene family and encodes a 929-amino-acid protein that can complement a heat-shock-sensitive yeast mutant deficient in phospho-diesterase genes. Recombinant TcPDE1 strongly associates with membranes and cannot be released with NaCl or sodium cholate, suggesting that it is an integral membrane protein. This enzyme is specific for cAMP and its activity is not affected by cGMP, Ca2+, calmodulin or fenotiazinic inhibitors. TcPDE1 is sensitive to the phosphodiesterase inhibitor dipyridamole but is resistant to 3-isobutyl-1-methylxanthine, theophylline, rolipram and zaprinast. Papaverine, erythro-9-(2-hydroxy-3-nonyl)-adenine hydrochloride, and vinpocetine are poor inhibitors of this enzyme. Confocal laser scanning of T. cruzi epimastigotes showed that TcPDE1 is associated with the plasma membrane and concentrated in the flagellum of the parasite. The association of TcPDE1 with this organelle was confirmed by subcellular fractionation and cell-disruption treatments. The localization of this enzyme is a unique feature that distinguishes it from all the trypanosomatid phosphodiesterases described so far and indicates that compartmentalization of cAMP phosphodiesterases could also be important in these parasites. PMID:14556647
mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2015-03-15

Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.
Rate of dehydration, state of subcellular organisation and nature of cryoprotection are critical factors contributing to the variable success of cryopreservation: studies on recalcitrant zygotic embryos of Haemanthus montanus.

PubMed

Sershen; Berjak, Patricia; Pammenter, N W; Wesley-Smith, James

2012-01-01

Effects of sequential procedures required for cryopreservation of embryos excised from the recalcitrant seeds of Haemanthus montanus were assessed ultrastructurally and in conjunction with respiratory activity and the rate of protein synthesis. Fresh material (water content, 5.05 ± 0.92 g g(-1) dry mass) afforded ultrastructural evidence of considerable metabolic activity, borne out by respiratory rates. Neither exposure to glycerol nor sucrose as penetrating and non-penetrating cryoprotectants, respectively, brought about degradative changes, although increased vacuolation and autophagy accompanied both, while respiratory and protein synthetic activity were not adversely affected. Glycerol-cryoprotected embryos flash dried to water contents >0.4 g g(-1) showed organised ultrastructural features and considerable autophagy consistent with metabolic activity, and although respiratory activity was lower, protein synthesis rate was enhanced relative to fresh material. However, at water contents <0.4 g g(-1), embryo tissue presented a mosaic of cells of variable density and ultrastructural status, but trends in rates of respiration and protein synthesis remained similar. Flash drying after sucrose exposure was accompanied by considerable ultrastructural abnormality particularly at water contents <0.4 g g(-1), lysis of individual and groups of cells and considerable depression of respiration, but not of protein synthesis. Success, assessed as ≥50% axes forming seedlings after cryogen exposure, was obtained only when glycerol-cryoprotected embryos at water contents >0.4 g g(-1)-in which the degree of vacuolation remained moderate-were rapidly cooled. The outcomes of this study are considered particularly in terms of the stresses imposed by prolonged, relatively slow dehydration and ultimate water contents, on embryos showing considerable metabolic activity.
Inter-kingdom prediction certainty evaluation of protein subcellular localization tools: microbial pathogenesis approach for deciphering host microbe interaction.

PubMed

Khan, Abdul Arif; Khan, Zakir; Kalam, Mohd Abul; Khan, Azmat Ali

2018-01-01

Microbial pathogenesis involves several aspects of host-pathogen interactions, including microbial proteins targeting host subcellular compartments and subsequent effects on host physiology. Such studies are supported by experimental data, but recent detection of bacterial proteins localization through computational eukaryotic subcellular protein targeting prediction tools has also come into practice. We evaluated inter-kingdom prediction certainty of these tools. The bacterial proteins experimentally known to target host subcellular compartments were predicted with eukaryotic subcellular targeting prediction tools, and prediction certainty was assessed. The results indicate that these tools alone are not sufficient for inter-kingdom protein targeting prediction. The correct prediction of pathogen's protein subcellular targeting depends on several factors, including presence of localization signal, transmembrane domain and molecular weight, etc., in addition to approach for subcellular targeting prediction. The detection of protein targeting in endomembrane system is comparatively difficult, as the proteins in this location are channelized to different compartments. In addition, the high specificity of training data set also creates low inter-kingdom prediction accuracy. Current data can help to suggest strategy for correct prediction of bacterial protein's subcellular localization in host cell. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Cognitive predictors of sequential motor impairments in children with dyslexia and/or attention deficit/hyperactivity disorder.

PubMed

Marchand-Krynski, Marie-Ève; Bélanger, Anne-Marie; Morin-Moncet, Olivier; Beauchamp, Miriam H; Leonard, Gabriel

2018-01-01

This study examined cognitive predictors of sequential motor skills in 215 children with dyslexia and/or attention deficit/hyperactivity disorder (ADHD). Visual working memory and math fluency abilities contributed significantly to performance of sequential motor abilities in children with dyslexia (N = 67), ADHD (N = 66) and those with a comorbid diagnosis (N = 82), generally without differentiation between groups. In addition, primary diagnostic features of each disorder, such as reading and inattention, did not contribute to the variance in motor skill performance of these children. The results support a unifying framework of motor impairment in children with neurodevelopmental disorders such as dyslexia and ADHD.
Self-organization across scales: from molecules to organisms.

PubMed

Saha, Tanumoy; Galic, Milos

2018-05-26

Creating ordered structures from chaotic environments is at the core of biological processes at the subcellular, cellular and organismic level. In this perspective, we explore the physical as well as biological features of two prominent concepts driving self-organization, namely phase transition and reaction-diffusion, before closing with a discussion on open questions and future challenges associated with studying self-organizing systems.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).
Subcellular Localization of HIV-1 gag-pol mRNAs Regulates Sites of Virion Assembly

PubMed Central

Becker, Jordan T.

2017-01-01

ABSTRACT Full-length unspliced human immunodeficiency virus type 1 (HIV-1) RNAs serve dual roles in the cytoplasm as mRNAs encoding the Gag and Gag-Pol capsid proteins as well as genomic RNAs (gRNAs) packaged by Gag into virions undergoing assembly at the plasma membrane (PM). Because Gag is sufficient to drive the assembly of virus-like particles even in the absence of gRNA binding, whether viral RNA trafficking plays an active role in the native assembly pathway is unknown. In this study, we tested the effects of modulating the cytoplasmic abundance or distribution of full-length viral RNAs on Gag trafficking and assembly in the context of single cells. Increasing full-length viral RNA abundance or distribution had little-to-no net effect on Gag assembly competency when provided in trans. In contrast, artificially tethering full-length viral RNAs or surrogate gag-pol mRNAs competent for Gag synthesis to non-PM membranes or the actin cytoskeleton severely reduced net virus particle production. These effects were explained, in large part, by RNA-directed changes to Gag's distribution in the cytoplasm, yielding aberrant subcellular sites of virion assembly. Interestingly, RNA-dependent disruption of Gag trafficking required either of two cis-acting RNA regulatory elements: the 5′ packaging signal (Psi) bound by Gag during genome encapsidation or, unexpectedly, the Rev response element (RRE), which regulates the nuclear export of gRNAs and other intron-retaining viral RNAs. Taken together, these data support a model for native infection wherein structural features of the gag-pol mRNA actively compartmentalize Gag to preferred sites within the cytoplasm and/or PM. IMPORTANCE The spatial distribution of viral mRNAs within the cytoplasm can be a crucial determinant of efficient translation and successful virion production. Here we provide direct evidence that mRNA subcellular trafficking plays an important role in regulating the assembly of human immunodeficiency virus type 1 (HIV-1) virus particles at the plasma membrane (PM). Artificially tethering viral mRNAs encoding Gag capsid proteins (gag-pol mRNAs) to distinct non-PM subcellular locales, such as cytoplasmic vesicles or the actin cytoskeleton, markedly alters Gag subcellular distribution, relocates sites of assembly, and reduces net virus particle production. These observations support a model for native HIV-1 assembly wherein HIV-1 gag-pol mRNA localization helps to confine interactions between Gag, viral RNAs, and host determinants in order to ensure virion production at the right place and right time. Direct perturbation of HIV-1 mRNA subcellular localization may represent a novel antiviral strategy. PMID:28053097
Subcellular Localization of HIV-1 gag-pol mRNAs Regulates Sites of Virion Assembly.

PubMed

Becker, Jordan T; Sherer, Nathan M

2017-03-15

Full-length unspliced human immunodeficiency virus type 1 (HIV-1) RNAs serve dual roles in the cytoplasm as mRNAs encoding the Gag and Gag-Pol capsid proteins as well as genomic RNAs (gRNAs) packaged by Gag into virions undergoing assembly at the plasma membrane (PM). Because Gag is sufficient to drive the assembly of virus-like particles even in the absence of gRNA binding, whether viral RNA trafficking plays an active role in the native assembly pathway is unknown. In this study, we tested the effects of modulating the cytoplasmic abundance or distribution of full-length viral RNAs on Gag trafficking and assembly in the context of single cells. Increasing full-length viral RNA abundance or distribution had little-to-no net effect on Gag assembly competency when provided in trans In contrast, artificially tethering full-length viral RNAs or surrogate gag-pol mRNAs competent for Gag synthesis to non-PM membranes or the actin cytoskeleton severely reduced net virus particle production. These effects were explained, in large part, by RNA-directed changes to Gag's distribution in the cytoplasm, yielding aberrant subcellular sites of virion assembly. Interestingly, RNA-dependent disruption of Gag trafficking required either of two cis -acting RNA regulatory elements: the 5' packaging signal (Psi) bound by Gag during genome encapsidation or, unexpectedly, the Rev response element (RRE), which regulates the nuclear export of gRNAs and other intron-retaining viral RNAs. Taken together, these data support a model for native infection wherein structural features of the gag-pol mRNA actively compartmentalize Gag to preferred sites within the cytoplasm and/or PM. IMPORTANCE The spatial distribution of viral mRNAs within the cytoplasm can be a crucial determinant of efficient translation and successful virion production. Here we provide direct evidence that mRNA subcellular trafficking plays an important role in regulating the assembly of human immunodeficiency virus type 1 (HIV-1) virus particles at the plasma membrane (PM). Artificially tethering viral mRNAs encoding Gag capsid proteins ( gag-pol mRNAs) to distinct non-PM subcellular locales, such as cytoplasmic vesicles or the actin cytoskeleton, markedly alters Gag subcellular distribution, relocates sites of assembly, and reduces net virus particle production. These observations support a model for native HIV-1 assembly wherein HIV-1 gag-pol mRNA localization helps to confine interactions between Gag, viral RNAs, and host determinants in order to ensure virion production at the right place and right time. Direct perturbation of HIV-1 mRNA subcellular localization may represent a novel antiviral strategy. Copyright © 2017 American Society for Microbiology.
Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.

PubMed

Wang, Chuangqi; Choi, Hee June; Kim, Sung-Jin; Desai, Aesha; Lee, Namgyu; Kim, Dohoon; Bae, Yongho; Lee, Kwonmoo

2018-04-27

Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanism of cell protrusion has been understood based on the ensemble average of actin regulator dynamics. Here, we establish a computational framework called HACKS (deconvolution of heterogeneous activity in coordination of cytoskeleton at the subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion from live cell imaging. HACKS identifies distinct subcellular protrusion phenotypes based on machine-learning algorithms and reveals their underlying actin regulator dynamics at the leading edge. Using our method, we discover "accelerating protrusion", which is driven by the temporally ordered coordination of Arp2/3 and VASP activities. We validate our finding by pharmacological perturbations and further identify the fine regulation of Arp2/3 and VASP recruitment associated with accelerating protrusion. Our study suggests HACKS can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation.
Incremental Bayesian Category Learning From Natural Language.

PubMed

Frermann, Lea; Lapata, Mirella

2016-08-01

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., chair is a member of the furniture category). We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: (a) the acquisition of features that discriminate among categories, and (b) the grouping of concepts into categories based on those features. Our model learns categories incrementally using particle filters, a sequential Monte Carlo method commonly used for approximate probabilistic inference that sequentially integrates newly observed data and can be viewed as a plausible mechanism for human learning. Experimental results show that our incremental learner obtains meaningful categories which yield a closer fit to behavioral data compared to related models while at the same time acquiring features which characterize the learned categories. (An earlier version of this work was published in Frermann and Lapata .). Copyright © 2015 Cognitive Science Society, Inc.
A stacked sequential learning method for investigator name recognition from web-based medical articles

NASA Astrophysics Data System (ADS)

Zhang, Xiaoli; Zou, Jie; Le, Daniel X.; Thoma, George

2010-01-01

"Investigator Names" is a newly required field in MEDLINE citations. It consists of personal names listed as members of corporate organizations in an article. Extracting investigator names automatically is necessary because of the increasing volume of articles reporting collaborative biomedical research in which a large number of investigators participate. In this paper, we present an SVM-based stacked sequential learning method in a novel application - recognizing named entities such as the first and last names of investigators from online medical journal articles. Stacked sequential learning is a meta-learning algorithm which can boost any base learner. It exploits contextual information by adding the predicted labels of the surrounding tokens as features. We apply this method to tag words in text paragraphs containing investigator names, and demonstrate that stacked sequential learning improves the performance of a nonsequential base learner such as an SVM classifier.
Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

PubMed Central

Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

2015-01-01

Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269
Subcellular Distribution of O-Acetylserine(thiol)lyase in Cauliflower (Brassica oleracea L.) Inflorescence.

PubMed

Rolland, N; Droux, M; Douce, R

1992-03-01

The subcellular localization of O-acetyiserine(thiol)lyase (EC 4.2.99.8) in nongreen tissue from higher plants has been studied using purified proplastids, mitochondria, and protoplasts from cauliflower (Brassica oleracea L.) buds as a source of subcellular fractions. O-Acetylserine(thiol)lyase has been detected in both organelles (proplastids and mitochondria) and a cytosolic extract obtained by protoplast fractionation. We confirmed these observations, demonstrating that a form of the enzyme different in global charge and separated from others by anion-exchange chromatography corresponded to each subcellular location. Our observations are consistent with the need for cysteine biosynthesis in each subcellular compartment where the synthesis of proteins occurs.
Subcellular Distribution of O-Acetylserine(thiol)lyase in Cauliflower (Brassica oleracea L.) Inflorescence

PubMed Central

Rolland, Norbert; Droux, Michel; Douce, Roland

1992-01-01

The subcellular localization of O-acetyiserine(thiol)lyase (EC 4.2.99.8) in nongreen tissue from higher plants has been studied using purified proplastids, mitochondria, and protoplasts from cauliflower (Brassica oleracea L.) buds as a source of subcellular fractions. O-Acetylserine(thiol)lyase has been detected in both organelles (proplastids and mitochondria) and a cytosolic extract obtained by protoplast fractionation. We confirmed these observations, demonstrating that a form of the enzyme different in global charge and separated from others by anion-exchange chromatography corresponded to each subcellular location. Our observations are consistent with the need for cysteine biosynthesis in each subcellular compartment where the synthesis of proteins occurs. ImagesFigure 1 PMID:16668766
Determination of the Subcellular Distribution of Liposomes Using Confocal Microscopy.

PubMed

Solomon, Melani A

2017-01-01

It is being increasingly recognized that therapeutics need to be delivered to specific organelle targets within cells. Liposomes are versatile lipid-based drug delivery vehicles that can be surface-modified to deliver the loaded cargo to specific subcellular locations within the cell. Hence, the development of such technology requires a means of measuring the subcellular distribution possibly by utilizing imaging techniques that can visualize and quantitate the extent of this subcellular localization. The apparent increase of resolution along the Z-axis offered by confocal microscopy makes this technique suitable for such studies. In this chapter, we describe the application of confocal laser scanning microscopy (CLSM) to determine the subcellular distribution of fluorescently labeled mitochondriotropic liposomes.
PA-GFP: a window into the subcellular adventures of the individual mitochondrion.

PubMed

Haigh, Sarah E; Twig, Gilad; Molina, Anthony A J; Wikstrom, Jakob D; Deutsch, Motti; Shirihai, Orian S

2007-01-01

Mitochondrial connectivity is characterized by matrix lumen continuity and by dynamic rewiring through fusion and fission events. While these mechanisms homogenize the mitochondrial population, a number of studies looking at mitochondrial membrane potential have demonstrated that mitochondria exist as a heterogeneous population within individual cells. To address the relationship between mitochondrial dynamics and heterogeneity, we tagged and tracked individual mitochondria over time while monitoring their mitochondrial membrane potential (deltapsi(m)). By utilizing photoactivatible-GFP (PA-GFP), targeted to the mitochondrial matrix, we determined the boundaries of the individual mitochondrion. A single mitochondrion is defined by the continuity of its matrix lumen. The boundaries set by luminal continuity matched those set by electrical coupling, indicating that the individual mitochondrion is equipotential throughout the entire organelle. Similar results were obtained with PA-GFP targeted to the inner membrane indicating that matrix continuity parallels inner membrane continuity. Sequential photoconversion of matrix PA-GFP in multiple locations within the mitochondrial web reveals that each ramified mitochondrial structure is composed of juxtaposed but discontinuous units. Moreover, as many as half of the events in which mitochondria come into contact, do not result in fusion. While all fission events generated two electrically uncoupled discontinuous matrices, the two daughter mitochondria frequently remained juxtaposed, keeping the tubular appearance unchanged. These morphologically invisible fission events illustrate the difference between mitochondrial fission and fragmentation; the latter representing the movement and separation of disconnected units. Simultaneous monitoring of deltapsi(m) of up to four individual mitochondria within the same cell revealed that subcellular heterogeneity in deltapsi(m) does not represent multiple unstable mitochondria that appear 'heterogeneous' at any given point, but rather multiple stable, but heterogeneous units.

Raman microspectroscopy of nucleus and cytoplasm for human colon cancer diagnosis.

PubMed

Liu, Wenjing; Wang, Hongbo; Du, Jingjing; Jing, Chuanyong

2017-11-15

Subcellular Raman analysis is a promising clinic tool for cancer diagnosis, but constrained by the difficulty of deciphering subcellular spectra in actual human tissues. We report a label-free subcellular Raman analysis for use in cancer diagnosis that integrates subcellular signature spectra by subtracting cytoplasm from nucleus spectra (Nuc.-Cyt.) with a partial least squares-discriminant analysis (PLS-DA) model. Raman mapping with the classical least-squares (CLS) model allowed direct visualization of the distribution of the cytoplasm and nucleus. The PLS-DA model was employed to evaluate the diagnostic performance of five types of spectral datasets, including non-selective, nucleus, cytoplasm, ratio of nucleus to cytoplasm (Nuc./Cyt.), and nucleus minus cytoplasm (Nuc.-Cyt.), resulting in diagnostic sensitivity of 88.3%, 84.0%, 98.4%, 84.5%, and 98.9%, respectively. Discriminating between normal and cancerous cells of actual human tissues through subcellular Raman markers is feasible, especially when using the nucleus-cytoplasm difference spectra. The subcellular Raman approach had good stability, and had excellent diagnostic performance for rectal as well as colon tissues. The insights gained from this study shed new light on the general applicability of subcellular Raman analysis in clinical trials. Copyright © 2017 Elsevier B.V. All rights reserved.
Sequential memory: Binding dynamics

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.
Enhancing the performance of tungsten doped InZnO thin film transistors via sequential ambient annealing

NASA Astrophysics Data System (ADS)

Park, Hyun-Woo; Song, Aeran; Kwon, Sera; Choi, Dukhyun; Kim, Younghak; Jun, Byung-Hyuk; Kim, Han-Ki; Chung, Kwun-Bum

2018-03-01

This study suggests a sequential ambient annealing process as an excellent post-treatment method to enhance the device performance and stability of W (tungsten) doped InZnO thin film transistors (WIZO-TFTs). Sequential ambient annealing at 250 °C significantly enhanced the device performance and stability of WIZO-TFTs, compared with other post-treatment methods, such as air ambient annealing and vacuum ambient annealing at 250 °C. To understand the enhanced device performance and stability of WIZO-TFT with sequential ambient annealing, we investigate the correlations between device performance and stability and electronic structures, such as band alignment, a feature of the conduction band, and band edge states below the conduction band. The enhanced performance of WIZO-TFTs with sequential ambient annealing is related to the modification of the electronic structure. In addition, the dominant mechanism responsible for the enhanced device performance and stability of WIZO-TFTs is considered to be a change in the shallow-level and deep-level band edge states below the conduction band.
Sequential memory: Binding dynamics.

PubMed

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.
Parallel algorithm for computation of second-order sequential best rotations

NASA Astrophysics Data System (ADS)

Redif, Soydan; Kasap, Server

2013-12-01

Algorithms for computing an approximate polynomial matrix eigenvalue decomposition of para-Hermitian systems have emerged as a powerful, generic signal processing tool. A technique that has shown much success in this regard is the sequential best rotation (SBR2) algorithm. Proposed is a scheme for parallelising SBR2 with a view to exploiting the modern architectural features and inherent parallelism of field-programmable gate array (FPGA) technology. Experiments show that the proposed scheme can achieve low execution times while requiring minimal FPGA resources.
Synthesis of Polyheteroaromatic Compounds via Rhodium-Catalyzed Multiple C-H Bond Activation and Oxidative Annulation.

PubMed

Peng, Shiyong; Liu, Suna; Zhang, Sai; Cao, Shengyu; Sun, Jiangtao

2015-10-16

Polyheteroaromatic compounds are potential optoelectronic conjugated materials due to their electro- and photochemical properties. Transition-metal-catalyzed multiple C-H activation and sequential oxidative annulation allows rapidly assembling of those compounds from readily available starting materials. A rhodium-catalyzed cascade oxidative annulation of β-enamino esters or 4-aminocoumarins with internal alkynes is described to access those compounds, featuring multiple C-H/N-H bond cleavages and sequential C-C/C-N bond formations in one pot.
Subcellular partitioning of metals in Aporrectodea caliginosa along a gradient of metal exposure in 31 field-contaminated soils.

PubMed

Beaumelle, Léa; Gimbert, Frédéric; Hedde, Mickaël; Guérin, Annie; Lamy, Isabelle

2015-07-01

Subcellular fractionation of metals in organisms was proposed as a better way to characterize metal bioaccumulation. Here we report the impact of a laboratory exposure to a wide range of field-metal contaminated soils on the subcellular partitioning of metals in the earthworm Aporrectodea caliginosa. Soils moderately contaminated were chosen to create a gradient of soil metal availability; covering ranges of both soil metal contents and of several soil parameters. Following exposure, Cd, Pb and Zn concentrations were determined both in total earthworm body and in three subcellular compartments: cytosolic, granular and debris fractions. Three distinct proxies of soil metal availability were investigated: CaCl2-extractable content dissolved content predicted by a semi-mechanistic model and free ion concentration predicted by a geochemical speciation model. Subcellular partitionings of Cd and Pb were modified along the gradient of metal exposure, while stable Zn partitioning reflected regulation processes. Cd subcellular distribution responded more strongly to increasing soil Cd concentration than the total internal content, when Pb subcellular distribution and total internal content were similarly affected. Free ion concentrations were better descriptors of Cd and Pb subcellular distribution than CaCl2 extractable and dissolved metal concentrations. However, free ion concentrations and soil total metal contents were equivalent descriptors of the subcellular partitioning of Cd and Pb because they were highly correlated. Considering lowly contaminated soils, our results raise the question of the added value of three proxies of metal availability compared to soil total metal content in the assessment of metal bioavailability to earthworm. Copyright © 2015 Elsevier B.V. All rights reserved.
Designer nanoparticle: nanobiotechnology tool for cell biology

NASA Astrophysics Data System (ADS)

Thimiri Govinda Raj, Deepak B.; Khan, Niamat Ali

2016-09-01

This article discusses the use of nanotechnology for subcellular compartment isolation and its application towards subcellular omics. This technology review significantly contributes to our understanding on use of nanotechnology for subcellular systems biology. Here we elaborate nanobiotechnology approach of using superparamagnetic nanoparticles (SPMNPs) optimized with different surface coatings for subcellular organelle isolation. Using pulse-chase approach, we review that SPMNPs interacted differently with the cell depending on its surface functionalization. The article focuses on the use of functionalized-SPMNPs as a nanobiotechnology tool to isolate high quality (both purity and yield) plasma membranes and endosomes or lysosomes. Such nanobiotechnology tool can be applied in generating subcellular compartment inventories. As a future perspective, this strategy could be applied in areas such as immunology, cancer and stem cell research.
Designer nanoparticle: nanobiotechnology tool for cell biology.

PubMed

Thimiri Govinda Raj, Deepak B; Khan, Niamat Ali

2016-01-01

This article discusses the use of nanotechnology for subcellular compartment isolation and its application towards subcellular omics. This technology review significantly contributes to our understanding on use of nanotechnology for subcellular systems biology. Here we elaborate nanobiotechnology approach of using superparamagnetic nanoparticles (SPMNPs) optimized with different surface coatings for subcellular organelle isolation. Using pulse-chase approach, we review that SPMNPs interacted differently with the cell depending on its surface functionalization. The article focuses on the use of functionalized-SPMNPs as a nanobiotechnology tool to isolate high quality (both purity and yield) plasma membranes and endosomes or lysosomes. Such nanobiotechnology tool can be applied in generating subcellular compartment inventories. As a future perspective, this strategy could be applied in areas such as immunology, cancer and stem cell research.
[L-arginine metabolism enzyme activities in rat liver subcellular fractions under condition of protein deprivation].

PubMed

Kopyl'chuk, G P; Buchkovskaia, I M

2014-01-01

The features of arginase and NO-synthase pathways of arginine's metabolism have been studied in rat liver subcellular fractions under condition of protein deprivation. During the experimental period (28 days) albino male rats were kept on semi synthetic casein diet AIN-93. The protein deprivation conditions were designed as total absence of protein in the diet and consumption of the diet partially deprived with 1/2 of the casein amount compared to in the regular diet. Daily diet consumption was regulated according to the pair feeding approach. It has been shown that the changes of enzyme activities, involved in L-arginine metabolism, were characterized by 1.4-1.7 fold decrease in arginase activity, accompanied with unchanged NO-synthase activity in cytosol. In mitochondrial fraction the unchanged arginase activity was accompanied by 3-5 fold increase of NO-synthase activity. At the terminal stages of the experiment the monodirectional dynamics in the studied activities have been observed in the mitochondrial and cytosolfractions in both experimental groups. In the studied subcellular fractions arginase activity decreased (2.4-2.7 fold with no protein in the diet and 1.5 fold with partly supplied protein) and was accompanied by NO-synthase activity increase by 3.8 fold in cytosole fraction, by 7.2 fold in mitochondrial fraction in the group with no protein in the diet and by 2.2 and 3.5 fold in the group partialy supplied with protein respectively. The observed tendency is presumably caused by the switch of L-arginine metabolism from arginase into oxidizing NO-synthase parthway.
Role of NH{sub 2}-terminal hydrophobic motif in the subcellular localization of ATP-binding cassette protein subfamily D: Common features in eukaryotic organisms

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

Lee, Asaka; Asahina, Kota; Okamoto, Takumi

Highlights: • ABCD proteins classifies based on with or without NH{sub 2}-terminal hydrophobic segment. • The ABCD proteins with the segment are targeted peroxisomes. • The ABCD proteins without the segment are targeted to the endoplasmic reticulum. • The role of the segment in organelle targeting is conserved in eukaryotic organisms. - Abstract: In mammals, four ATP-binding cassette (ABC) proteins belonging to subfamily D have been identified. ABCD1–3 possesses the NH{sub 2}-terminal hydrophobic region and are targeted to peroxisomes, while ABCD4 lacking the region is targeted to the endoplasmic reticulum (ER). Based on hydropathy plot analysis, we found that severalmore » eukaryotes have ABCD protein homologs lacking the NH{sub 2}-terminal hydrophobic segment (H0 motif). To investigate whether the role of the NH{sub 2}-terminal H0 motif in subcellular localization is conserved across species, we expressed ABCD proteins from several species (metazoan, plant and fungi) in fusion with GFP in CHO cells and examined their subcellular localization. ABCD proteins possessing the NH{sub 2}-terminal H0 motif were localized to peroxisomes, while ABCD proteins lacking this region lost this capacity. In addition, the deletion of the NH{sub 2}-terminal H0 motif of ABCD protein resulted in their localization to the ER. These results suggest that the role of the NH{sub 2}-terminal H0 motif in organelle targeting is widely conserved in living organisms.« less
7 CFR 340.8 - Container requirements for the movement of regulated articles.

Code of Federal Regulations, 2011 CFR

2011-01-01

... requirements—(1) Plants and plant parts. All plants or plant parts, except seeds, cells, and subcellular... strength. (3) Live microorganisms and/or etiologic agents, cells, or subcellular elements. All regulated articles which are live (non-inactivated) microorganisms, or etiologic agents, cells, or subcellular...
7 CFR 340.8 - Container requirements for the movement of regulated articles.

Code of Federal Regulations, 2014 CFR

2014-01-01

... requirements—(1) Plants and plant parts. All plants or plant parts, except seeds, cells, and subcellular... strength. (3) Live microorganisms and/or etiologic agents, cells, or subcellular elements. All regulated articles which are live (non-inactivated) microorganisms, or etiologic agents, cells, or subcellular...
7 CFR 340.8 - Container requirements for the movement of regulated articles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... requirements—(1) Plants and plant parts. All plants or plant parts, except seeds, cells, and subcellular... strength. (3) Live microorganisms and/or etiologic agents, cells, or subcellular elements. All regulated articles which are live (non-inactivated) microorganisms, or etiologic agents, cells, or subcellular...
7 CFR 340.8 - Container requirements for the movement of regulated articles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... requirements—(1) Plants and plant parts. All plants or plant parts, except seeds, cells, and subcellular... strength. (3) Live microorganisms and/or etiologic agents, cells, or subcellular elements. All regulated articles which are live (non-inactivated) microorganisms, or etiologic agents, cells, or subcellular...
Movies of cellular and sub-cellular motion by digital holographic microscopy.

PubMed

Mann, Christopher J; Yu, Lingfeng; Kim, Myung K

2006-03-23

Many biological specimens, such as living cells and their intracellular components, often exhibit very little amplitude contrast, making it difficult for conventional bright field microscopes to distinguish them from their surroundings. To overcome this problem phase contrast techniques such as Zernike, Normarsky and dark-field microscopies have been developed to improve specimen visibility without chemically or physically altering them by the process of staining. These techniques have proven to be invaluable tools for studying living cells and furthering scientific understanding of fundamental cellular processes such as mitosis. However a drawback of these techniques is that direct quantitative phase imaging is not possible. Quantitative phase imaging is important because it enables determination of either the refractive index or optical thickness variations from the measured optical path length with sub-wavelength accuracy. Digital holography is an emergent phase contrast technique that offers an excellent approach in obtaining both qualitative and quantitative phase information from the hologram. A CCD camera is used to record a hologram onto a computer and numerical methods are subsequently applied to reconstruct the hologram to enable direct access to both phase and amplitude information. Another attractive feature of digital holography is the ability to focus on multiple focal planes from a single hologram, emulating the focusing control of a conventional microscope. A modified Mach-Zender off-axis setup in transmission is used to record and reconstruct a number of holographic amplitude and phase images of cellular and sub-cellular features. Both cellular and sub-cellular features are imaged with sub-micron, diffraction-limited resolution. Movies of holographic amplitude and phase images of living microbes and cells are created from a series of holograms and reconstructed with numerically adjustable focus, so that the moving object can be accurately tracked with a reconstruction rate of 300ms for each hologram. The holographic movies show paramecium swimming among other microbes as well as displaying some of their intracellular processes. A time lapse movie is also shown for fibroblast cells in the process of migration. Digital holography and movies of digital holography are seen to be useful new tools for visualization of dynamic processes in biological microscopy. Phase imaging digital holography is a promising technique in terms of the lack of coherent noise and the precision with which the optical thickness of a sample can be profiled, which can lead to images with an axial resolution of a few nanometres.
Subcellular controls of mercury trophic transfer to a marine fish.

PubMed

Dang, Fei; Wang, Wen-Xiong

2010-09-15

Different behaviors of inorganic mercury [Hg(II)] and methylmercury (MeHg) during trophic transfer along the marine food chain have been widely reported, but the mechanisms are not fully understood. The bioavailability of ingested mercury, quantified by assimilation efficiency (AE), was investigated in a marine fish, the grunt Terapon jarbua, based on mercury subcellular partitioning in prey and purified subcellular fractions of prey tissues. The subcellular distribution of Hg(II) differed substantially among prey types, with cellular debris being a major (49-57% in bivalves) or secondary (14-19% in other prey) binding pool. However, MeHg distribution varied little among prey types, with most MeHg (43-79%) in heat-stable protein (HSP) fraction. The greater AEs measured for MeHg (90-94%) than for Hg(II) (23-43%) confirmed the findings of previous studies. Bioavailability of each purified subcellular fraction rather than the proposed trophically available metal (TAM) fraction could better elucidate mercury assimilation difference. Hg(II) associated with insoluble fraction (e.g. cellular debris) was less bioavailable than that in soluble fraction (e.g. HSP). However, subcellular distribution was shown to be less important for MeHg, with each fraction having comparable MeHg bioavailability. Subcellular distribution in prey should be an important consideration in mercury trophic transfer studies. 2010 Elsevier B.V. All rights reserved.
Intracellular Mannose Binding Lectin Mediates Subcellular Trafficking of HIV-1 gp120 in Neurons

PubMed Central

Teodorof, C; Divakar, S; Soontornniyomkij, B; Achim, CL; Kaul, M; Singh, KK

2014-01-01

Human immunodeficiency virus -1 (HIV-1) enters the brain early during infection and leads to severe neuronal damage and central nervous system impairment. HIV-1 envelope glycoprotein 120 (gp120), a neurotoxin, undergoes intracellular trafficking and transport across neurons; however mechanisms of gp120 trafficking in neurons are unclear. Our results show that mannose binding lectin (MBL) that binds to the N-linked mannose residues on gp120, participates in intravesicular packaging of gp120 in neuronal subcellular organelles and also in subcellular trafficking of these vesicles in neuronal cells. Perinuclear MBL:gp120 vesicular complexes were observed and MBL facilitated the subcellular trafficking of gp120 via the endoplasmic reticulum (ER) and Golgi vesicles. The functional carbohydrate recognition domain of MBL was required for perinuclear organization, distribution and subcellular trafficking of MBL:gp120 vesicular complexes. Nocodazole, an agent that depolymerizes the microtubule network, abolished the trafficking of MBL:gp120 vesicles, suggesting that these vesicular complexes were transported along the microtubule network. Live cell imaging confirmed the association of the MBL:gp120 complexes with dynamic subcellular vesicles that underwent trafficking in neuronal soma and along the neurites. Thus, our findings suggest that intracellular MBL mediates subcellular trafficking and transport of viral glycoproteins in a microtubule-dependent mechanism in the neurons. PMID:24825317
Intracellular mannose binding lectin mediates subcellular trafficking of HIV-1 gp120 in neurons.

PubMed

Teodorof, C; Divakar, S; Soontornniyomkij, B; Achim, C L; Kaul, M; Singh, K K

2014-09-01

Human immunodeficiency virus-1 (HIV-1) enters the brain early during infection and leads to severe neuronal damage and central nervous system impairment. HIV-1 envelope glycoprotein 120 (gp120), a neurotoxin, undergoes intracellular trafficking and transport across neurons; however mechanisms of gp120 trafficking in neurons are unclear. Our results show that mannose binding lectin (MBL) that binds to the N-linked mannose residues on gp120, participates in intravesicular packaging of gp120 in neuronal subcellular organelles and also in subcellular trafficking of these vesicles in neuronal cells. Perinuclear MBL:gp120 vesicular complexes were observed and MBL facilitated the subcellular trafficking of gp120 via the endoplasmic reticulum (ER) and Golgi vesicles. The functional carbohydrate recognition domain of MBL was required for perinuclear organization, distribution and subcellular trafficking of MBL:gp120 vesicular complexes. Nocodazole, an agent that depolymerizes the microtubule network, abolished the trafficking of MBL:gp120 vesicles, suggesting that these vesicular complexes were transported along the microtubule network. Live cell imaging confirmed the association of the MBL:gp120 complexes with dynamic subcellular vesicles that underwent trafficking in neuronal soma and along the neurites. Thus, our findings suggest that intracellular MBL mediates subcellular trafficking and transport of viral glycoproteins in a microtubule-dependent mechanism in the neurons. Published by Elsevier Inc.
Heterobimetallic Pd–K carbene complexes via one-electron reductions of palladium radical carbenes

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

Cui, Peng; Hoffbauer, Melissa R.; Vyushkova, Mariya

2016-03-24

Unprecedented sequential substitution/reduction synthetic strategy on the Pd radical carbenes afforded heterobimetallic Pd–K carbene complexes, which features novel Pd–C carbene–K structural moieties.

Heterobimetallic Pd–K carbene complexes via one-electron reductions of palladium radical carbenes

DOE PAGES

Cui, Peng; Hoffbauer, Melissa R.; Vyushkova, Mariya; ...

2016-01-01

Unprecedented sequential substitution/reduction synthetic strategy on the Pd radical carbenes afforded heterobimetallic Pd–K carbene complexes, which features novel Pd–C carbene–K structural moieties.
Instructor Support Feature Guidelines. Volume 2.

DTIC Science & Technology

1986-05-01

starts his final approach, the display formats change to provide graphic depictions of glideslope, lineup and airspeed parameters, and indications of...and evaluate several facets of student performance simultaneously . It may also provide objective, standardized performance measurement of the student’s...procedures monitoring feature shall provide the instructor cation with a method of monitoring the sequential mission training activities of a student. The
Research on aviation unsafe incidents classification with improved TF-IDF algorithm

NASA Astrophysics Data System (ADS)

Wang, Yanhua; Zhang, Zhiyuan; Huo, Weigang

2016-05-01

The text content of Aviation Safety Confidential Reports contains a large number of valuable information. Term frequency-inverse document frequency algorithm is commonly used in text analysis, but it does not take into account the sequential relationship of the words in the text and its role in semantic expression. According to the seven category labels of civil aviation unsafe incidents, aiming at solving the problems of TF-IDF algorithm, this paper improved TF-IDF algorithm based on co-occurrence network; established feature words extraction and words sequential relations for classified incidents. Aviation domain lexicon was used to improve the accuracy rate of classification. Feature words network model was designed for multi-documents unsafe incidents classification, and it was used in the experiment. Finally, the classification accuracy of improved algorithm was verified by the experiments.
Reflectance confocal microscopy of oral epithelial tissue using an electrically tunable lens

NASA Astrophysics Data System (ADS)

Jabbour, Joey M.; Malik, Bilal H.; Cuenca, Rodrigo; Cheng, Shuna; Jo, Javier A.; Cheng, Yi-Shing L.; Wright, John M.; Maitland, Kristen C.

2014-02-01

We present the use of a commercially available electrically tunable lens to achieve axial scanning in a reflectance confocal microscope. Over a 255 μm axial scan range, the lateral and axial resolutions varied from 1-2 μm and 4-14 μm, respectively, dependent on the variable focal length of the tunable lens. Confocal imaging was performed on normal human biopsies from the oral cavity ex vivo. Sub-cellular morphologic features were seen throughout the depth of the epithelium while axially scanning using the focus tunable lens.
Predicting protein submitochondrial locations using a K-Nearest neighbor method based on the Bit-Score weighted euclidean distance

USDA-ARS?s Scientific Manuscript database

Mitochondria are essential subcellular organelles found in eukaryotic cells. Knowing information on a protein’s subcellular or sub subcellular location provides in-depth insights about the microenvironment where it interacts with other molecules and is crucial for inferring the protein’s function. T...
Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning.

PubMed

Mei, Suyu

2012-10-07

Recent years have witnessed much progress in computational modeling for protein subcellular localization. However, there are far few computational models for predicting plant protein subcellular multi-localization. In this paper, we propose a multi-label multi-kernel transfer learning model for predicting multiple subcellular locations of plant proteins (MLMK-TLM). The method proposes a multi-label confusion matrix and adapts one-against-all multi-class probabilistic outputs to multi-label learning scenario, based on which we further extend our published work MK-TLM (multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization) for plant protein subcellular multi-localization. By proper homolog knowledge transfer, MLMK-TLM is applicable to novel plant protein subcellular localization in multi-label learning scenario. The experiments on plant protein benchmark dataset show that MLMK-TLM outperforms the baseline model. Unlike the existing models, MLMK-TLM also reports its misleading tendency, which is important for comprehensive survey of model's multi-labeling performance. Copyright © 2012 Elsevier Ltd. All rights reserved.
Sub-cellular force microscopy in single normal and cancer cells.

PubMed

Babahosseini, H; Carmichael, B; Strobl, J S; Mahmoodi, S N; Agah, M

2015-08-07

This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer and significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. Copyright © 2015 Elsevier Inc. All rights reserved.
Three-body effects in the Hoyle-state decay

NASA Astrophysics Data System (ADS)

Refsgaard, J.; Fynbo, H. O. U.; Kirsebom, O. S.; Riisager, K.

2018-04-01

We use a sequential R-matrix model to describe the breakup of the Hoyle state into three α particles via the ground state of 8Be. It is shown that even in a sequential picture, features resembling a direct breakup branch appear in the phase-space distribution of the α particles. We construct a toy model to describe the Coulomb interaction in the three-body final state and its effects on the decay spectrum are investigated. The framework is also used to predict the phase-space distribution of the α particles emitted in a direct breakup of the Hoyle state and the possibility of interference between a direct and sequential branch is discussed. Our numerical results are compared to the current upper limit on the direct decay branch determined in recent experiments.
The Fate of Visible Features of Invisible Elements

PubMed Central

Herzog, Michael H.; Otto, Thomas U.; Ögmen, Haluk

2012-01-01

To investigate the integration of features, we have developed a paradigm in which an element is rendered invisible by visual masking. Still, the features of the element are visible as part of other display elements presented at different locations and times (sequential metacontrast). In this sense, we can “transport” features non-retinotopically across space and time. The features of the invisible element integrate with features of other elements if and only if the elements belong to the same spatio-temporal group. The mechanisms of this kind of feature integration seem to be quite different from classical mechanisms proposed for feature binding. We propose that feature processing, binding, and integration occur concurrently during processes that group elements into wholes. PMID:22557985
Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

PubMed

Wang, Xiao; Li, Guo-Zheng

2013-03-12

Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.
Full Intelligent Cancer Classification of Thermal Breast Images to Assist Physician in Clinical Diagnostic Applications

PubMed Central

Lashkari, AmirEhsan; Pak, Fatemeh; Firouzmand, Mohammad

2016-01-01

Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more than 75% – 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy. Infra-red breast thermography is an imaging technique based on recording temperature distribution patterns of breast tissue. Compared with breast mammography technique, thermography is more suitable technique because it is noninvasive, non-contact, passive and free ionizing radiation. In this paper, a full automatic high accuracy technique for classification of suspicious areas in thermogram images with the aim of assisting physicians in early detection of breast cancer has been presented. Proposed algorithm consists of four main steps: pre-processing & segmentation, feature extraction, feature selection and classification. At the first step, using full automatic operation, region of interest (ROI) determined and the quality of image improved. Using thresholding and edge detection techniques, both right and left breasts separated from each other. Then relative suspected areas become segmented and image matrix normalized due to the uniqueness of each person's body temperature. At feature extraction stage, 23 features, including statistical, morphological, frequency domain, histogram and Gray Level Co-occurrence Matrix (GLCM) based features are extracted from segmented right and left breast obtained from step 1. To achieve the best features, feature selection methods such as minimum Redundancy and Maximum Relevance (mRMR), Sequential Forward Selection (SFS), Sequential Backward Selection (SBS), Sequential Floating Forward Selection (SFFS), Sequential Floating Backward Selection (SFBS) and Genetic Algorithm (GA) have been used at step 3. Finally to classify and TH labeling procedures, different classifiers such as AdaBoost, Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naïve Bayes (NB) and probability Neural Network (PNN) are assessed to find the best suitable one. These steps are applied on different thermogram images degrees. The results obtained on native database showed the best and significant performance of the proposed algorithm in comprise to the similar studies. According to experimental results, GA combined with AdaBoost with the mean accuracy of 85.33% and 87.42% on the left and right breast images with 0 degree, GA combined with AdaBoost with mean accuracy of 85.17% on the left breast images with 45 degree and mRMR combined with AdaBoost with mean accuracy of 85.15% on the right breast images with 45 degree, and also GA combined with AdaBoost with a mean accuracy of 84.67% and 86.21%, on the left and right breast images with 90 degree, are the best combinations of feature selection and classifier for evaluation of breast images. PMID:27014608
On the origin of reproducible sequential activity in neural circuits

NASA Astrophysics Data System (ADS)

Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.
On the origin of reproducible sequential activity in neural circuits.

PubMed

Afraimovich, V S; Zhigulin, V P; Rabinovich, M I

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.
Using multiscale texture and density features for near-term breast cancer risk analysis

PubMed Central

Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

2015-01-01

Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038
Optogenetic Tools for Subcellular Applications in Neuroscience.

PubMed

Rost, Benjamin R; Schneider-Warme, Franziska; Schmitz, Dietmar; Hegemann, Peter

2017-11-01

The ability to study cellular physiology using photosensitive, genetically encoded molecules has profoundly transformed neuroscience. The modern optogenetic toolbox includes fluorescent sensors to visualize signaling events in living cells and optogenetic actuators enabling manipulation of numerous cellular activities. Most optogenetic tools are not targeted to specific subcellular compartments but are localized with limited discrimination throughout the cell. Therefore, optogenetic activation often does not reflect context-dependent effects of highly localized intracellular signaling events. Subcellular targeting is required to achieve more specific optogenetic readouts and photomanipulation. Here we first provide a detailed overview of the available optogenetic tools with a focus on optogenetic actuators. Second, we review established strategies for targeting these tools to specific subcellular compartments. Finally, we discuss useful tools and targeting strategies that are currently missing from the optogenetics repertoire and provide suggestions for novel subcellular optogenetic applications. Copyright © 2017 Elsevier Inc. All rights reserved.
Modeling of Protein Subcellular Localization in Bacteria

NASA Astrophysics Data System (ADS)

Xu, Xiaohua; Kulkarni, Rahul

2006-03-01

Specific subcellular localization of proteins is a vital component of important bacterial processes: e.g. the Min proteins which regulate cell division in E. coli and Spo0J-Soj system which is critical for sporulation in B. subtilis. We examine how the processes of diffusion and membrane attachment contribute to protein subcellular localization for the above systems. We use previous experimental results to suggest minimal models for these processes. For the minimal models, we derive analytic expressions which provide insight into the processes that determine protein subcellular localization. Finally, we present the results of numerical simulations for the systems studied and make connections to the observed experiemental phenomenology.
LOCATE: a mouse protein subcellular localization database

PubMed Central

Fink, J. Lynn; Aturaliya, Rajith N.; Davis, Melissa J.; Zhang, Fasheng; Hanson, Kelly; Teasdale, Melvena S.; Kai, Chikatoshi; Kawai, Jun; Carninci, Piero; Hayashizaki, Yoshihide; Teasdale, Rohan D.

2006-01-01

We present here LOCATE, a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set. Membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing >1700 peer-reviewed publications. LOCATE represents the first effort to catalogue the experimentally verified subcellular location and membrane organization of mammalian proteins using a high-throughput approach and provides localization data for ∼40% of the mouse proteome. It is available at . PMID:16381849
Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems

PubMed Central

Schubert, Walter

2013-01-01

Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described—a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (<40 nm distances). It is shown that the subcellular and transcellular features of such supermolecules can be described at the compositional and constitutional levels; that the spatial connection, relational stoichiometry, and topology of supermolecules generate hitherto unrecognized functional self-segmentation of biological tissues; that hierarchical features, common to thousands of simultaneously imaged supermolecules, can be identified; and how the resulting supramolecular order relates to spatial coding of cellular functionalities in biological systems. A large body of observations with IC molecular systems microscopy collected over 20 years have disclosed principles governed by a law of supramolecular segregation of cellular functionalities. This pervades phenomena, such as exceptional orderliness, functional selectivity, combinatorial and spatial periodicity, and hierarchical organization of large molecular systems, across all species investigated so far. This insight is based on the high degree of specificity, selectivity, and sensitivity of molecular recognition processes for fluorescence imaging beyond the spectral resolution limit, using probe libraries controlled by ICs. © 2013 The Authors. Journal of Molecular Recognition published by John Wiley & Sons, Ltd. PMID:24375580
Identification and Molecular Characterization of the Chloroplast Targeting Domain of Turnip yellow mosaic virus Replication Proteins

PubMed Central

Moriceau, Lucille; Jomat, Lucile; Bressanelli, Stéphane; Alcaide-Loridan, Catherine; Jupin, Isabelle

2017-01-01

Turnip yellow mosaic virus (TYMV) is a positive-strand RNA virus infecting plants. The TYMV 140K replication protein is a key organizer of viral replication complex (VRC) assembly, being responsible for recruitment of the viral polymerase and for targeting the VRCs to the chloroplast envelope where viral replication takes place. However, the structural requirements determining the subcellular localization and membrane association of this essential viral protein have not yet been defined. In this study, we investigated determinants for the in vivo chloroplast targeting of the TYMV 140K replication protein. Subcellular localization studies of deletion mutants identified a 41-residue internal sequence as the chloroplast targeting domain (CTD) of TYMV 140K; this sequence is sufficient to target GFP to the chloroplast envelope. The CTD appears to be located in the C-terminal extension of the methyltransferase domain—a region shared by 140K and its mature cleavage product 98K, which behaves as an integral membrane protein during infection. We predicted the CTD to fold into two amphipathic α-helices—a folding that was confirmed in vitro by circular dichroism spectroscopy analyses of a synthetic peptide. The importance for subcellular localization of the integrity of these amphipathic helices, and the function of 140K/98K, was demonstrated by performing amino acid substitutions that affected chloroplast targeting, membrane association and viral replication. These results establish a short internal α-helical peptide as an unusual signal for targeting proteins to the chloroplast envelope membrane, and provide new insights into membrane targeting of viral replication proteins—a universal feature of positive-strand RNA viruses. PMID:29312393
Real and Non-Real Time Interaction: Unraveling Multiple Threads of Discourse.

ERIC Educational Resources Information Center

Black, Steven D.; And Others

1983-01-01

Compares discourse in several different media and finds that strict sequentiality is not a universal feature of discourse. Concludes that discourse in nonreal time media, such as electronic message systems, has multiple threads. (FL)

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.
Intelligent feature selection techniques for pattern classification of Lamb wave signals

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

Hinders, Mark K.; Miller, Corey A.

2014-02-18

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crossholemore » tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy.« less
Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Eils, Roland

2006-06-14

The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given protein when only the amino acid sequence of the protein is known. Although many efforts have been made to predict subcellular location from sequence information only, there is the need for further research to improve the accuracy of prediction. A novel method called HensBC is introduced to predict protein subcellular location. HensBC is a recursive algorithm which constructs a hierarchical ensemble of classifiers. The classifiers used are Bayesian classifiers based on Markov chain models. We tested our method on six various datasets; among them are Gram-negative bacteria dataset, data for discriminating outer membrane proteins and apoptosis proteins dataset. We observed that our method can predict the subcellular location with high accuracy. Another advantage of the proposed method is that it can improve the accuracy of the prediction of some classes with few sequences in training and is therefore useful for datasets with imbalanced distribution of classes. This study introduces an algorithm which uses only the primary sequence of a protein to predict its subcellular location. The proposed recursive scheme represents an interesting methodology for learning and combining classifiers. The method is computationally efficient and competitive with the previously reported approaches in terms of prediction accuracies as empirical results indicate. The code for the software is available upon request.
Finding the Subcellular Location of Barley, Wheat, Rice and Maize Proteins: The Compendium of Crop Proteins with Annotated Locations (cropPAL).

PubMed

Hooper, Cornelia M; Castleden, Ian R; Aryamanesh, Nader; Jacoby, Richard P; Millar, A Harvey

2016-01-01

Barley, wheat, rice and maize provide the bulk of human nutrition and have extensive industrial use as agricultural products. The genomes of these crops each contains >40,000 genes encoding proteins; however, the major genome databases for these species lack annotation information of protein subcellular location for >80% of these gene products. We address this gap, by constructing the compendium of crop protein subcellular locations called crop Proteins with Annotated Locations (cropPAL). Subcellular location is most commonly determined by fluorescent protein tagging of live cells or mass spectrometry detection in subcellular purifications, but can also be predicted from amino acid sequence or protein expression patterns. The cropPAL database collates 556 published studies, from >300 research institutes in >30 countries that have been previously published, as well as compiling eight pre-computed subcellular predictions for all Hordeum vulgare, Triticum aestivum, Oryza sativa and Zea mays protein sequences. The data collection including metadata for proteins and published studies can be accessed through a search portal http://crop-PAL.org. The subcellular localization information housed in cropPAL helps to depict plant cells as compartmentalized protein networks that can be investigated for improving crop yield and quality, and developing new biotechnological solutions to agricultural challenges. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks

NASA Astrophysics Data System (ADS)

Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

2016-01-01

The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named “DeepMethyl” to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.
Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.
Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks.

PubMed

Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

2016-01-22

The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named "DeepMethyl" to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.
High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels†

PubMed Central

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L.; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J.; Hierlemann, Andreas

2017-01-01

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm2). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons. PMID:25973786
Intermediate filament proteins of digestive organs: physiology and pathophysiology.

PubMed

Omary, M Bishr

2017-06-01

Intermediate filament proteins (IFs), such as cytoplasmic keratins in epithelial cells and vimentin in mesenchymal cells and the nuclear lamins, make up one of the three major cytoskeletal protein families. Whether in digestive organs or other tissues, IFs share several unique features including stress-inducible overexpression, abundance, cell-selective and differentiation state expression, and association with >80 human diseases when mutated. Whereas most IF mutations cause disease, mutations in simple epithelial keratins 8, 18, or 19 or in lamin A/C predispose to liver disease with or without other tissue manifestations. Keratins serve major functions including protection from apoptosis, providing cellular and subcellular mechanical integrity, protein targeting to subcellular compartments, and scaffolding and regulation of cell-signaling processes. Keratins are essential for Mallory-Denk body aggregate formation that occurs in association with several liver diseases, whereas an alternate type of keratin and lamin aggregation occurs upon liver involvement in porphyria. IF-associated diseases have no known directed therapy, but high-throughput drug screening to identify potential therapies is an appealing ongoing approach. Despite the extensive current knowledge base, much remains to be discovered regarding IF physiology and pathophysiology in digestive and nondigestive organs. Copyright © 2017 the American Physiological Society.
High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels.

PubMed

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J; Hierlemann, Andreas

2015-07-07

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm(2)). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.
PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

PubMed

Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

2010-07-01

PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.
Protein subcellular localization prediction using multiple kernel learning based support vector machine.

PubMed

Hasan, Md Al Mehedi; Ahmad, Shamim; Molla, Md Khademul Islam

2017-03-28

Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered proteins has been growing exponentially, which in turns, makes the subcellular localization prediction by purely laboratory tests prohibitively laborious and expensive. In this context, to tackle the challenges, computational methods are being developed as an alternative choice to aid biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging issue, particularly, when query proteins have multi-label characteristics, i.e., if they exist simultaneously in more than one subcellular location or if they move between two or more different subcellular locations. To date, to address this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM) has been employed to provide potential solutions to the protein subcellular localization prediction problem. However, the practicability of an SVM is affected by the challenges of selecting an appropriate kernel and selecting the parameters of the selected kernel. To address this difficulty, in this study, we aimed to develop an efficient multi-label protein subcellular localization prediction system, named as MKLoc, by introducing multiple kernel learning (MKL) based SVM. We evaluated MKLoc using a combined dataset containing 5447 single-localized proteins (originally published as part of the Höglund dataset) and 3056 multi-localized proteins (originally published as part of the DBMLoc set). Note that this dataset was used by Briesemeister et al. in their extensive comparison of multi-localization prediction systems. Finally, our experimental results indicate that MKLoc not only achieves higher accuracy than a single kernel based SVM system but also shows significantly better results than those obtained from other top systems (MDLoc, BNCs, YLoc+). Moreover, MKLoc requires less computation time to tune and train the system than that required for BNCs and single kernel based SVM.
Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

NASA Astrophysics Data System (ADS)

Xie, Yaoqin; Xing, Lei; Gu, Jia; Liu, Wu

2013-06-01

Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow.
Conformational Clusters of Phosphorylated Tyrosine.

PubMed

Abdelrasoul, Maha; Ponniah, Komala; Mao, Alice; Warden, Meghan S; Elhefnawy, Wessam; Li, Yaohang; Pascal, Steven M

2017-12-06

Tyrosine phosphorylation plays an important role in many cellular and intercellular processes including signal transduction, subcellular localization, and regulation of enzymatic activity. In 1999, Blom et al., using the limited number of protein data bank (PDB) structures available at that time, reported that the side chain structures of phosphorylated tyrosine (pY) are partitioned into two conserved conformational clusters ( Blom, N.; Gammeltoft, S.; Brunak, S. J. Mol. Biol. 1999 , 294 , 1351 - 1362 ). We have used the spectral clustering algorithm to cluster the increasingly growing number of protein structures with pY sites, and have found that the pY residues cluster into three distinct side chain conformations. Two of these pY conformational clusters associate strongly with a narrow range of tyrosine backbone conformation. The novel cluster also highly correlates with the identity of the n + 1 residue, and is strongly associated with a sequential pYpY conformation which places two adjacent pY side chains in a specific relative orientation. Further analysis shows that the three pY clusters are associated with distinct distributions of cognate protein kinases.
Characterizing the Specificity and Co-operation of Aminopeptidases in the Cytosol and ER During MHC Class I antigen Presentation1

PubMed Central

Hearn, Arron; York, Ian A.; Bishop, Courtney; Rock, Kenneth L.

2010-01-01

Many MHC class I binding peptides are generated as N-extended precursors during protein degradation by the proteasome. These peptides can be subsequently trimmed by aminopeptidases in the cytosol and/or the ER to produce mature epitope. However, the contribution and specificity of each of these subcellular compartments in removing N-terminal amino acids for antigen presentation is not well defined. Here we investigate this issue for antigenic precursors that are expressed in the cytosol. By systematically varying the N-terminal flanking sequences of peptides we show that the amino acids upstream of an epitope precursor are a major determinant of the amount of antigen presentation. In many cases MHC class I binding peptides are produced through sequential trimming in both the cytosol and ER. Trimming of flanking residues in the cytosol contributes most to sequences that are poorly trimmed in the ER. Since N-terminal trimming has different specificity in the cytosol and ER, the cleavage of peptides in both of these compartments serves to broaden the repertoire of sequences that are presented. PMID:20351195
Role of PIN-mediated auxin efflux in apical hook development of Arabidopsis thaliana.

PubMed

Zádníková, Petra; Petrásek, Jan; Marhavy, Peter; Raz, Vered; Vandenbussche, Filip; Ding, Zhaojun; Schwarzerová, Katerina; Morita, Miyo T; Tasaka, Masao; Hejátko, Jan; Van Der Straeten, Dominique; Friml, Jirí; Benková, Eva

2010-02-01

The apical hook of dark-grown Arabidopsis seedlings is a simple structure that develops soon after germination to protect the meristem tissues during emergence through the soil and that opens upon exposure to light. Differential growth at the apical hook proceeds in three sequential steps that are regulated by multiple hormones, principally auxin and ethylene. We show that the progress of the apical hook through these developmental phases depends on the dynamic, asymmetric distribution of auxin, which is regulated by auxin efflux carriers of the PIN family. Several PIN proteins exhibited specific, partially overlapping spatial and temporal expression patterns, and their subcellular localization suggested auxin fluxes during hook development. Genetic manipulation of individual PIN activities interfered with different stages of hook development, implying that specific combinations of PIN genes are required for progress of the apical hook through the developmental phases. Furthermore, ethylene might modulate apical hook development by prolonging the formation phase and strongly suppressing the maintenance phase. This ethylene effect is in part mediated by regulation of PIN-dependent auxin efflux and auxin signaling.
Identification of cell wall proteins in the flax (Linum usitatissimum) stem.

PubMed

Day, Arnaud; Fénart, Stéphane; Neutelings, Godfrey; Hawkins, Simon; Rolando, Christian; Tokarski, Caroline

2013-03-01

Sequential salt (CaCl2 , LiCl) extractions were used to obtain fractions enriched in cell wall proteins (CWPs) from the stem of 60-day-old flax (Linum usitatissimum) plants. High-resolution FT-ICR MS analysis and the use of recently published genomic data allowed the identification of 11 912 peptides corresponding to a total of 1418 different proteins. Subcellular localization using TargetP, Predotar, and WoLF PSORT led to the identification of 152 putative flax CWPs that were classified into nine different functional classes previously established for Arabidopsis thaliana. Examination of different functional classes revealed the presence of a number of proteins known to be involved in, or potentially involved in cell-wall metabolism in plants. The flax stem cell wall proteome was also compared with transcriptomic data previously obtained on comparable samples. This study represents a major contribution to the identification of CWPs in flax and will lead to a better understanding of cell wall biology in this species. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Visual perception as retrospective Bayesian decoding from high- to low-level features

PubMed Central

Ding, Stephanie; Cueva, Christopher J.; Tsodyks, Misha; Qian, Ning

2017-01-01

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. PMID:29073108
Optogenetic stimulation of myelination (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yang, In Hong; Lee, Hae Ung; Thakor, Nitish V.

2016-03-01

Myelination is governed by axon-glia interaction which is modulated by neural activity. Currently, the effects of subcellular activation of neurons which induce neural activity upon myelination are not well understood. To identify if subcellular neuronal stimulation can enhance myelination, we developed a novel system for focal stimulation of neural activity with optogenetic in a compartmentalized microfluidic platform. In our systems, stimulation for neurons in restricted subcellular parts, such as cell bodies and axons promoted oligodendrocyte differentiation and the myelination of axons the just as much as whole cell activation of neurons did. The number of premature O4 positive oligodendrocytes was reduced and the numbers of mature and myelin basic protein-positive oligodendrocytes was increased both by subcellular optogenetic stimulation.
Visualizing Single Cell Biology: Nanosims Studies of Carbon and Nitrogen Metabolism in Diazotrophic Cyanobacteria

NASA Astrophysics Data System (ADS)

Pett-Ridge, J.; Finzi, J. A.; Capone, D. G.; Popa, R.; Nealson, K. H.; Ng, W.; Spormann, A. M.; Hutcheon, I. D.; Weber, P. K.

2007-12-01

Filamentous nitrogen fixing (diazotrophic) cyanobacteria are key players in global nutrient cycling, but the relationship between CO2- and N2-fixation and intercellular exchange of these elements remains poorly understood in many genera. These bacteria are faced with the challenge of isolating regions of N-fixation (O2 inhibited) and photosynthetic (O2 producing) activity. We used isotope labeling in conjunction with a high-resolution isotope and elemental mapping technique (NanoSIMS) to quantitatively describe 13C and 15N uptake and transport in two aquatic cyanobacteria grown on NaH13CO3 and 15N2. The technical challenges of tracing isotopes within individual bacteria can be overcome with high resolution Secondary Ion Mass Spectrometry (NanoSIMS). In NanoSIMS analysis, samples are sputtered with an energetic primary beam (Cs+, O-) liberating secondary ions that are separated by the mass spectrometer and detected in a suite of electron multipliers. Five isotopic species may be analyzed concurrently with spatial resolution as fine as 50nm. A high sensitivity isotope ratio 'map' can then be generated for the analyzed area. Using sequentially harvested cyanobacteria in conjunction with enriched H13CO3 and 15N2 incubations, we measured temporal enrichment patterns that evolve over the course of a day's growth and suggest tightly regulated changes in fixation kinetics. With a combination of TEM, SEM and NanoSIMS analyses, we also mapped the distribution of C, N and Mo (a critical nitrogenase co-factor) isotopes in intact cells. Our results suggest that NanoSIMS mapping of metal enzyme co-factors may be a powerful method of identifying physiological and morphological characteristics within individual bacterial cells, and could be used to provide a 3-dimensional context for more traditional analyses such as immunogold labeling. Finally, we resolved patterns of isotope enrichment at multiple spatial scales: sub-cellular variation, cell-cell differences along filaments, inter-species transfers (with Rhizobium epibionts), and within-cell depth profiles. Spatial enrichment patterns were correlated with morphological features evidenced in TEM images of microtomed filaments. These features indicate how 15N and 13C "hotspots" are dispersed throughout individual cells in different species, and may indicate isolated locations of increased N2 fixation, sites of amino acid/protein synthesis, or cyanophycin storage granules. This combination of Nano-Secondary Ion Mass Spectrometry (NanoSIMS) analysis and high resolution microscopy allows isotopic analysis to be linked to morphological features and holds great promise for fine-scale studies of bacteria metabolism.

Subcellular glucose exposure biases the spatial distribution of insulin granules in single pancreatic beta cells.

PubMed

Terao, Kyohei; Gel, Murat; Okonogi, Atsuhito; Fuke, Ariko; Okitsu, Teru; Tada, Takashi; Suzuki, Takaaki; Nagamatsu, Shinya; Washizu, Masao; Kotera, Hidetoshi

2014-02-18

In living tissues, a cell is exposed to chemical substances delivered partially to its surface. Such a heterogeneous chemical environment potentially induces cell polarity. To evaluate this effect, we developed a microfluidic device that realizes spatially confined delivery of chemical substances at subcellular resolution. Our microfluidic device allows simple setup and stable operation for over 4 h to deliver chemicals partially to a single cell. Using the device, we showed that subcellular glucose exposure triggers an intracellular [Ca(2+)] change in the β-cells. In addition, the imaging of a cell expressing GFP-tagged insulin showed that continuous subcellular exposure to glucose biased the spatial distribution of insulin granules toward the site where the glucose was delivered. Our approach illustrates an experimental technique that will be applicable to many biological experiments for imaging the response to subcellular chemical exposure and will also provide new insights about the development of polarity of β-cells.
Subcellular glucose exposure biases the spatial distribution of insulin granules in single pancreatic beta cells

PubMed Central

Terao, Kyohei; Gel, Murat; Okonogi, Atsuhito; Fuke, Ariko; Okitsu, Teru; Tada, Takashi; Suzuki, Takaaki; Nagamatsu, Shinya; Washizu, Masao; Kotera, Hidetoshi

2014-01-01

In living tissues, a cell is exposed to chemical substances delivered partially to its surface. Such a heterogeneous chemical environment potentially induces cell polarity. To evaluate this effect, we developed a microfluidic device that realizes spatially confined delivery of chemical substances at subcellular resolution. Our microfluidic device allows simple setup and stable operation for over 4 h to deliver chemicals partially to a single cell. Using the device, we showed that subcellular glucose exposure triggers an intracellular [Ca2+] change in the β-cells. In addition, the imaging of a cell expressing GFP-tagged insulin showed that continuous subcellular exposure to glucose biased the spatial distribution of insulin granules toward the site where the glucose was delivered. Our approach illustrates an experimental technique that will be applicable to many biological experiments for imaging the response to subcellular chemical exposure and will also provide new insights about the development of polarity of β-cells. PMID:24535122
A draft map of the mouse pluripotent stem cell spatial proteome

PubMed Central

Christoforou, Andy; Mulvey, Claire M.; Breckels, Lisa M.; Geladaki, Aikaterini; Hurrell, Tracey; Hayward, Penelope C.; Naake, Thomas; Gatto, Laurent; Viner, Rosa; Arias, Alfonso Martinez; Lilley, Kathryn S.

2016-01-01

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data. PMID:26754106
BUSCA: an integrative web server to predict subcellular localization of proteins.

PubMed

Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Profiti, Giuseppe; Casadio, Rita

2018-04-30

Here, we present BUSCA (http://busca.biocomp.unibo.it), a novel web server that integrates different computational tools for predicting protein subcellular localization. BUSCA combines methods for identifying signal and transit peptides (DeepSig and TPpred3), GPI-anchors (PredGPI) and transmembrane domains (ENSEMBLE3.0 and BetAware) with tools for discriminating subcellular localization of both globular and membrane proteins (BaCelLo, MemLoci and SChloro). Outcomes from the different tools are processed and integrated for annotating subcellular localization of both eukaryotic and bacterial protein sequences. We benchmark BUSCA against protein targets derived from recent CAFA experiments and other specific data sets, reporting performance at the state-of-the-art. BUSCA scores better than all other evaluated methods on 2732 targets from CAFA2, with a F1 value equal to 0.49 and among the best methods when predicting targets from CAFA3. We propose BUSCA as an integrated and accurate resource for the annotation of protein subcellular localization.
The parallel-sequential field subtraction techniques for nonlinear ultrasonic imaging

NASA Astrophysics Data System (ADS)

Cheng, Jingwei; Potter, Jack N.; Drinkwater, Bruce W.

2018-04-01

Nonlinear imaging techniques have recently emerged which have the potential to detect cracks at a much earlier stage and have sensitivity to particularly closed defects. This study utilizes two modes of focusing: parallel, in which the elements are fired together with a delay law, and sequential, in which elements are fired independently. In the parallel focusing, a high intensity ultrasonic beam is formed in the specimen at the focal point. However, in sequential focusing only low intensity signals from individual elements enter the sample and the full matrix of transmit-receive signals is recorded; with elastic assumptions, both parallel and sequential images are expected to be identical. Here we measure the difference between these images formed from the coherent component of the field and use this to characterize nonlinearity of closed fatigue cracks. In particular we monitor the reduction in amplitude at the fundamental frequency at each focal point and use this metric to form images of the spatial distribution of nonlinearity. The results suggest the subtracted image can suppress linear features (e.g., back wall or large scatters) and allow damage to be detected at an early stage.
Quantitative Analysis of Subcellular Distribution of the SUMO Conjugation System by Confocal Microscopy Imaging.

PubMed

Mas, Abraham; Amenós, Montse; Lois, L Maria

2016-01-01

Different studies point to an enrichment in SUMO conjugation in the cell nucleus, although non-nuclear SUMO targets also exist. In general, the study of subcellular localization of proteins is essential for understanding their function within a cell. Fluorescence microscopy is a powerful tool for studying subcellular protein partitioning in living cells, since fluorescent proteins can be fused to proteins of interest to determine their localization. Subcellular distribution of proteins can be influenced by binding to other biomolecules and by posttranslational modifications. Sometimes these changes affect only a portion of the protein pool or have a partial effect, and a quantitative evaluation of fluorescence images is required to identify protein redistribution among subcellular compartments. In order to obtain accurate data about the relative subcellular distribution of SUMO conjugation machinery members, and to identify the molecular determinants involved in their localization, we have applied quantitative confocal microscopy imaging. In this chapter, we will describe the fluorescent protein fusions used in these experiments, and how to measure, evaluate, and compare average fluorescence intensities in cellular compartments by image-based analysis. We show the distribution of some components of the Arabidopsis SUMOylation machinery in epidermal onion cells and how they change their distribution in the presence of interacting partners or even when its activity is affected.
Cell biology of prokaryotic organelles.

PubMed

Murat, Dorothee; Byrne, Meghan; Komeili, Arash

2010-10-01

Mounting evidence in recent years has challenged the dogma that prokaryotes are simple and undefined cells devoid of an organized subcellular architecture. In fact, proteins once thought to be the purely eukaryotic inventions, including relatives of actin and tubulin control prokaryotic cell shape, DNA segregation, and cytokinesis. Similarly, compartmentalization, commonly noted as a distinguishing feature of eukaryotic cells, is also prevalent in the prokaryotic world in the form of protein-bounded and lipid-bounded organelles. In this article we highlight some of these prokaryotic organelles and discuss the current knowledge on their ultrastructure and the molecular mechanisms of their biogenesis and maintenance.
Sequential strand displacement beacon for detection of DNA coverage on functionalized gold nanoparticles.

PubMed

Paliwoda, Rebecca E; Li, Feng; Reid, Michael S; Lin, Yanwen; Le, X Chris

2014-06-17

Functionalizing nanomaterials for diverse analytical, biomedical, and therapeutic applications requires determination of surface coverage (or density) of DNA on nanomaterials. We describe a sequential strand displacement beacon assay that is able to quantify specific DNA sequences conjugated or coconjugated onto gold nanoparticles (AuNPs). Unlike the conventional fluorescence assay that requires the target DNA to be fluorescently labeled, the sequential strand displacement beacon method is able to quantify multiple unlabeled DNA oligonucleotides using a single (universal) strand displacement beacon. This unique feature is achieved by introducing two short unlabeled DNA probes for each specific DNA sequence and by performing sequential DNA strand displacement reactions. Varying the relative amounts of the specific DNA sequences and spacing DNA sequences during their coconjugation onto AuNPs results in different densities of the specific DNA on AuNP, ranging from 90 to 230 DNA molecules per AuNP. Results obtained from our sequential strand displacement beacon assay are consistent with those obtained from the conventional fluorescence assays. However, labeling of DNA with some fluorescent dyes, e.g., tetramethylrhodamine, alters DNA density on AuNP. The strand displacement strategy overcomes this problem by obviating direct labeling of the target DNA. This method has broad potential to facilitate more efficient design and characterization of novel multifunctional materials for diverse applications.
Ultra-spatial synchrotron radiation for imaging molecular chemical structure: Applications in plant and animal studies

DOE PAGES

Yu, Peiqiang

2007-01-01

Synchrotron-based Fourier transform infrared microspectroscopy (S-FTIR) has been developed as a rapid, direct, non-destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical features and make-up within microstructures of a biological tissue without destruction of inherent structures at ultra-spatial resolutions within cellular dimension. To date there has been very little application of this advanced synchrotron technique to the study of plant and animal tissues' inherent structure at a cellular or subcellular level. In this article, a novel approach was introduced to show the potential of themore » newly developed, advanced synchrotron-based analytical technology, which can be used to reveal molecular structural-chemical features of various plant and animal tissues.« less
Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

PubMed Central

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-01-01

Purpose: Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis (CAD) schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification. Methods: We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features, and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest (ROIs), we performed the study using a ten-fold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only. Results: The area under the receiver operating characteristic curve (AUC) = 0.805±0.012 was obtained for the classification task. The results also showed that the most frequently-selected features by the SFFS-based algorithm in 10-fold iterations were those related to mass shape, isodensity and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions. Conclusions: In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be useful as a “second reader” in future clinical practice. PMID:24664267
Designing group sequential randomized clinical trials with time to event end points using a R function.

PubMed

Filleron, Thomas; Gal, Jocelyn; Kramar, Andrew

2012-10-01

A major and difficult task is the design of clinical trials with a time to event endpoint. In fact, it is necessary to compute the number of events and in a second step the required number of patients. Several commercial software packages are available for computing sample size in clinical trials with sequential designs and time to event endpoints, but there are a few R functions implemented. The purpose of this paper is to describe features and use of the R function. plansurvct.func, which is an add-on function to the package gsDesign which permits in one run of the program to calculate the number of events, and required sample size but also boundaries and corresponding p-values for a group sequential design. The use of the function plansurvct.func is illustrated by several examples and validated using East software. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Learning multiple variable-speed sequences in striatum via cortical tutoring.

PubMed

Murray, James M; Escola, G Sean

2017-05-08

Sparse, sequential patterns of neural activity have been observed in numerous brain areas during timekeeping and motor sequence tasks. Inspired by such observations, we construct a model of the striatum, an all-inhibitory circuit where sequential activity patterns are prominent, addressing the following key challenges: (i) obtaining control over temporal rescaling of the sequence speed, with the ability to generalize to new speeds; (ii) facilitating flexible expression of distinct sequences via selective activation, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausible learning of sequences, consistent with the decoupling of learning and execution suggested by lesion studies showing that cortical circuits are necessary for learning, but that subcortical circuits are sufficient to drive learned behaviors. The same mechanisms that we describe can also be applied to circuits with both excitatory and inhibitory populations, and hence may underlie general features of sequential neural activity pattern generation in the brain.
Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.
Peroxygenase-Catalyzed Fatty Acid Epoxidation in Cereal Seeds (Sequential Oxidation of Linoleic Acid into 9(S),12(S),13(S)-Trihydroxy-10(E)-Octadecenoic Acid).

PubMed Central

Hamberg, M.; Hamberg, G.

1996-01-01

Peroxygenase-catalyzed epoxidation of oleic acid in preparations of cereal seeds was investigated. The 105,000g particle fraction of oat (Avena sativa) seed homogenate showed high peroxygenase activity, i.e. 3034 [plus or minus] 288 and 2441 [plus or minus] 168 nmol (10 min)-1 mg-1 protein in two cultivars, whereas the corresponding fraction obtained from barley (Hordeum vulgare and Hordeum distichum), rye (Secale cereale), and wheat (Triticum aestivum) showed only weak activity, i.e. 13 to 138 nmol (10 min)-1 mg-1 protein. In subcellular fractions of oat seed homogenate, peroxygenase specific activity was highest in the 105,000g particle fraction, whereas lipoxygenase activity was more evenly distributed and highest in the 105,000g supernatant fraction. Incubation of [1-14C]linoleic acid with the 105,000g supernatant of oat seed homogenate led to the formation of several metabolites, i.e. in order of decreasing abundance, 9(S)-hydroxy-10(E),12(Z)-octadecadienoic acid, 9(S),12(S),13(S)-trihydroxy-10(E)-octadecenoic acid, cis-9,10-epoxy-12(Z)-octadecenoic acid [mainly the 9(R),10(S) enantiomer], cis-12,13-epoxy-9(Z)-octadecenoic acid [mainly the 12(R),13(S) enantiomer], threo-12,13-dihydroxy-9(Z)-octadecenoic acid, and 12(R),13(S)-epoxy-9(S)-hydroxy-10(E)-octadecenoic acid. Incubation of linoleic acid with the 105,000g particle fraction gave a similar, but not identical, pattern of metabolites. Conversion of linoleic acid into 9(S),12(S),13(S)-trihydroxy-10(E)-octadecenoic acid, a naturally occurring oxylipin with antifungal properties, took place by a pathway involving sequential catalysis by lipoxygenase, peroxygenase, and epoxide hydrolase. PMID:12226220
Dynamic Virus-Dependent Subnuclear Localization of the Capsid Protein from a Geminivirus

PubMed Central

Wang, Liping; Tan, Huang; Wu, Mengshi; Jimenez-Gongora, Tamara; Tan, Li; Lozano-Duran, Rosa

2017-01-01

Viruses are intracellular parasites with a nucleic acid genome and a proteinaceous capsid. Viral capsids are formed of at least one virus-encoded capsid protein (CP), which is often multifunctional, playing additional non-structural roles during the infection cycle. In animal viruses, there are examples of differential localization of CPs associated to the progression of the infection and/or enabled by other viral proteins; these changes in the distribution of CPs may ultimately regulate the involvement of these proteins in different viral functions. In this work, we analyze the subcellular localization of a GFP- or RFP-fused CP from the plant virus Tomato yellow leaf curl virus (TYLCV; Fam. Geminiviridae) in the presence or absence of the virus upon transient expression in the host plants Nicotiana benthamiana and tomato. Our findings show that, in agreement with previous reports, when the CP is expressed alone it localizes mainly in the nucleolus and weakly in the nucleoplasm. Interestingly, the presence of the virus causes the sequential re-localization of the CP outside of the nucleolus and into discrete nuclear foci and, eventually, into an uneven distribution in the nucleoplasm. Expression of the viral replication-associated protein, Rep, is sufficient to exclude the CP from the nucleolus, but the localization of the CP in the characteristic patterns induced by the virus cannot be recapitulated by co-expression with any individual viral protein. Our results demonstrate that the subcellular distribution of the CP is a dynamic process, temporally regulated throughout the progression of the infection. The regulation of the localization of the CP is determined by the presence of other viral components or changes in the cellular environment induced by the virus, and is likely to contribute to the multifunctionality of this protein. Bearing in mind these observations, we suggest that viral proteins should be studied in the context of the infection and considering the temporal dimension in order to comprehensively understand their roles and effects in the interaction between virus and host. PMID:29312406
Reporting and Reacting: Concurrent Responses to Reported Speech.

ERIC Educational Resources Information Center

Holt, Elizabeth

2000-01-01

Uses conversation analysis to investigate reported speech in talk-in-interaction. Beginning with an examination of direct and indirect reported speech, the article highlights some of the design features of the former, and the sequential environments in which it occurs. (Author/VWL)
Isolation and characterization of distinct domains of sarcolemma and T-tubules from rat skeletal muscle.

PubMed

Muñoz, P; Rosemblatt, M; Testar, X; Palacín, M; Zorzano, A

1995-04-01

1. Several cell-surface domains of sarcolemma and T-tubule from skeletal-muscle fibre were isolated and characterized. 2. A protocol of subcellular fractionation was set up that involved the sequential low- and high-speed homogenization of rat skeletal muscle followed by KCl washing, Ca2+ loading and sucrose-density-gradient centrifugation. This protocol led to the separation of cell-surface membranes from membranes enriched in sarcoplasmic reticulum and intracellular GLUT4-containing vesicles. 3. Agglutination of cell-surface membranes using wheat-germ agglutinin allowed the isolation of three distinct cell-surface membrane domains: sarcolemmal fraction 1 (SM1), sarcolemmal fraction 2 (SM2) and a T-tubule fraction enriched in protein tt28 and the alpha 2-component of dihydropyridine receptor. 4. Fractions SM1 and SM2 represented distinct sarcolemmal subcompartments based on different compositions of biochemical markers: SM2 was characterized by high levels of beta 1-integrin and dystrophin, and SM1 was enriched in beta 1-integrin but lacked dystrophin. 5. The caveolae-associated molecule caveolin was very abundant in SM1, SM2 and T-tubules, suggesting the presence of caveolae or caveolin-rich domains in these cell-surface membrane domains. In contrast, clathrin heavy chain was abundant in SM1 and T-tubules, but only trace levels were detected in SM2. 6. Immunoadsorption of T-tubule vesicles with antibodies against protein tt28 and against GLUT4 revealed the presence of GLUT4 in T-tubules under basal conditions and it also allowed the identification of two distinct pools of T-tubules showing different contents of tt28 and dihydropyridine receptors. 7. Our data on distribution of clathrin and dystrophin reveal the existence of subcompartments in sarcolemma from muscle fibre, featuring selective mutually exclusive components. T-tubules contain caveolin and clathrin suggesting that they contain caveolin- and clathrin-rich domains. Furthermore, evidence for the heterogeneous distribution of membrane proteins in T-tubules is also presented.
Distinct and Atypical Intrinsic and Extrinsic Cell Death Pathways between Photoreceptor Cell Types upon Specific Ablation of Ranbp2 in Cone Photoreceptors

PubMed Central

Cho, Kyoung-in; Yu, Minzhong; Hao, Ying; Qiu, Sunny; Pillai, Indulekha C. L.; Peachey, Neal S.; Ferreira, Paulo A.

2013-01-01

Non-autonomous cell-death is a cardinal feature of the disintegration of neural networks in neurodegenerative diseases, but the molecular bases of this process are poorly understood. The neural retina comprises a mosaic of rod and cone photoreceptors. Cone and rod photoreceptors degenerate upon rod-specific expression of heterogeneous mutations in functionally distinct genes, whereas cone-specific mutations are thought to cause only cone demise. Here we show that conditional ablation in cone photoreceptors of Ran-binding protein-2 (Ranbp2), a cell context-dependent pleiotropic protein linked to neuroprotection, familial necrotic encephalopathies, acute transverse myelitis and tumor-suppression, promotes early electrophysiological deficits, subcellular erosive destruction and non-apoptotic death of cones, whereas rod photoreceptors undergo cone-dependent non-autonomous apoptosis. Cone-specific Ranbp2 ablation causes the temporal activation of a cone-intrinsic molecular cascade highlighted by the early activation of metalloproteinase 11/stromelysin-3 and up-regulation of Crx and CoREST, followed by the down-modulation of cone-specific phototransduction genes, transient up-regulation of regulatory/survival genes and activation of caspase-7 without apoptosis. Conversely, PARP1+-apoptotic rods develop upon sequential activation of caspase-9 and caspase-3 and loss of membrane permeability. Rod photoreceptor demise ceases upon cone degeneration. These findings reveal novel roles of Ranbp2 in the modulation of intrinsic and extrinsic cell death mechanisms and pathways. They also unveil a novel spatiotemporal paradigm of progression of neurodegeneration upon cell-specific genetic damage whereby a cone to rod non-autonomous death pathway with intrinsically distinct cell-type death manifestations is triggered by cell-specific loss of Ranbp2. Finally, this study casts new light onto cell-death mechanisms that may be shared by human dystrophies with distinct retinal spatial signatures as well as with other etiologically distinct neurodegenerative disorders. PMID:23818861
Immunogold labeling reveals subcellular localisation of silica nanoparticles in a human blood-brain barrier model

NASA Astrophysics Data System (ADS)

Ye, Dong; Anguissola, Sergio; O'Neill, Tiina; Dawson, Kenneth A.

2015-05-01

Subcellular location of nanoparticles has been widely investigated with fluorescence microscopy, via fluorescently labeled antibodies to visualise target antigens in cells. However, fluorescence microscopy, such as confocal or live cell imaging, has generally limited 3D spatial resolution. Conventional electron microscopy can be useful in bridging resolution gap, but still not ideal in resolving subcellular organelle identities. Using the pre-embedding immunogold electron microscopic imaging, we performed accurate examination of the intracellular trafficking and gathered further evidence of transport mechanisms of silica nanoparticles across a human in vitro blood-brain barrier model. Our approach can effectively immunolocalise a variety of intracellular compartments and provide new insights into the uptake and subcellular transport of nanoparticles.Subcellular location of nanoparticles has been widely investigated with fluorescence microscopy, via fluorescently labeled antibodies to visualise target antigens in cells. However, fluorescence microscopy, such as confocal or live cell imaging, has generally limited 3D spatial resolution. Conventional electron microscopy can be useful in bridging resolution gap, but still not ideal in resolving subcellular organelle identities. Using the pre-embedding immunogold electron microscopic imaging, we performed accurate examination of the intracellular trafficking and gathered further evidence of transport mechanisms of silica nanoparticles across a human in vitro blood-brain barrier model. Our approach can effectively immunolocalise a variety of intracellular compartments and provide new insights into the uptake and subcellular transport of nanoparticles. Electronic supplementary information (ESI) available: Nanoparticle characterisation data, preservation of cellular structures, staining controls, optimisation of size amplification via the silver enhancement, and more imaging results from anti-clathrin and anti-caveolin 1 immunolabeling. See DOI: 10.1039/c5nr01539a
Subcellular analysis by laser ablation electrospray ionization mass spectrometry

DOEpatents

Vertes, Akos; Stolee, Jessica A; Shrestha, Bindesh

2014-12-02

In various embodiments, a method of laser ablation electrospray ionization mass spectrometry (LAESI-MS) may generally comprise micro-dissecting a cell comprising at least one of a cell wall and a cell membrane to expose at least one subcellular component therein, ablating the at least one subcellular component by an infrared laser pulse to form an ablation plume, intercepting the ablation plume by an electrospray plume to form ions, and detecting the ions by mass spectrometry.

Subcellular SIMS imaging of gadolinium isotopes in human glioblastoma cells treated with a gadolinium containing MRI agent

NASA Astrophysics Data System (ADS)

Smith, Duane R.; Lorey, Daniel R.; Chandra, Subhash

2004-06-01

Neutron capture therapy is an experimental binary radiotherapeutic modality for the treatment of brain tumors such as glioblastoma multiforme. Recently, neutron capture therapy with gadolinium-157 has gained attention, and techniques for studying the subcellular distribution of gadolinium-157 are needed. In this preliminary study, we have been able to image the subcellular distribution of gadolinium-157, as well as the other six naturally abundant isotopes of gadolinium, with SIMS ion microscopy. T98G human glioblastoma cells were treated for 24 h with 25 mg/ml of the metal ion complex diethylenetriaminepentaacetic acid Gd(III) dihydrogen salt hydrate (Gd-DTPA). Gd-DTPA is a contrast enhancing agent used for MRI of brain tumors, blood-brain barrier impairment, diseases of the central nervous system, etc. A highly heterogeneous subcellular distribution was observed for gadolinium-157. The nuclei in each cell were distinctly lower in gadolinium-157 than in the cytoplasm. Even within the cytoplasm the gadolinium-157 was heterogeneously distributed. The other six naturally abundant isotopes of gadolinium were imaged from the same cells and exhibited a subcellular distribution consistent with that observed for gadolinium-157. These observations indicate that SIMS ion microscopy may be a viable approach for subcellular studies of gadolinium containing neutron capture therapy drugs and may even play a major role in the development and validation of new gadolinium contrast enhancing agents for diagnostic MRI applications.
Subcellular distribution of 3 beta-hydroxysteroid dehydrogenase-isomerase in bovine and murine adrenocortical tissue: species differences in the localization of activity and immunoreactivity.

PubMed

Perry, J E; Ishii-Ohba, H; Stalvey, J R

1991-06-01

Key to the production of biologically active steroids is the enzyme 3 beta-hydroxysteroid dehydrogenase-isomerase. Some controversy has arisen concerning the subcellular distribution of this enzyme within steroidogenic cells. The distribution of 3 beta-hydroxysteroid dehydrogenase-isomerase was assessed in subcellular fractions obtained from homogenates of rat, bovine, and mouse adrenal glands in two ways. The activity of 3 beta-hydroxysteroid dehydrogenase-isomerase was quantitated by measuring the conversion of radiolabeled pregnenolone to radiolabeled progesterone in an aliquot of each of the fractions obtained. The presence of the enzyme was assessed by performing Western analyses on aliquots of each of the fractions obtained with the use of a specific polyclonal antiserum against 3 beta-hydroxysteroid dehydrogenase-isomerase, the characterization of which is described. In control experiments, the degree of contamination of the fractions was determined by assessing the presence of known subcellular fraction markers with Western analysis. In the bovine and mouse adrenal glands, 3 beta-hydroxysteroid dehydrogenase-isomerase appears to be localized solely in the microsomal fraction, while in the rat, 3 beta-hydroxysteroid dehydrogenase-isomerase appears to have dual subcellular distribution: the microsomes and the inner mitochondrial membrane. We conclude that there is a species difference in the subcellular distribution of this important steroidogenic enzyme and that this species difference may be related to the steroidogenic pathway preferred in that species.
Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain.

PubMed

Kuipers, Jeroen; Kalicharan, Ruby D; Wolters, Anouk H G; van Ham, Tjakko J; Giepmans, Ben N G

2016-05-25

Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae(1-7). Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture(1-5). Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)(8) on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner.
Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain

PubMed Central

Kuipers, Jeroen; Kalicharan, Ruby D.; Wolters, Anouk H. G.

2016-01-01

Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae1-7. Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture1-5. Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)8 on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner. PMID:27285162
Biochemical label-free tissue imaging with subcellular-resolution synchrotron FTIR with focal plane array detector.

PubMed

Kastyak-Ibrahim, M Z; Nasse, M J; Rak, M; Hirschmugl, C; Del Bigio, M R; Albensi, B C; Gough, K M

2012-03-01

The critical questions into the cause of neural degeneration, in Alzheimer disease and other neurodegenerative disorders, are closely related to the question of why certain neurons survive. Answers require detailed understanding of biochemical changes in single cells. Fourier transform infrared microspectroscopy is an excellent tool for biomolecular imaging in situ, but resolution is limited. The mid-infrared beamline IRENI (InfraRed ENvironmental Imaging) at the Synchrotron Radiation Center, University of Wisconsin-Madison, enables label-free subcellular imaging and biochemical analysis of neurons with an increase of two orders of magnitude in pixel spacing over current systems. With IRENI's capabilities, it is now possible to study changes in individual neurons in situ, and to characterize their surroundings, using only the biochemical signatures of naturally-occurring components in unstained, unfixed tissue. We present examples of analyses of brain from two transgenic mouse models of Alzheimer disease (TgCRND8 and 3xTg) that exhibit different features of pathogenesis. Data processing on spectral features for nuclei reveals individual hippocampal neurons, and neurons located in the proximity of amyloid plaque in TgCRND8 mouse. Elevated lipids are detected surrounding and, for the first time, within the dense core of amyloid plaques, offering support for inflammatory and aggregation roles. Analysis of saturated and unsaturated fatty acid ester content in retina allows characterization of neuronal layers. IRENI images also reveal spatially-resolved data with unprecedented clarity and distinct spectral variation, from sub-regions including photoreceptors, neuronal cell bodies and synapses in sections of mouse retina. Biochemical composition of retinal layers can be used to study changes related to disease processes and dietary modification. Copyright © 2011 Elsevier Inc. All rights reserved.
Evaluation on subcellular partitioning and biodynamics of pulse copper toxicity in tilapia reveals impacts of a major environmental disturbance.

PubMed

Ju, Yun-Ru; Yang, Ying-Fei; Tsai, Jeng-Wei; Cheng, Yi-Hsien; Chen, Wei-Yu; Liao, Chung-Min

2017-07-01

Fluctuation exposure of trace metal copper (Cu) is ubiquitous in aquatic environments. The purpose of this study was to investigate the impacts of chronically pulsed exposure on biodynamics and subcellular partitioning of Cu in freshwater tilapia (Oreochromis mossambicus). Long-term 28-day pulsed Cu exposure experiments were performed to explore subcellular partitioning and toxicokinetics/toxicodynamics of Cu in tilapia. Subcellular partitioning linking with a metal influx scheme was used to estimate detoxification and elimination rates. A biotic ligand model-based damage assessment model was used to take into account environmental effects and biological mechanisms of Cu toxicity. We demonstrated that the probability causing 50% of susceptibility risk in response to pulse Cu exposure in generic Taiwan aquaculture ponds was ~33% of Cu in adverse physiologically associated, metabolically active pool, implicating no significant susceptibility risk for tilapia. We suggest that our integrated ecotoxicological models linking chronic exposure measurements with subcellular partitioning can facilitate a risk assessment framework that provides a predictive tool for preventive susceptibility reduction strategies for freshwater fish exposed to pulse metal stressors.
Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

PubMed

Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi

2016-01-01

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.
Comparison of Sequential and Variational Data Assimilation

NASA Astrophysics Data System (ADS)

Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Weerts, Albrecht

2017-04-01

Data assimilation is a valuable tool to improve model state estimates by combining measured observations with model simulations. It has recently gained significant attention due to its potential in using remote sensing products to improve operational hydrological forecasts and for reanalysis purposes. This has been supported by the application of sequential techniques such as the Ensemble Kalman Filter which require no additional features within the modeling process, i.e. it can use arbitrary black-box models. Alternatively, variational techniques rely on optimization algorithms to minimize a pre-defined objective function. This function describes the trade-off between the amount of noise introduced into the system and the mismatch between simulated and observed variables. While sequential techniques have been commonly applied to hydrological processes, variational techniques are seldom used. In our believe, this is mainly attributed to the required computation of first order sensitivities by algorithmic differentiation techniques and related model enhancements, but also to lack of comparison between both techniques. We contribute to filling this gap and present the results from the assimilation of streamflow data in two basins located in Germany and Canada. The assimilation introduces noise to precipitation and temperature to produce better initial estimates of an HBV model. The results are computed for a hindcast period and assessed using lead time performance metrics. The study concludes with a discussion of the main features of each technique and their advantages/disadvantages in hydrological applications.
Short-term memory for spatial, sequential and duration information.

PubMed

Manohar, Sanjay G; Pertzov, Yoni; Husain, Masud

2017-10-01

Space and time appear to play key roles in the way that information is organized in short-term memory (STM). Some argue that they are crucial contexts within which other stored features are embedded, allowing binding of information that belongs together within STM. Here we review recent behavioral, neurophysiological and imaging studies that have sought to investigate the nature of spatial, sequential and duration representations in STM, and how these might break down in disease. Findings from these studies point to an important role of the hippocampus and other medial temporal lobe structures in aspects of STM, challenging conventional accounts of involvement of these regions in only long-term memory.
Digital Circuit Analysis Using an 8080 Processor.

ERIC Educational Resources Information Center

Greco, John; Stern, Kenneth

1983-01-01

Presents the essentials of a program written in Intel 8080 assembly language for the steady state analysis of a combinatorial logic gate circuit. Program features and potential modifications are considered. For example, the program could also be extended to include clocked/unclocked sequential circuits. (JN)
Experiences with digital processing of images at INPE

NASA Technical Reports Server (NTRS)

Mascarenhas, N. D. A. (Principal Investigator)

1984-01-01

Four different research experiments with digital image processing at INPE will be described: (1) edge detection by hypothesis testing; (2) image interpolation by finite impulse response filters; (3) spatial feature extraction methods in multispectral classification; and (4) translational image registration by sequential tests of hypotheses.
Sequential sensory and decision processing in posterior parietal cortex

PubMed Central

Ibos, Guilhem; Freedman, David J

2017-01-01

Decisions about the behavioral significance of sensory stimuli often require comparing sensory inference of what we are looking at to internal models of what we are looking for. Here, we test how neuronal selectivity for visual features is transformed into decision-related signals in posterior parietal cortex (area LIP). Monkeys performed a visual matching task that required them to detect target stimuli composed of conjunctions of color and motion-direction. Neuronal recordings from area LIP revealed two main findings. First, the sequential processing of visual features and the selection of target-stimuli suggest that LIP is involved in transforming sensory information into decision-related signals. Second, the patterns of color and motion selectivity and their impact on decision-related encoding suggest that LIP plays a role in detecting target stimuli by comparing bottom-up sensory inputs (what the monkeys were looking at) and top-down cognitive encoding inputs (what the monkeys were looking for). DOI: http://dx.doi.org/10.7554/eLife.23743.001 PMID:28418332
"Developing a Perspective", "Inter-Connecting", and "Bringing It Together": Who Chooses to Use a Labelling Feature in Online Conversations in a Graduate Course?

ERIC Educational Resources Information Center

Bures, Eva Mary; Schmid, Richard F.; Abrami, Philip C.

2009-01-01

This study explores a labelling feature that allows students to tag parts of their online messages. Data comes from four sequentially offered sessions of a graduate education course. Students engaged in two to three online activities in groups of three or four. Students (n = 53) contributed from 0 to 56 labels (M = 12.42, SD = 13.50) and 18 to 114…
Visual perception as retrospective Bayesian decoding from high- to low-level features.

PubMed

Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning

2017-10-24

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.
Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.

PubMed

Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D; Jeong, Jaeseung

2014-08-01

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.
Extrasynaptic N-methyl-D-aspartate (NMDA) receptor stimulation induces cytoplasmic translocation of the CDKL5 kinase and its proteasomal degradation.

PubMed

Rusconi, Laura; Kilstrup-Nielsen, Charlotte; Landsberger, Nicoletta

2011-10-21

Mutations in the X-linked gene cyclin-dependent kinase-like 5 (CDKL5) have been found in patients with epileptic encephalopathy characterized by early onset intractable epilepsy, including infantile spasms and other types of seizures, severe developmental delay, and often the development of Rett syndrome-like features. Despite its clear involvement in proper brain development, CDKL5 functions are still far from being understood. In this study, we analyzed the subcellular localization of the endogenous kinase in primary murine hippocampal neurons. CDKL5 was localized both in nucleus and cytoplasm and, conversely to proliferating cells, did not undergo constitutive shuttling between these compartments. Nevertheless, glutamate stimulation was able to induce the exit of the kinase from the nucleus and its subsequent accumulation in the perinuclear cytoplasm. Moreover, we found that sustained glutamate stimulation promoted CDKL5 proteasomal degradation. Both events were mediated by the specific activation of extrasynaptic pool of N-methyl-d-aspartate receptors. Proteasomal degradation was also induced by withdrawal of neurotrophic factors and hydrogen peroxide treatment, two different paradigms of cell death. Altogether, our results indicate that both subcellular localization and expression of CDKL5 are modulated by the activation of extrasynaptic N-methyl-D-aspartate receptors and suggest regulation of CDKL5 by cell death pathways.
Noninvasive identification of subcellular organization and nuclear morphology features associated with leukemic cells using light-scattering spectroscopy

NASA Astrophysics Data System (ADS)

Hsiao, Austin; Hunter, Martin; Greiner, Cherry; Gupta, Sharad; Georgakoudi, Irene

2011-03-01

Leukemia is the most common and deadly cancer among children and one of the most prevalent cancers among adults. Improvements in its diagnosis and monitoring of leukemic patients could have a significant impact in their long-term treatment. We demonstrate that light-scattering spectroscopy (LSS)-based approaches could serve as a tool to achieve this goal. Specifically, we characterize the light scattering properties of leukemic (NALM-6) cells and compare them to those of normal lymphocytes and granulocytes in the 440-710 nm range, over +/-4 deg about the exact backscattering direction. We find that the LSS spectra are well described by an inverse power-law wavelength dependence, with a power exponent insensitive to the scattering angle but significantly higher for leukemic cells than for normal leukocytes. This is consistent with differences in the subcellular morphology of these cells, detected in differential interference contrast images. Furthermore, the residual light-scattering signal, extracted after subtracting the inverse power-law fit from the data, can be analyzed assuming a Gaussian distribution of spherical scatterers using Mie theory. This analysis yields scatterer sizes that are consistent with the diameters of cell nuclei and allows the detection of the larger nuclei of NALM-6 cells compared to those of lymphocytes and granulocytes.
Multi-scale computational study of the mechanical regulation of cell mitotic rounding in epithelia

PubMed Central

Xu, Zhiliang; Zartman, Jeremiah J.; Alber, Mark

2017-01-01

Mitotic rounding during cell division is critical for preventing daughter cells from inheriting an abnormal number of chromosomes, a condition that occurs frequently in cancer cells. Cells must significantly expand their apical area and transition from a polygonal to circular apical shape to achieve robust mitotic rounding in epithelial tissues, which is where most cancers initiate. However, how cells mechanically regulate robust mitotic rounding within packed tissues is unknown. Here, we analyze mitotic rounding using a newly developed multi-scale subcellular element computational model that is calibrated using experimental data. Novel biologically relevant features of the model include separate representations of the sub-cellular components including the apical membrane and cytoplasm of the cell at the tissue scale level as well as detailed description of cell properties during mitotic rounding. Regression analysis of predictive model simulation results reveals the relative contributions of osmotic pressure, cell-cell adhesion and cortical stiffness to mitotic rounding. Mitotic area expansion is largely driven by regulation of cytoplasmic pressure. Surprisingly, mitotic shape roundness within physiological ranges is most sensitive to variation in cell-cell adhesivity and stiffness. An understanding of how perturbed mechanical properties impact mitotic rounding has important potential implications on, amongst others, how tumors progressively become more genetically unstable due to increased chromosomal aneuploidy and more aggressive. PMID:28531187
Comparative studies of a new subfamily of human Ste20-like kinases: homodimerization, subcellular localization, and selective activation of MKK3 and p38.

PubMed

Yustein, Jason T; Xia, Liang; Kahlenburg, J Michelle; Robinson, Dan; Templeton, Dennis; Kung, Hsing-Jien

2003-09-18

The Sterile-20 or Ste20 family of serine/threonine kinases is a group of signaling molecules whose physiological roles within mammalian cells are just starting to be elucidated. Here, in this report we present the characterization of three human Ste20-like kinases with greater than 90% similarity within their catalytic domains that define a novel subfamily of Ste20s. Members of this kinase family include rat thousand and one (TAO1) and chicken KFC (kinase from chicken). For the lack of a consensus nomenclature in the literature, in this report, we shall call this family hKFC (for their homology to chicken KFC) and the three members hKFC-A, hKFC-B, and hKFC-C, respectively. These kinases have many similarities including an aminoterminal kinase domain, a serine-rich region, and a coiled-coil configuration within the C-terminus. All three kinases are able to activate the p38 MAP kinase pathway through the specific activation of the upstream MKK3 kinase. We also offer evidence, both theoretical and biochemical, showing that these kinases can undergo self-association. Despite these similarities, these kinases differ in tissue distribution, apparent subcellular localization, and feature structural differences largely within the carboxyl-terminal sequence.
X-ray microscopy of human malaria

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

Magowan, C.; Brown, J.T.; Mohandas, N.

Associations between intracellular organisms and host cells are complex and particularly difficult to examine. X-ray microscopy provides transmission images of subcellular structures in intact cells at resolutions superior to available methodologies. The spatial resolution is 50-60nm with a 1 micron depth of focus, superior to anything achievable with light microscopy. Image contrast is generated by differences in photoelectric absorption by the atoms in different areas (i.e. subcellular structures) throughout the full thickness of the sample. Absorption due to carbon dominates among all the elements in the sample at 2.4 nm x-ray wavelength. Thus images show features or structures, in amore » way not usually seen by other types of microscopy. The authors used soft x-ray microscopy to investigate structural development of Plasmodium falciparum malaria parasites in normal and genetically abnormal erythrocytes, and in infected erythrocytes treated with compounds that have anti-malarial effects. X-ray microscopy showed newly elaborated structures in the cytosol of unstained, intact erythrocytes, redistribution of mass (carbon) in infected erythrocytes, and aberrant parasite morphology. Better understanding of the process of intracellular parasite maturation and the interactions between the parasite and its host erythrocyte can help define new approaches to the control of this deadly disease.« less

The Emotion Recognition System Based on Autoregressive Model and Sequential Forward Feature Selection of Electroencephalogram Signals

PubMed Central

Hatamikia, Sepideh; Maghooli, Keivan; Nasrabadi, Ali Motie

2014-01-01

Electroencephalogram (EEG) is one of the useful biological signals to distinguish different brain diseases and mental states. In recent years, detecting different emotional states from biological signals has been merged more attention by researchers and several feature extraction methods and classifiers are suggested to recognize emotions from EEG signals. In this research, we introduce an emotion recognition system using autoregressive (AR) model, sequential forward feature selection (SFS) and K-nearest neighbor (KNN) classifier using EEG signals during emotional audio-visual inductions. The main purpose of this paper is to investigate the performance of AR features in the classification of emotional states. To achieve this goal, a distinguished AR method (Burg's method) based on Levinson-Durbin's recursive algorithm is used and AR coefficients are extracted as feature vectors. In the next step, two different feature selection methods based on SFS algorithm and Davies–Bouldin index are used in order to decrease the complexity of computing and redundancy of features; then, three different classifiers include KNN, quadratic discriminant analysis and linear discriminant analysis are used to discriminate two and three different classes of valence and arousal levels. The proposed method is evaluated with EEG signals of available database for emotion analysis using physiological signals, which are recorded from 32 participants during 40 1 min audio visual inductions. According to the results, AR features are efficient to recognize emotional states from EEG signals, and KNN performs better than two other classifiers in discriminating of both two and three valence/arousal classes. The results also show that SFS method improves accuracies by almost 10-15% as compared to Davies–Bouldin based feature selection. The best accuracies are %72.33 and %74.20 for two classes of valence and arousal and %61.10 and %65.16 for three classes, respectively. PMID:25298928
Wavelet-based energy features for glaucomatous image classification.

PubMed

Dua, Sumeet; Acharya, U Rajendra; Chowriappa, Pradeep; Sree, S Vinitha

2012-01-01

Texture features within images are actively pursued for accurate and efficient glaucoma classification. Energy distribution over wavelet subbands is applied to find these important texture features. In this paper, we investigate the discriminatory potential of wavelet features obtained from the daubechies (db3), symlets (sym3), and biorthogonal (bio3.3, bio3.5, and bio3.7) wavelet filters. We propose a novel technique to extract energy signatures obtained using 2-D discrete wavelet transform, and subject these signatures to different feature ranking and feature selection strategies. We have gauged the effectiveness of the resultant ranked and selected subsets of features using a support vector machine, sequential minimal optimization, random forest, and naïve Bayes classification strategies. We observed an accuracy of around 93% using tenfold cross validations to demonstrate the effectiveness of these methods.
Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

PubMed

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.
Protein subcellular localization assays using split fluorescent proteins

DOEpatents

Waldo, Geoffrey S [Santa Fe, NM; Cabantous, Stephanie [Los Alamos, NM

2009-09-08

The invention provides protein subcellular localization assays using split fluorescent protein systems. The assays are conducted in living cells, do not require fixation and washing steps inherent in existing immunostaining and related techniques, and permit rapid, non-invasive, direct visualization of protein localization in living cells. The split fluorescent protein systems used in the practice of the invention generally comprise two or more self-complementing fragments of a fluorescent protein, such as GFP, wherein one or more of the fragments correspond to one or more beta-strand microdomains and are used to "tag" proteins of interest, and a complementary "assay" fragment of the fluorescent protein. Either or both of the fragments may be functionalized with a subcellular targeting sequence enabling it to be expressed in or directed to a particular subcellular compartment (i.e., the nucleus).
Sub-cellular force microscopy in single normal and cancer cells

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

Babahosseini, H.; Carmichael, B.; Strobl, J.S.

2015-08-07

This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer andmore » significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. - Highlights: • The cells are modeled as a triple-layered structure using Generalized Maxwell model. • The sub-domains include membrane/cortex, cytoplasm/nucleus, and nuclear/integrin. • Biomechanics of corresponding sub-domains are compared among normal and cancer cells. • Viscoelasticity of sub-domains show a decreasing trend from normal to cancer cells. • The decreasing trend becomes most significant in the deeper sub-domain.« less
High Speed Size Sorting of Subcellular Organelles by Flow Field-Flow Fractionation.

PubMed

Yang, Joon Seon; Lee, Ju Yong; Moon, Myeong Hee

2015-06-16

Separation/isolation of subcellular species, such as mitochondria, lysosomes, peroxisomes, Golgi apparatus, and others, from cells is important for gaining an understanding of the cellular functions performed by specific organelles. This study introduces a high speed, semipreparative scale, biocompatible size sorting method for the isolation of subcellular organelle species from homogenate mixtures of HEK 293T cells using flow field-flow fractionation (FlFFF). Separation of organelles was achieved using asymmetrical FlFFF (AF4) channel system at the steric/hyperlayer mode in which nuclei, lysosomes, mitochondria, and peroxisomes were separated in a decreasing order of hydrodynamic diameter without complicated preprocessing steps. Fractions in which organelles were not clearly separated were reinjected to AF4 for a finer separation using the normal mode, in which smaller sized species can be well fractionated by an increasing order of diameter. The subcellular species contained in collected AF4 fractions were examined with scanning electron microscopy to evaluate their size and morphology, Western blot analysis using organelle specific markers was used for organelle confirmation, and proteomic analysis was performed with nanoflow liquid chromatography-tandem mass spectrometry (nLC-ESI-MS/MS). Since FlFFF operates with biocompatible buffer solutions, it offers great flexibility in handling subcellular components without relying on a high concentration sucrose solution for centrifugation or affinity- or fluorescence tag-based sorting methods. Consequently, the current study provides an alternative, competitive method for the isolation/purification of subcellular organelle species in their intact states.
Detecting Circular RNAs by RNA Fluorescence In Situ Hybridization.

PubMed

Zirkel, Anne; Papantonis, Argyris

2018-01-01

Fluorescence in situ hybridization (FISH) coupled to high-resolution microscopy is a powerful method for analyzing the subcellular localization of RNA. However, the detection of circular RNAs (circRNAs) using microscopy is challenging because the only feature of a circRNA that can be used for the probe design is its junction. Circular RNAs are expressed at varying levels, and for their efficient monitoring by FISH, background fluorescence levels need to be kept low. Here, we describe a FISH protocol coupled to high-precision localizations using a single fluorescently labeled probe spanning the circRNA junction; this allows circRNA detection in mammalian cells with high signal-to-noise ratios.
Zone plate lenses for X-ray microscopy

NASA Astrophysics Data System (ADS)

Vladimirsky, Y.; Kern, D. P.; Chang, T. H. P.; Attwood, D. T.; Iskander, N.; Rothman, S.; McQuaide, K.; Kirz, J.; Ade, H.; McNulty, I.; Rarback, H.; Shu, D.

1988-04-01

Fresnel zone plate lenses with feature sizes as small as 50 nm have been constructed and used in the Stony Brook/NSLS scanning X-ray microscope with 3.1 nm radiation from Brookhaven's X-17 mini-undulator. The zone plates were fabricated at IBM using electron beam writing techniques, moiré pattern techniques to monitor ellipticity, and a double development/double plating technique to provide additional thickness in the central region. A spatial resolution down to 75 nm was measured in the microscope. Using these zone plates, biological images were obtained of unaltered subcellular components. The images highlight protein concentration in unsectioned, unfixed, and unstained enzymatic granules in an aqueous environment.
Associative learning in baboons (Papio papio) and humans (Homo sapiens): species differences in learned attention to visual features.

PubMed

Fagot, J; Kruschke, J K; Dépy, D; Vauclair, J

1998-10-01

We examined attention shifting in baboons and humans during the learning of visual categories. Within a conditional matching-to-sample task, participants of the two species sequentially learned two two-feature categories which shared a common feature. Results showed that humans encoded both features of the initially learned category, but predominantly only the distinctive feature of the subsequently learned category. Although baboons initially encoded both features of the first category, they ultimately retained only the distinctive features of each category. Empirical data from the two species were analyzed with the 1996 ADIT connectionist model of Kruschke. ADIT fits the baboon data when the attentional shift rate is zero, and the human data when the attentional shift rate is not zero. These empirical and modeling results suggest species differences in learned attention to visual features.
Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278
Minimalist ensemble algorithms for genome-wide protein localization prediction.

PubMed

Lin, Jhih-Rong; Mondal, Ananda Mohan; Liu, Rong; Hu, Jianjun

2012-07-03

Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. We proposed a method for rational design of minimalist ensemble algorithms using feature selection and classifiers. The proposed minimalist ensemble algorithm based on logistic regression can achieve equal or better prediction performance while using only half or one-third of individual predictors compared to other ensemble algorithms. The results also suggested that meta-predictors that take advantage of a variety of features by combining individual predictors tend to achieve the best performance. The LR ensemble server and related benchmark datasets are available at http://mleg.cse.sc.edu/LRensemble/cgi-bin/predict.cgi.
Minimalist ensemble algorithms for genome-wide protein localization prediction

PubMed Central

2012-01-01

Background Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. Results This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. Conclusions We proposed a method for rational design of minimalist ensemble algorithms using feature selection and classifiers. The proposed minimalist ensemble algorithm based on logistic regression can achieve equal or better prediction performance while using only half or one-third of individual predictors compared to other ensemble algorithms. The results also suggested that meta-predictors that take advantage of a variety of features by combining individual predictors tend to achieve the best performance. The LR ensemble server and related benchmark datasets are available at http://mleg.cse.sc.edu/LRensemble/cgi-bin/predict.cgi. PMID:22759391
pLoc_bal-mGpos: Predict subcellular localization of Gram-positive bacterial proteins by quasi-balancing training dataset and PseAAC.

PubMed

Xiao, Xuan; Cheng, Xiang; Chen, Genqiang; Mao, Qi; Chou, Kuo-Chen

2018-05-26

Knowledge of protein subcellular localization is vitally important for both basic research and drug development. With the avalanche of protein sequences emerging in the post-genomic age, it is highly desired to develop computational tools for timely and effectively identifying their subcellular localization purely based on the sequence information alone. Recently, a predictor called "pLoc-mGpos" was developed for identifying the subcellular localization of Gram-positive bacterial proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems in which some proteins, called "multiplex proteins", may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mGpos was trained by an extremely skewed dataset in which some subset (subcellular location) was over 11 times the size of the other subsets. Accordingly, it cannot avoid the bias consequence caused by such an uneven training dataset. To alleviate such bias consequence, we have developed a new and bias-reducing predictor called pLoc_bal-mGpos by quasi-balancing the training dataset. Rigorous target jackknife tests on exactly the same experiment-confirmed dataset have indicated that the proposed new predictor is remarkably superior to pLoc-mGpos, the existing state-of-the-art predictor in identifying the subcellular localization of Gram-positive bacterial proteins. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mGpos/, by which users can easily get their desired results without the need to go through the detailed mathematics. Copyright © 2018 Elsevier Inc. All rights reserved.
Protein subcellular location pattern classification in cellular images using latent discriminative models.

PubMed

Li, Jieyue; Xiong, Liang; Schneider, Jeff; Murphy, Robert F

2012-06-15

Knowledge of the subcellular location of a protein is crucial for understanding its functions. The subcellular pattern of a protein is typically represented as the set of cellular components in which it is located, and an important task is to determine this set from microscope images. In this article, we address this classification problem using confocal immunofluorescence images from the Human Protein Atlas (HPA) project. The HPA contains images of cells stained for many proteins; each is also stained for three reference components, but there are many other components that are invisible. Given one such cell, the task is to classify the pattern type of the stained protein. We first randomly select local image regions within the cells, and then extract various carefully designed features from these regions. This region-based approach enables us to explicitly study the relationship between proteins and different cell components, as well as the interactions between these components. To achieve these two goals, we propose two discriminative models that extend logistic regression with structured latent variables. The first model allows the same protein pattern class to be expressed differently according to the underlying components in different regions. The second model further captures the spatial dependencies between the components within the same cell so that we can better infer these components. To learn these models, we propose a fast approximate algorithm for inference, and then use gradient-based methods to maximize the data likelihood. In the experiments, we show that the proposed models help improve the classification accuracies on synthetic data and real cellular images. The best overall accuracy we report in this article for classifying 942 proteins into 13 classes of patterns is about 84.6%, which to our knowledge is the best so far. In addition, the dependencies learned are consistent with prior knowledge of cell organization. http://murphylab.web.cmu.edu/software/.
pLoc-mAnimal: predict subcellular localization of animal proteins with both single and multiple sites.

PubMed

Cheng, Xiang; Zhao, Shu-Guang; Lin, Wei-Zhong; Xiao, Xuan; Chou, Kuo-Chen

2017-11-15

Cells are deemed the basic unit of life. However, many important functions of cells as well as their growth and reproduction are performed via the protein molecules located at their different organelles or locations. Facing explosive growth of protein sequences, we are challenged to develop fast and effective method to annotate their subcellular localization. However, this is by no means an easy task. Particularly, mounting evidences have indicated proteins have multi-label feature meaning that they may simultaneously exist at, or move between, two or more different subcellular location sites. Unfortunately, most of the existing computational methods can only be used to deal with the single-label proteins. Although the 'iLoc-Animal' predictor developed recently is quite powerful that can be used to deal with the animal proteins with multiple locations as well, its prediction quality needs to be improved, particularly in enhancing the absolute true rate and reducing the absolute false rate. Here we propose a new predictor called 'pLoc-mAnimal', which is superior to iLoc-Animal as shown by the compelling facts. When tested by the most rigorous cross-validation on the same high-quality benchmark dataset, the absolute true success rate achieved by the new predictor is 37% higher and the absolute false rate is four times lower in comparison with the state-of-the-art predictor. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc-mAnimal/, by which users can easily get their desired results without the need to go through the complicated mathematics involved. xxiao@gordonlifescience.org or kcchou@gordonlifescience.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

PubMed

Lin, Wei-Zhong; Fang, Jian-An; Xiao, Xuan; Chou, Kuo-Chen

2013-04-05

Predicting protein subcellular localization is a challenging problem, particularly when query proteins have multi-label features meaning that they may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing methods can only be used to deal with the single-label proteins. Actually, multi-label proteins should not be ignored because they usually bear some special function worthy of in-depth studies. By introducing the "multi-label learning" approach, a new predictor, called iLoc-Animal, has been developed that can be used to deal with the systems containing both single- and multi-label animal (metazoan except human) proteins. Meanwhile, to measure the prediction quality of a multi-label system in a rigorous way, five indices were introduced; they are "Absolute-True", "Absolute-False" (or Hamming-Loss"), "Accuracy", "Precision", and "Recall". As a demonstration, the jackknife cross-validation was performed with iLoc-Animal on a benchmark dataset of animal proteins classified into the following 20 location sites: (1) acrosome, (2) cell membrane, (3) centriole, (4) centrosome, (5) cell cortex, (6) cytoplasm, (7) cytoskeleton, (8) endoplasmic reticulum, (9) endosome, (10) extracellular, (11) Golgi apparatus, (12) lysosome, (13) mitochondrion, (14) melanosome, (15) microsome, (16) nucleus, (17) peroxisome, (18) plasma membrane, (19) spindle, and (20) synapse, where many proteins belong to two or more locations. For such a complicated system, the outcomes achieved by iLoc-Animal for all the aforementioned five indices were quite encouraging, indicating that the predictor may become a useful tool in this area. It has not escaped our notice that the multi-label approach and the rigorous measurement metrics can also be used to investigate many other multi-label problems in molecular biology. As a user-friendly web-server, iLoc-Animal is freely accessible to the public at the web-site .
Seeking Positive Experiences Can Produce Illusory Correlations

ERIC Educational Resources Information Center

Denrell, Jerker; Le Mens, Gael

2011-01-01

Individuals tend to select again alternatives about which they have positive impressions and to avoid alternatives about which they have negative impressions. Here we show how this sequential sampling feature of the information acquisition process leads to the emergence of an illusory correlation between estimates of the attributes of…
Item Selection in Multidimensional Computerized Adaptive Testing--Gaining Information from Different Angles

ERIC Educational Resources Information Center

Wang, Chun; Chang, Hua-Hua

2011-01-01

Over the past thirty years, obtaining diagnostic information from examinees' item responses has become an increasingly important feature of educational and psychological testing. The objective can be achieved by sequentially selecting multidimensional items to fit the class of latent traits being assessed, and therefore Multidimensional…
ASPEN Plus in the Chemical Engineering Curriculum: Suitable Course Content and Teaching Methodology

ERIC Educational Resources Information Center

Rockstraw, David A.

2005-01-01

An established methodology involving the sequential presentation of five skills on ASPEN Plus to undergraduate seniors majoring in ChE is presented in this document: (1) specifying unit operations; (2) manipulating physical properties; (3) accessing variables; (4) specifying nonstandard components; and (5) applying advanced features. This…
Edge-following algorithm for tracking geological features

NASA Technical Reports Server (NTRS)

Tietz, J. C.

1977-01-01

Sequential edge-tracking algorithm employs circular scanning to point permit effective real-time tracking of coastlines and rivers from earth resources satellites. Technique eliminates expensive high-resolution cameras. System might also be adaptable for application in monitoring automated assembly lines, inspecting conveyor belts, or analyzing thermographs, or x ray images.

Visualization of metallodrugs in single cells by secondary ion mass spectrometry imaging.

PubMed

Wu, Kui; Jia, Feifei; Zheng, Wei; Luo, Qun; Zhao, Yao; Wang, Fuyi

2017-07-01

Secondary ion mass spectrometry, including nanoscale secondary ion mass spectrometry (NanoSIMS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), has emerged as a powerful tool for biological imaging, especially for single cell imaging. SIMS imaging can provide information on subcellular distribution of endogenous and exogenous chemicals, including metallodrugs, from membrane through to cytoplasm and nucleus without labeling, and with high spatial resolution and chemical specificity. In this mini-review, we summarize recent progress in the field of SIMS imaging, particularly in the characterization of the subcellular distribution of metallodrugs. We anticipate that the SIMS imaging method will be widely applied to visualize subcellular distributions of drugs and drug candidates in single cells, exerting significant influence on early drug evaluation and metabolism in medicinal and pharmaceutical chemistry. Recent progress of SIMS applications in characterizing the subcellular distributions of metallodrugs was summarized.
System dynamics of subcellular transport.

PubMed

Chen, Vivien Y; Khersonsky, Sonya M; Shedden, Kerby; Chang, Young Tae; Rosania, Gus R

2004-01-01

In pharmacokinetic experiments, interpretations often hinge on treating cells as a "black box": a single, lumped compartment or boundary. Here, a combinatorial library of fluorescent small molecules was used to visualize subcellular transport pathways in living cells, using a kinetic, high content imaging system to monitor spatiotemporal variations of intracellular probe distribution. Most probes accumulate in cytoplasmic vesicles and probe kinetics conform to a nested, two-compartment dynamical system. At steady state, probes preferentially partition from the extracellular medium to the cytosol, and from the cytosol to cytoplasmic vesicles, with hydrophobic molecules favoring sequestration. Altogether, these results point to a general organizing principle underlying the system dynamics of subcellular, small molecule transport. In addition to plasma membrane permeability, subcellular transport phenomena can determine the active concentration of small molecules in the cytosol and the efflux of small molecules from cells. Fundamentally, direct observation of intracellular probe distribution challenges the simple boundary model of classical pharmacokinetics, which considers cells as static permeability barriers.
Identification of mycobacterial surface proteins released into subcellular compartments of infected macrophages.

PubMed

Beatty, W L; Russell, D G

2000-12-01

Considerable effort has focused on the identification of proteins secreted from Mycobacterium spp. that contribute to the development of protective immunity. Little is known, however, about the release of mycobacterial proteins from the bacterial phagosome and the potential role of these molecules in chronically infected macrophages. In the present study, the release of mycobacterial surface proteins from the bacterial phagosome into subcellular compartments of infected macrophages was analyzed. Mycobacterium bovis BCG was surface labeled with fluorescein-tagged succinimidyl ester, an amine-reactive probe. The fluorescein tag was then used as a marker for the release of bacterial proteins in infected macrophages. Fractionation studies revealed bacterial proteins within subcellular compartments distinct from mycobacteria and mycobacterial phagosomes. To identify these proteins, subcellular fractions free of bacteria were probed with mycobacterium-specific antibodies. The fibronectin attachment protein and proteins of the antigen 85-kDa complex were identified among the mycobacterial proteins released from the bacterial phagosome.
Time scale of random sequential adsorption.

PubMed

Erban, Radek; Chapman, S Jonathan

2007-04-01

A simple multiscale approach to the diffusion-driven adsorption from a solution to a solid surface is presented. The model combines two important features of the adsorption process: (i) The kinetics of the chemical reaction between adsorbing molecules and the surface and (ii) geometrical constraints on the surface made by molecules which are already adsorbed. The process (i) is modeled in a diffusion-driven context, i.e., the conditional probability of adsorbing a molecule provided that the molecule hits the surface is related to the macroscopic surface reaction rate. The geometrical constraint (ii) is modeled using random sequential adsorption (RSA), which is the sequential addition of molecules at random positions on a surface; one attempt to attach a molecule is made per one RSA simulation time step. By coupling RSA with the diffusion of molecules in the solution above the surface the RSA simulation time step is related to the real physical time. The method is illustrated on a model of chemisorption of reactive polymers to a virus surface.
A class of temporal boundaries derived by quantifying the sense of separation.

PubMed

Paine, Llewyn Elise; Gilden, David L

2013-12-01

The perception of moment-to-moment environmental flux as being composed of meaningful events requires that memory processes coordinate with cues that signify beginnings and endings. We have constructed a technique that allows this coordination to be monitored indirectly. This technique works by embedding a sequential priming task into the event under study. Memory and perception must be coordinated to resolve temporal flux into scenes. The implicit memory processes inherent in sequential priming are able to effectively shadow then mirror scene-forming processes. Certain temporal boundaries are found to weaken the strength of irrelevant feature priming, a signal which can then be used in more ambiguous cases to infer how people segment time. Over the course of 13 independent studies, we were able to calibrate the technique and then use it to measure the strength of event segmentation in several instructive contexts that involved both visual and auditory modalities. The signal generated by sequential priming may permit the sense of separation between events to be measured as an extensive psychophysical quantity.
Online feature selection with streaming features.

PubMed

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.
Method of Real-Time Principal-Component Analysis

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu

2005-01-01

Dominant-element-based gradient descent and dynamic initial learning rate (DOGEDYN) is a method of sequential principal-component analysis (PCA) that is well suited for such applications as data compression and extraction of features from sets of data. In comparison with a prior method of gradient-descent-based sequential PCA, this method offers a greater rate of learning convergence. Like the prior method, DOGEDYN can be implemented in software. However, the main advantage of DOGEDYN over the prior method lies in the facts that it requires less computation and can be implemented in simpler hardware. It should be possible to implement DOGEDYN in compact, low-power, very-large-scale integrated (VLSI) circuitry that could process data in real time.
Multiple independent identification decisions: a method of calibrating eyewitness identifications.

PubMed

Pryke, Sean; Lindsay, R C L; Dysart, Jennifer E; Dupuis, Paul

2004-02-01

Two experiments (N = 147 and N = 90) explored the use of multiple independent lineups to identify a target seen live. In Experiment 1, simultaneous face, body, and sequential voice lineups were used. In Experiment 2, sequential face, body, voice, and clothing lineups were used. Both studies demonstrated that multiple identifications (by the same witness) from independent lineups of different features are highly diagnostic of suspect guilt (G. L. Wells & R. C. L. Lindsay, 1980). The number of suspect and foil selections from multiple independent lineups provides a powerful method of calibrating the accuracy of eyewitness identification. Implications for use of current methods are discussed. ((c) 2004 APA, all rights reserved)
Overcoming catastrophic forgetting in neural networks

PubMed Central

Kirkpatrick, James; Pascanu, Razvan; Rabinowitz, Neil; Veness, Joel; Desjardins, Guillaume; Rusu, Andrei A.; Milan, Kieran; Quan, John; Ramalho, Tiago; Grabska-Barwinska, Agnieszka; Hassabis, Demis; Clopath, Claudia; Kumaran, Dharshan; Hadsell, Raia

2017-01-01

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on a hand-written digit dataset and by learning several Atari 2600 games sequentially. PMID:28292907
A Method for Isolation of Extracellular Vesicles and Characterization of Exosomes from Brain Extracellular Space.

PubMed

Pérez-González, Rocío; Gauthier, Sebastien A; Kumar, Asok; Saito, Mitsuo; Saito, Mariko; Levy, Efrat

2017-01-01

Extracellular vesicles (EV), including exosomes, secreted vesicles of endocytic origin, and microvesicles derived from the plasma membrane, have been widely isolated and characterized from conditioned culture media and bodily fluids. The difficulty in isolating EV from tissues, however, has hindered their study in vivo. Here, we describe a novel method designed to isolate EV and characterize exosomes from the extracellular space of brain tissues. The purification of EV is achieved by gentle dissociation of the tissue to free the brain extracellular space, followed by sequential low-speed centrifugations, filtration, and ultracentrifugations. To further purify EV from other extracellular components, they are separated on a sucrose step gradient. Characterization of the sucrose step gradient fractions by electron microscopy demonstrates that this method yields pure EV preparations free of large vesicles, subcellular organelles, or debris. The level of EV secretion and content are determined by assays for acetylcholinesterase activity and total protein estimation, and exosomal identification and protein content are analyzed by Western blot and immuno-electron microscopy. Additionally, we present here a method to delipidate EV in order to improve the resolution of downstream electrophoretic analysis of EV proteins.
On-chip immobilization of planarians for in vivo imaging.

PubMed

Dexter, Joseph P; Tamme, Mary B; Lind, Christine H; Collins, Eva-Maria S

2014-09-17

Planarians are an important model organism for regeneration and stem cell research. A complete understanding of stem cell and regeneration dynamics in these animals requires time-lapse imaging in vivo, which has been difficult to achieve due to a lack of tissue-specific markers and the strong negative phototaxis of planarians. We have developed the Planarian Immobilization Chip (PIC) for rapid, stable immobilization of planarians for in vivo imaging without injury or biochemical alteration. The chip is easy and inexpensive to fabricate, and worms can be mounted for and removed after imaging within minutes. We show that the PIC enables significantly higher-stability immobilization than can be achieved with standard techniques, allowing for imaging of planarians at sub-cellular resolution in vivo using brightfield and fluorescence microscopy. We validate the performance of the PIC by performing time-lapse imaging of planarian wound closure and sequential imaging over days of head regeneration. We further show that the device can be used to immobilize Hydra, another photophobic regenerative model organism. The simple fabrication, low cost, ease of use, and enhanced specimen stability of the PIC should enable its broad application to in vivo studies of stem cell and regeneration dynamics in planarians and Hydra.
On-chip immobilization of planarians for in vivo imaging

PubMed Central

Dexter, Joseph P.; Tamme, Mary B.; Lind, Christine H.; Collins, Eva-Maria S.

2014-01-01

Planarians are an important model organism for regeneration and stem cell research. A complete understanding of stem cell and regeneration dynamics in these animals requires time-lapse imaging in vivo, which has been difficult to achieve due to a lack of tissue-specific markers and the strong negative phototaxis of planarians. We have developed the Planarian Immobilization Chip (PIC) for rapid, stable immobilization of planarians for in vivo imaging without injury or biochemical alteration. The chip is easy and inexpensive to fabricate, and worms can be mounted for and removed after imaging within minutes. We show that the PIC enables significantly higher-stability immobilization than can be achieved with standard techniques, allowing for imaging of planarians at sub-cellular resolution in vivo using brightfield and fluorescence microscopy. We validate the performance of the PIC by performing time-lapse imaging of planarian wound closure and sequential imaging over days of head regeneration. We further show that the device can be used to immobilize Hydra, another photophobic regenerative model organism. The simple fabrication, low cost, ease of use, and enhanced specimen stability of the PIC should enable its broad application to in vivo studies of stem cell and regeneration dynamics in planarians and Hydra. PMID:25227263
Lysine Methylation of Nuclear Co-repressor Receptor Interacting Protein 140

PubMed Central

Huq, MD Mostaqul; Ha, Sung Gil; Barcelona, Helene; Wei, Li-Na

2009-01-01

Receptor interacting protein 140 (RIP140) undergoes extensive posttranslational modifications (PTMs), including phosphorylation, acetylation, arginine methylation, and pyridoxylation. PTMs affect its sub-cellular distribution, protein-protein interaction, and biological activity in adipocyte differentiation. Arginine methylation on Arg240, Arg650, and Arg948 suppresses the repressive activity of RIP140. Here we find that endogenous RIP140 in differentiated 3T3-L1 cells is also modified by lysine methylation. Three lysine residues, Lys591, Lys653, and Lys757 are mapped as potential methylation sites by mass spectrometry. Site-directed mutagenesis study shows that lysine methylation enhances its gene repressive activity. Mutation of lysine methylation sites enhances arginine methylation, while mutation on arginine methylation sites has little effect on its lysine methylation, suggesting a relationship between lysine methylation and arginine methylation. Kinetic analysis of PTMs of endogenous RIP140 in differentiated 3T3-L1 cells demonstrates sequential modifications on RIP140, initiated from constitutive lysine methylation, followed by increased arginine methylation later in differentiation. This study reveals a potential hierarchy of modifications, at least for lysine and arginine methylation, which bi-directionally regulate the functionality of a non-histone protein. PMID:19216533
Homosubtypic and heterosubtypic antibodies against highly pathogenic avian influenza H5N1 recombinant proteins in H5N1 survivors and non-H5N1 subjects.

PubMed

Noisumdaeng, Pirom; Pooruk, Phisanu; Prasertsopon, Jarunee; Assanasen, Susan; Kitphati, Rungrueng; Auewarakul, Prasert; Puthavathana, Pilaipan

2014-04-01

Six recombinant vaccinia viruses containing HA, NA, NP, M or NS gene insert derived from a highly pathogenic avian influenza H5N1 virus, and the recombinant vaccinia virus harboring plasmid backbone as the virus control were constructed. The recombinant proteins were characterized for their expression and subcellular locations in TK(-) cells. Antibodies to the five recombinant proteins were detected in all 13 sequential serum samples collected from four H5N1 survivors during four years of follow-up; and those directed to rVac-H5 HA and rVac-NA proteins were found in higher titers than those directed to the internal proteins as revealed by indirect immunofluorescence assay. Although all 28 non-H5N1 subjects had no neutralizing antibodies against H5N1 virus, they did have cross-reactive antibodies to those five recombinant proteins. A significant increase in cross-reactive antibody titer to rVac-H5 HA and rVac-NA was found in paired blood samples from patients infected with the 2009 pandemic virus. Copyright © 2014 Elsevier Inc. All rights reserved.
Sequential congruency effects: disentangling priming and conflict adaptation.

PubMed

Puccioni, Olga; Vallesi, Antonino

2012-09-01

Responding to the color of a word is slower and less accurate if the word refers to a different color (incongruent condition) than if it refers to the same color (congruent condition). This phenomenon, known as the Stroop effect, is modulated by sequential effects: it is bigger when the current trial is preceded by a congruent condition than by an incongruent one in the previous trial. Whether this phenomenon is due to priming mechanisms or to cognitive control is still debated. To disentangle the contribution of priming with respect to conflict adaptation mechanisms in determining sequential effects, two experiments were designed here with a four-alternative forced choice (4-AFC) Stroop task: in the first one only trials with complete alternations of features were used, while in the second experiment all possible types of repetitions were presented. Both response times (RTs) and errors were evaluated. Conflict adaptation effects on RTs were limited to congruent trials and were exclusively due to priming: they disappeared in the priming-free experiment and, in the second experiment, they occurred in sequences with feature repetitions but not in complete alternation sequences. Error results, instead, support the presence of conflict adaptation effects in incongruent trials. In priming-free sequences (experiment 1 and complete alternation sequences of experiment 2) with incongruent previous trials there was no error Stroop effect, while this effect was significant with congruent previous trials. These results indicate that cognitive control may modulate performance above and beyond priming effects.
Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions

PubMed Central

Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D.; Jeong, Jaeseung

2014-01-01

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices. PMID:25122498
A Feature Selection Algorithm to Compute Gene Centric Methylation from Probe Level Methylation Data.

PubMed

Baur, Brittany; Bozdag, Serdar

2016-01-01

DNA methylation is an important epigenetic event that effects gene expression during development and various diseases such as cancer. Understanding the mechanism of action of DNA methylation is important for downstream analysis. In the Illumina Infinium HumanMethylation 450K array, there are tens of probes associated with each gene. Given methylation intensities of all these probes, it is necessary to compute which of these probes are most representative of the gene centric methylation level. In this study, we developed a feature selection algorithm based on sequential forward selection that utilized different classification methods to compute gene centric DNA methylation using probe level DNA methylation data. We compared our algorithm to other feature selection algorithms such as support vector machines with recursive feature elimination, genetic algorithms and ReliefF. We evaluated all methods based on the predictive power of selected probes on their mRNA expression levels and found that a K-Nearest Neighbors classification using the sequential forward selection algorithm performed better than other algorithms based on all metrics. We also observed that transcriptional activities of certain genes were more sensitive to DNA methylation changes than transcriptional activities of other genes. Our algorithm was able to predict the expression of those genes with high accuracy using only DNA methylation data. Our results also showed that those DNA methylation-sensitive genes were enriched in Gene Ontology terms related to the regulation of various biological processes.
Classification of burn wounds using support vector machines

NASA Astrophysics Data System (ADS)

Acha, Begona; Serrano, Carmen; Palencia, Sergio; Murillo, Juan Jose

2004-05-01

The purpose of this work is to improve a previous method developed by the authors for the classification of burn wounds into their depths. The inputs of the system are color and texture information, as these are the characteristics observed by physicians in order to give a diagnosis. Our previous work consisted in segmenting the burn wound from the rest of the image and classifying the burn into its depth. In this paper we focus on the classification problem only. We already proposed to use a Fuzzy-ARTMAP neural network (NN). However, we may take advantage of new powerful classification tools such as Support Vector Machines (SVM). We apply the five-folded cross validation scheme to divide the database into training and validating sets. Then, we apply a feature selection method for each classifier, which will give us the set of features that yields the smallest classification error for each classifier. Features used to classify are first-order statistical parameters extracted from the L*, u* and v* color components of the image. The feature selection algorithms used are the Sequential Forward Selection (SFS) and the Sequential Backward Selection (SBS) methods. As data of the problem faced here are not linearly separable, the SVM was trained using some different kernels. The validating process shows that the SVM method, when using a Gaussian kernel of variance 1, outperforms classification results obtained with the rest of the classifiers, yielding an error classification rate of 0.7% whereas the Fuzzy-ARTMAP NN attained 1.6 %.
Subcellular Redox Targeting: Bridging in Vitro and in Vivo Chemical Biology.

PubMed

Long, Marcus J C; Poganik, Jesse R; Ghosh, Souradyuti; Aye, Yimon

2017-03-17

Networks of redox sensor proteins within discrete microdomains regulate the flow of redox signaling. Yet, the inherent reactivity of redox signals complicates the study of specific redox events and pathways by traditional methods. Herein, we review designer chemistries capable of measuring flux and/or mimicking subcellular redox signaling at the cellular and organismal level. Such efforts have begun to decipher the logic underlying organelle-, site-, and target-specific redox signaling in vitro and in vivo. These data highlight chemical biology as a perfect gateway to interrogate how nature choreographs subcellular redox chemistry to drive precision redox biology.
Critical behavior of subcellular density organization during neutrophil activation and migration.

PubMed

Baker-Groberg, Sandra M; Phillips, Kevin G; Healy, Laura D; Itakura, Asako; Porter, Juliana E; Newton, Paul K; Nan, Xiaolin; McCarty, Owen J T

2015-12-01

Physical theories of active matter continue to provide a quantitative understanding of dynamic cellular phenomena, including cell locomotion. Although various investigations of the rheology of cells have identified important viscoelastic and traction force parameters for use in these theoretical approaches, a key variable has remained elusive both in theoretical and experimental approaches: the spatiotemporal behavior of the subcellular density. The evolution of the subcellular density has been qualitatively observed for decades as it provides the source of image contrast in label-free imaging modalities (e.g., differential interference contrast, phase contrast) used to investigate cellular specimens. While these modalities directly visualize cell structure, they do not provide quantitative access to the structures being visualized. We present an established quantitative imaging approach, non-interferometric quantitative phase microscopy, to elucidate the subcellular density dynamics in neutrophils undergoing chemokinesis following uniform bacterial peptide stimulation. Through this approach, we identify a power law dependence of the neutrophil mean density on time with a critical point, suggesting a critical density is required for motility on 2D substrates. Next we elucidate a continuum law relating mean cell density, area, and total mass that is conserved during neutrophil polarization and migration. Together, our approach and quantitative findings will enable investigators to define the physics coupling cytoskeletal dynamics with subcellular density dynamics during cell migration.

Critical behavior of subcellular density organization during neutrophil activation and migration

PubMed Central

Baker-Groberg, Sandra M.; Phillips, Kevin G.; Healy, Laura D.; Itakura, Asako; Porter, Juliana E.; Newton, Paul K.; Nan, Xiaolin; McCarty, Owen J.T.

2015-01-01

Physical theories of active matter continue to provide a quantitative understanding of dynamic cellular phenomena, including cell locomotion. Although various investigations of the rheology of cells have identified important viscoelastic and traction force parameters for use in these theoretical approaches, a key variable has remained elusive both in theoretical and experimental approaches: the spatiotemporal behavior of the subcellular density. The evolution of the subcellular density has been qualitatively observed for decades as it provides the source of image contrast in label-free imaging modalities (e.g., differential interference contrast, phase contrast) used to investigate cellular specimens. While these modalities directly visualize cell structure, they do not provide quantitative access to the structures being visualized. We present an established quantitative imaging approach, non-interferometric quantitative phase microscopy, to elucidate the subcellular density dynamics in neutrophils undergoing chemokinesis following uniform bacterial peptide stimulation. Through this approach, we identify a power law dependence of the neutrophil mean density on time with a critical point, suggesting a critical density is required for motility on 2D substrates. Next we elucidate a continuum law relating mean cell density, area, and total mass that is conserved during neutrophil polarization and migration. Together, our approach and quantitative findings will enable investigators to define the physics coupling cytoskeletal dynamics with subcellular density dynamics during cell migration. PMID:26640599
FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

PubMed

Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

2015-10-01

Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.
Imaging Subcellular Structures in the Living Zebrafish Embryo.

PubMed

Engerer, Peter; Plucinska, Gabriela; Thong, Rachel; Trovò, Laura; Paquet, Dominik; Godinho, Leanne

2016-04-02

In vivo imaging provides unprecedented access to the dynamic behavior of cellular and subcellular structures in their natural context. Performing such imaging experiments in higher vertebrates such as mammals generally requires surgical access to the system under study. The optical accessibility of embryonic and larval zebrafish allows such invasive procedures to be circumvented and permits imaging in the intact organism. Indeed the zebrafish is now a well-established model to visualize dynamic cellular behaviors using in vivo microscopy in a wide range of developmental contexts from proliferation to migration and differentiation. A more recent development is the increasing use of zebrafish to study subcellular events including mitochondrial trafficking and centrosome dynamics. The relative ease with which these subcellular structures can be genetically labeled by fluorescent proteins and the use of light microscopy techniques to image them is transforming the zebrafish into an in vivo model of cell biology. Here we describe methods to generate genetic constructs that fluorescently label organelles, highlighting mitochondria and centrosomes as specific examples. We use the bipartite Gal4-UAS system in multiple configurations to restrict expression to specific cell-types and provide protocols to generate transiently expressing and stable transgenic fish. Finally, we provide guidelines for choosing light microscopy methods that are most suitable for imaging subcellular dynamics.
Dynamic changes to survivin subcellular localization are initiated by DNA damage

PubMed Central

Asumen, Maritess Gay; Ifeacho, Tochukwu V; Cockerham, Luke; Pfandl, Christina; Wall, Nathan R

2010-01-01

Subcellular distribution of the apoptosis inhibitor survivin and its ability to relocalize as a result of cell cycle phase or therapeutic insult has led to the hypothesis that these subcellular pools may coincide with different survivin functions. The PIK kinases (ATM, ATR and DNA-PK) phosphorylate a variety of effector substrates that propagate DNA damage signals, resulting in various biological outputs. Here we demonstrate that subcellular repartitioning of survivin in MCF-7 cells as a result of UV light-mediated DNA damage is dependent upon DNA damage-sensing proteins as treatment with the pan PIK kinase inhibitor wortmannin repartitioned survivin in the mitochondria and diminished it from the cytosol and nucleus. Mitochondrial redistribution of survivin, such as was recorded after wortmannin treatment, occurred in cells lacking any one of the three DNA damage sensing protein kinases: DNA-PK, ATM or ATR. However, failed survivin redistribution from the mitochondria in response to low-dose UV occurred only in the cells lacking ATM, implying that ATM may be the primary kinase involved in this process. Taken together, this data implicates survivian’s subcellular distribution is a dynamic physiological process that appears responsive to UV light-initiated DNA damage and that its distribution may be responsible for its multifunctionality. PMID:20856848
Metropolitan open-space protection with uncertain site availability

Treesearch

Robert G. Haight; Stephanie A. Snyder; Charles S. Revelle

2005-01-01

Urban planners acquire open space to protect natural areas and provide public access to recreation opportunities. Because of limited budgets and dynamic land markets, acquisitions take place sequentially depending on available funds and sites. To address these planning features, we formulated a two-period site selection model with two objectives: maximize the...
Sequential Analysis of the Numerical Stroop Effect Reveals Response Suppression

ERIC Educational Resources Information Center

Kadosh, Roi Cohen; Gevers, Wim; Notebaert, Wim

2011-01-01

Automatic processing of irrelevant stimulus dimensions has been demonstrated in a variety of tasks. Previous studies have shown that conflict between relevant and irrelevant dimensions can be reduced when a feature of the irrelevant dimension is repeated. The specific level at which the automatic process is suppressed (e.g., perceptual repetition,…
Robustness of Ability Estimation to Multidimensionality in CAST with Implications to Test Assembly

ERIC Educational Resources Information Center

Zhang, Yanwei; Nandakumar, Ratna

2006-01-01

Computer Adaptive Sequential Testing (CAST) is a test delivery model that combines features of the traditional conventional paper-and-pencil testing and item-based computerized adaptive testing (CAT). The basic structure of CAST is a panel composed of multiple testlets adaptively administered to examinees at different stages. Current applications…
Parallel Consolidation of Simple Features into Visual Short-Term Memory

ERIC Educational Resources Information Center

Mance, Irida; Becker, Mark W.; Liu, Taosheng

2012-01-01

Although considerable research has examined the storage limits of visual short-term memory (VSTM), little is known about the initial formation (i.e., the consolidation) of VSTM representations. A few previous studies have estimated the capacity of consolidation to be one item at a time. Here we used a sequential-simultaneous manipulation to…
PATTERN RECOGNITION APPROACH TO MEDICAL DIAGNOSIS,

DTIC Science & Technology

A sequential method of pattern recognition was used to recognize hyperthyroidism in a sample of 2219 patients being treated at the Straub Clinic in...the most prominent class features are selected. Thus, the symptoms which best distinguish hyperthyroidism are extracted at every step and the number of tests required to reach a diagnosis is reduced. (Author)
Identification of coniferous woods

Treesearch

B. Francis Kukachka

1960-01-01

The identification of coniferous woods is generally regarded as being more difficult than for the hardwood species. This is due to the fact that conifers are more elemental in their structure and, as a consequence, the number of diagnostic features that may he employed is proportionately smaller. Instructions are given here in the sequential use of primary diagnostic...
What Have You Got To Lose? New World Tropical Rainforests. Grades 3-8.

ERIC Educational Resources Information Center

Murphey, Carol E.

In this unit, designed for use with grades three through eight, students explore the biology and peoples of Latin American rainforests and the problems caused by the interactions of people with this environment. The featured activities integrate art, science, language, and social studies. Fourteen lessons, arranged in sequential order, comprise…
Optimal decision-making in mammals: insights from a robot study of rodent texture discrimination

PubMed Central

Lepora, Nathan F.; Fox, Charles W.; Evans, Mathew H.; Diamond, Mathew E.; Gurney, Kevin; Prescott, Tony J.

2012-01-01

Texture perception is studied here in a physical model of the rat whisker system consisting of a robot equipped with a biomimetic vibrissal sensor. Investigations of whisker motion in rodents have led to several explanations for texture discrimination, such as resonance or stick-slips. Meanwhile, electrophysiological studies of decision-making in monkeys have suggested a neural mechanism of evidence accumulation to threshold for competing percepts, described by a probabilistic model of Bayesian sequential analysis. For our robot whisker data, we find that variable reaction-time decision-making with sequential analysis performs better than the fixed response-time maximum-likelihood estimation. These probabilistic classifiers also use whatever available features of the whisker signals aid the discrimination, giving improved performance over a single-feature strategy, such as matching the peak power spectra of whisker vibrations. These results cast new light on how the various proposals for texture discrimination in rodents depend on the whisker contact mechanics and suggest the possibility of a common account of decision-making across mammalian species. PMID:22279155
Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis

PubMed Central

Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James

2013-01-01

Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or ‘expressology’, thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au). PMID:24147765
Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis.

PubMed

Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James

2013-12-01

Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or 'expressology', thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au). © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.
Biodynamics of copper oxide nanoparticles and copper ions in an oligochaete - Part II: Subcellular distribution following sediment exposure

USGS Publications Warehouse

Thit, Amalie; Ramskov, Tina; Croteau, Marie-Noele; Selck, Henriette

2016-01-01

The use and likely incidental release of metal nanoparticles (NPs) is steadily increasing. Despite the increasing amount of published literature on metal NP toxicity in the aquatic environment, very little is known about the biological fate of NPs after sediment exposures. Here, we compare the bioavailability and subcellular distribution of copper oxide (CuO) NPs and aqueous Cu (Cu-Aq) in the sediment-dwelling worm Lumbriculus variegatus. Ten days (d) sediment exposure resulted in marginal Cu bioaccumulation in L. variegatus for both forms of Cu. Bioaccumulation was detected because isotopically enriched 65Cu was used as a tracer. Neither burrowing behavior or survival was affected by the exposure. Once incorporated into tissue, Cu loss was negligible over 10 d of elimination in clean sediment (Cu elimination rate constants were not different from zero). With the exception of day 10, differences in bioaccumulation and subcellular distribution between Cu forms were either not detectable or marginal. After 10 d of exposure to Cu-Aq, the accumulated Cu was primarily partitioned in the subcellular fraction containing metallothionein-like proteins (MTLP, ≈40%) and cellular debris (CD, ≈30%). Cu concentrations in these fractions were significantly higher than in controls. For worms exposed to CuO NPs for 10 d, most of the accumulated Cu was partitioned in the CD fraction (≈40%), which was the only subcellular fraction where the Cu concentration was significantly higher than for the control group. Our results indicate that L. variegatus handle the two Cu forms differently. However, longer-term exposures are suggested in order to clearly highlight differences in the subcellular distribution of these two Cu forms.
Subcellular distribution of raffinose oligosaccharides and other metabolites in summer and winter leaves of Ajuga reptans (Lamiaceae).

PubMed

Findling, Sarah; Zanger, Klaus; Krueger, Stephan; Lohaus, Gertrud

2015-01-01

In Ajuga reptans, raffinose oligosaccharides accumulated during winter. Stachyose, verbascose, and higher RFO oligomers were exclusively found in the vacuole whereas one-fourth of raffinose was localized in the stroma. The evergreen labiate Ajuga reptans L. can grow at low temperature. The carbohydrate metabolism changes during the cold phase, e.g., raffinose family oligosaccharides (RFOs) accumulate. Additionally, A. reptans translocates RFOs in the phloem. In the present study, subcellular concentrations of metabolites were studied in summer and winter leaves of A. reptans to gain further insight into regulatory instances involved in the cold acclimation process and into the function of RFOs. Subcellular metabolite concentrations were determined by non-aqueous fractionation. Volumes of the subcellular compartments of summer and winter leaves were analyzed by morphometric measurements. The metabolite content varied strongly between summer and winter leaves. Soluble metabolites increased up to tenfold during winter whereas the starch content was decreased. In winter leaves, the subcellular distribution showed a shift of carbohydrates from cytoplasm to vacuole and chloroplast. Despite this, the metabolite concentration was higher in all compartments in winter leaves compared to summer leaves because of the much higher total metabolite content in winter leaves. The different oligosaccharides did show different compartmentations. Stachyose, verbascose, and higher RFO oligomers were almost exclusively found in the vacuole whereas one-fourth of raffinose was localized in the stroma. Apparently, the subcellular distribution of the RFOs differs because they fulfill different functions in plant metabolism during winter. Raffinose might function in protecting chloroplast membranes during freezing, whereas higher RFO oligomers may exert protective effects on vacuolar membranes. In addition, the high content of RFOs in winter leaves may also result from reduced consumption of assimilates.
Vaccinia-related kinase 3 (VRK3) sets the circadian period and amplitude by affecting the subcellular localization of clock proteins in mammalian cells

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

Park, Nayoung; Department of Brain Science, Ajou University School of Medicine, 164 Worldcup-ro, Yeongtong-gu, Suwon, Kyunggi-do, 16499; Song, Jieun

In the eukaryotic circadian clock machinery, negative feedback repression of CLOCK (CLK) and BMAL1 transcriptional activity by PERIOD (PER) and CRYPTOCHROME (CRY) underlies the basis for 24 h rhythmic gene expression. Thus, precise regulation of the time-dependent nuclear entry of circadian repressors is crucial to generating normal circadian rhythms. Here, we sought to identify novel kinase(s) that regulate nuclear entry of mammalian CRY1 (mCRY1) with an unbiased screening using red fluorescent protein (RFP)-tagged human kinome expression plasmids in mammalian cells. Transient expression of human vaccinia-related kinase 3 (hVRK3) reduced the nuclear presence of mCRY1. hVRK3 expression also induced alterations in themore » subcellular localization of other core clock proteins, including mCRY2, mPER2, and BMAL1. In contrast, the subcellular localization of mCLK was not changed. Given that singly expressed mCLK mostly resides in the cytoplasm and that nuclear localization sequence (NLS) mutation of hVRK3 attenuated the effect of hVRK3 co-expression on subcellular localization, ectopically expressed hVRK3 presumably reduces the retention of proteins in the nucleus. Finally, downregulation of hvrk3 using siRNA reduced the amplitude and lengthened the period of the cellular bioluminescence rhythm. Taken together, these data suggest that VRK3 plays a role in setting the amplitude and period length of circadian rhythms in mammalian cells. - Highlights: • Screening was performed to identify kinases that regulate CRY1 subcellular localization. • VRK3 alters the subcellular localization of CRY1, CRY2, PER2, and BMAL1. • VRK3 knock-down alters the circadian bioluminescence rhythm in mammalian cells.« less
Optical Coherence Microscopy

NASA Astrophysics Data System (ADS)

Aguirre, Aaron D.; Zhou, Chao; Lee, Hsiang-Chieh; Ahsen, Osman O.; Fujimoto, James G.

Cellular imaging of human tissues remains an important advance for many clinical applications of optical coherence tomography (OCT). Imaging cells with traditional OCT systems has not been possible due to the limited transverse resolution of such techniques. Optical coherence microscopy (OCM) refers to OCT methods that achieve high transverse resolution to visualize cells and subcellular features. This chapter provides a comprehensive discussion of the rationale for cellular imaging in human tissues as well as a review of the key technological advances required to achieve it. Time domain and Fourier domain OCM approaches are described with an emphasis on state of the art system designs, including miniaturized endoscopic imaging probes. Clinical applications are discussed and multiple examples of cellular imaging in human tissues are provided.
Clinico-Pathologic Relevance of Survivin Splice Variant Expression in Cancer

PubMed Central

de Necochea-Campion, Rosalia; Chen, Chien-Shing; Mirshahidi, Saied; Howard, Frank D.; Wall, Nathan R.

2013-01-01

Survivin is a member of the inhibitor of apoptosis (IAP) family and has multifunctional properties that include aspects of proliferation, invasion and cell survival control. Survivin is a promising candidate for targeted cancer therapy as its expression is associated with poor clinical outcome, more aggressive clinico-pathologic features, and resistance to radiation and chemotherapy. In the present review the different properties of the Survivin splice variants are discussed and their activities correlated with different aspects of cancer cell biology, to include subcellular location. Special emphasis is placed on our current understanding of these Survivin splice variants influence on each other and on the phenotypic responses to therapy that they may control. PMID:23791888
Comparison of Different EHG Feature Selection Methods for the Detection of Preterm Labor

PubMed Central

Alamedine, D.; Khalil, M.; Marque, C.

2013-01-01

Numerous types of linear and nonlinear features have been extracted from the electrohysterogram (EHG) in order to classify labor and pregnancy contractions. As a result, the number of available features is now very large. The goal of this study is to reduce the number of features by selecting only the relevant ones which are useful for solving the classification problem. This paper presents three methods for feature subset selection that can be applied to choose the best subsets for classifying labor and pregnancy contractions: an algorithm using the Jeffrey divergence (JD) distance, a sequential forward selection (SFS) algorithm, and a binary particle swarm optimization (BPSO) algorithm. The two last methods are based on a classifier and were tested with three types of classifiers. These methods have allowed us to identify common features which are relevant for contraction classification. PMID:24454536

Design and validation of a new ratiometric intracellular pH imaging probe using lanthanide-doped upconverting nanoparticles.

PubMed

Du, Shuoren; Hernández-Gil, Javier; Dong, Hao; Zheng, Xiaoyu; Lyu, Guangming; Bañobre-López, Manuel; Gallo, Juan; Sun, Ling-Dong; Yan, Chun-Hua; Long, Nicholas J

2017-10-17

pH homeostasis is strictly controlled at a subcellular level. A deregulation of the intra/extra/subcellular pH environment is associated with a number of diseases and as such, the monitoring of the pH state of cells and tissues is a valuable diagnostic tool. To date, only a few tools have been developed to measure the pH in living cells with the spatial resolution needed for intracellular imaging. Among the techniques available, only optical imaging offers enough resolution and biocompatibility to be proposed for subcellular pH monitoring. We present herein a ratiometric probe based on upconversion nanoparticles modified with a pH sensitive moiety for the quantitative imaging of pH at the subcellular level in living cells. This system provides the properties required for live cell quantitative imaging i.e. positive cellular uptake, biocompatibility, long wavelength excitation, sensitive response to pH within a biologically relevant range, and self-referenced signal.
Identification of Mycobacterial Surface Proteins Released into Subcellular Compartments of Infected Macrophages

PubMed Central

Beatty, Wandy L.; Russell, David G.

2000-01-01

Considerable effort has focused on the identification of proteins secreted from Mycobacterium spp. that contribute to the development of protective immunity. Little is known, however, about the release of mycobacterial proteins from the bacterial phagosome and the potential role of these molecules in chronically infected macrophages. In the present study, the release of mycobacterial surface proteins from the bacterial phagosome into subcellular compartments of infected macrophages was analyzed. Mycobacterium bovis BCG was surface labeled with fluorescein-tagged succinimidyl ester, an amine-reactive probe. The fluorescein tag was then used as a marker for the release of bacterial proteins in infected macrophages. Fractionation studies revealed bacterial proteins within subcellular compartments distinct from mycobacteria and mycobacterial phagosomes. To identify these proteins, subcellular fractions free of bacteria were probed with mycobacterium-specific antibodies. The fibronectin attachment protein and proteins of the antigen 85-kDa complex were identified among the mycobacterial proteins released from the bacterial phagosome. PMID:11083824
Subcellular Localization of Pseudomonas syringae pv. tomato Effector Proteins in Plants.

PubMed

Aung, Kyaw; Xin, Xiufang; Mecey, Christy; He, Sheng Yang

2017-01-01

Animal and plant pathogenic bacteria use type III secretion systems to translocate proteinaceous effectors to subvert innate immunity of their host organisms. Type III secretion/effector systems are a crucial pathogenicity factor in many bacterial pathogens of plants and animals. Pseudomonas syringae pv. tomato (Pst) DC3000 injects a total of 36 protein effectors that target a variety of host proteins. Studies of a subset of Pst DC3000 effectors demonstrated that bacterial effectors, once inside the host cell, are localized to different subcellular compartments, including plasma membrane, cytoplasm, mitochondria, chloroplast, and Trans-Golgi network, to carry out their virulence functions. Identifying the subcellular localization of bacterial effector proteins in host cells could provide substantial clues to understanding the molecular and cellular basis of the virulence activities of effector proteins. In this chapter, we present methods for transient or stable expression of bacterial effector proteins in tobacco and/or Arabidopsis thaliana for live cell imaging as well as confirming the subcellular localization in plants using fluorescent organelle markers or chemical treatment.
Review: Microbial Analysis in Dielectrophoretic Microfluidic Systems

PubMed Central

Fernandez, Renny E.; Rohani, Ali; Farmehini, Vahid; Swami, Nathan S.

2017-01-01

Infections caused by various known and emerging pathogenic microorganisms, including antibiotic-resistant strains, are a major threat to global health and well-being. This highlights the urgent need for detection systems for microbial identification, quantification and characterization towards assessing infections, prescribing therapies and understanding the dynamic cellular modifications. Current state-of-the-art microbial detection systems exhibit a trade-off between sensitivity and assay time, which could be alleviated by selective and label-free microbial capture onto the sensor surface from dilute samples. AC electrokinetic methods, such as dielectrophoresis, enable frequency-selective capture of viable microbial cells and spores due to polarization based on their distinguishing size, shape and sub-cellular compositional characteristics, for downstream coupling to various detection modalities. Following elucidation of the polarization mechanisms that distinguish bacterial cells from each other, as well as from mammalian cells, this review compares the microfluidic platforms for dielectrophoretic manipulation of microbials and their coupling to various detection modalities, including immuno-capture, impedance measurement, Raman spectroscopy and nucleic acid amplification methods, as well as for phenotypic assessment of microbial viability and antibiotic susceptibility. Based on the urgent need within point-of-care diagnostics towards reducing assay times and enhancing capture of the target organism, as well as the emerging interest in isolating intact microbials based on their phenotype and subcellular features, we envision widespread adoption of these label-free and selective electrokinetic techniques. PMID:28372723
Extrasynaptic N-Methyl-d-aspartate (NMDA) Receptor Stimulation Induces Cytoplasmic Translocation of the CDKL5 Kinase and Its Proteasomal Degradation*

PubMed Central

Rusconi, Laura; Kilstrup-Nielsen, Charlotte; Landsberger, Nicoletta

2011-01-01

Mutations in the X-linked gene cyclin-dependent kinase-like 5 (CDKL5) have been found in patients with epileptic encephalopathy characterized by early onset intractable epilepsy, including infantile spasms and other types of seizures, severe developmental delay, and often the development of Rett syndrome-like features. Despite its clear involvement in proper brain development, CDKL5 functions are still far from being understood. In this study, we analyzed the subcellular localization of the endogenous kinase in primary murine hippocampal neurons. CDKL5 was localized both in nucleus and cytoplasm and, conversely to proliferating cells, did not undergo constitutive shuttling between these compartments. Nevertheless, glutamate stimulation was able to induce the exit of the kinase from the nucleus and its subsequent accumulation in the perinuclear cytoplasm. Moreover, we found that sustained glutamate stimulation promoted CDKL5 proteasomal degradation. Both events were mediated by the specific activation of extrasynaptic pool of N-methyl-d-aspartate receptors. Proteasomal degradation was also induced by withdrawal of neurotrophic factors and hydrogen peroxide treatment, two different paradigms of cell death. Altogether, our results indicate that both subcellular localization and expression of CDKL5 are modulated by the activation of extrasynaptic N-methyl-d-aspartate receptors and suggest regulation of CDKL5 by cell death pathways. PMID:21832092
Applications of geostatistics and Markov models for logo recognition

NASA Astrophysics Data System (ADS)

Pham, Tuan

2003-01-01

Spatial covariances based on geostatistics are extracted as representative features of logo or trademark images. These spatial covariances are different from other statistical features for image analysis in that the structural information of an image is independent of the pixel locations and represented in terms of spatial series. We then design a classifier in the sense of hidden Markov models to make use of these geostatistical sequential data to recognize the logos. High recognition rates are obtained from testing the method against a public-domain logo database.
Distribution of polycyclic aromatic hydrocarbons in subcellular root tissues of ryegrass (Lolium multiflorum Lam.)

PubMed Central

2010-01-01

Background Because of the increasing quantity and high toxicity to humans of polycyclic aromatic hydrocarbons (PAHs) in the environment, several bioremediation mechanisms and protocols have been investigated to restore PAH-contaminated sites. The transport of organic contaminants among plant cells via tissues and their partition in roots, stalks, and leaves resulting from transpiration and lipid content have been extensively investigated. However, information about PAH distributions in intracellular tissues is lacking, thus limiting the further development of a mechanism-based phytoremediation strategy to improve treatment efficiency. Results Pyrene exhibited higher uptake and was more recalcitrant to metabolism in ryegrass roots than was phenanthrene. The kinetic processes of uptake from ryegrass culture medium revealed that these two PAHs were first adsorbed onto root cell walls, and they then penetrated cell membranes and were distributed in intracellular organelle fractions. At the beginning of uptake (< 50 h), adsorption to cell walls dominated the subcellular partitioning of the PAHs. After 96 h of uptake, the subcellular partition of PAHs approached a stable state in the plant water system, with the proportion of PAH distributed in subcellular fractions being controlled by the lipid contents of each component. Phenanthrene and pyrene primarily accumulated in plant root cell walls and organelles, with about 45% of PAHs in each of these two fractions, and the remainder was retained in the dissolved fraction of the cells. Because of its higher lipophilicity, pyrene displayed greater accumulation factors in subcellular walls and organelle fractions than did phenanthrene. Conclusions Transpiration and the lipid content of root cell fractions are the main drivers of the subcellular partition of PAHs in roots. Initially, PAHs adsorb to plant cell walls, and they then gradually diffuse into subcellular fractions of tissues. The lipid content of intracellular components determines the accumulation of lipophilic compounds, and the diffusion rate is related to the concentration gradient established between cell walls and cell organelles. Our results offer insights into the transport mechanisms of PAHs in ryegrass roots and their diffusion in root cells. PMID:20860818
Real-time skin feature identification in a time-sequential video stream

NASA Astrophysics Data System (ADS)

Kramberger, Iztok

2005-04-01

Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.
Article and method of forming an article

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

Lacy, Benjamin Paul; Kottilingam, Srikanth Chandrudu; Dutta, Sandip

Provided are an article and a method of forming an article. The method includes providing a metallic powder, heating the metallic powder to a temperature sufficient to joint at least a portion of the metallic powder to form an initial layer, sequentially forming additional layers in a build direction by providing a distributed layer of the metallic powder over the initial layer and heating the distributed layer of the metallic powder, repeating the steps of sequentially forming the additional layers in the build direction to form a portion of the article having a hollow space formed in the build direction,more » and forming an overhang feature extending into the hollow space. The article includes an article formed by the method described herein.« less
Semi-supervised protein subcellular localization.

PubMed

Xu, Qian; Hu, Derek Hao; Xue, Hong; Yu, Weichuan; Yang, Qiang

2009-01-30

Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data. In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions. Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.
Studies on proinsulin and proglucagon biosynthesis and conversion at the subcellular level: I. Fractionation procedure and characterization of the subcellular fractions

PubMed Central

Noe, BD; Baste, CA; Bauer, GE

1977-01-01

Anglerfish islets were homogenized in 0.25 M sucrose and separated into seven separate subcellular fractions by differential and discontinuous density gradient centrifugation. The objective was to isolate microsomes and secretory granules in a highly purified state. The fractions were characterized by electron microscopy and chemical analyses. Each fraction was assayed for its content of protein, RNA, DNA, immunoreactive insulin (IRI), and immunoreactive glucagon (IRG). Ultrastructural examination showed that two of the seven subcellular fractions contain primarily mitochondria, and that two others consist almost exclusively of secretory granules. A fifth fraction contains rough and smooth microsomal vesicles. The remaining two fractions are the cell supernate and the nuclei and cell debris. The content of DNA and RNA in all fractions is consistent with the observed ultrastructure. More than 82 percent of the total cellular IRI and 89(percent) of the total cellular IRG are found in the fractions of secretory granules. The combined fractions of secretory granules and microsomes consistently yield >93 percent of the total IRG. These results indicate that the fractionation procedure employed yields fractions of microsomes and secretory granules that contain nearly all the immunoassayable insulin and glucagons found in whole islet tissue. These fractions are thus considered suitable for study of proinsulin and proglucagon biosynthesis and their metabolic conversion at the subcellular level. PMID:328517
Separate responses of karyopherins to glucose and amino acid availability regulate nucleocytoplasmic transport

PubMed Central

Huang, Hsiao-Yun; Hopper, Anita K.

2014-01-01

The importin-β family members (karyopherins) mediate the majority of nucleocytoplasmic transport. Msn5 and Los1, members of the importin-β family, function in tRNA nuclear export. tRNAs move bidirectionally between the nucleus and the cytoplasm. Nuclear tRNA accumulation occurs upon amino acid (aa) or glucose deprivation. To understand the mechanisms regulating tRNA subcellular trafficking, we investigated whether Msn5 and Los1 are regulated in response to nutrient availability. We provide evidence that tRNA subcellular trafficking is regulated by distinct aa-sensitive and glucose-sensitive mechanisms. Subcellular distributions of Msn5 and Los1 are altered upon glucose deprivation but not aa deprivation. Redistribution of tRNA exportins from the nucleus to the cytoplasm likely provides one mechanism for tRNA nuclear distribution upon glucose deprivation. We extended our studies to other members of the importin-β family and found that all tested karyopherins invert their subcellular distributions upon glucose deprivation but not aa deprivation. Glucose availability regulates the subcellular distributions of karyopherins likely due to alteration of the RanGTP gradient since glucose deprivation causes redistribution of Ran. Thus nuclear–cytoplasmic distribution of macromolecules is likely generally altered upon glucose deprivation due to collapse of the RanGTP gradient and redistribution of karyopherins between the nucleus and the cytoplasm. PMID:25057022
Organelle-targeting surface-enhanced Raman scattering (SERS) nanosensors for subcellular pH sensing.

PubMed

Shen, Yanting; Liang, Lijia; Zhang, Shuqin; Huang, Dianshuai; Zhang, Jing; Xu, Shuping; Liang, Chongyang; Xu, Weiqing

2018-01-25

The pH value of subcellular organelles in living cells is a significant parameter in the physiological activities of cells. Its abnormal fluctuations are commonly believed to be associated with cancers and other diseases. Herein, a series of surface-enhanced Raman scattering (SERS) nanosensors with high sensitivity and targeting function was prepared for the quantification and monitoring of pH values in mitochondria, nucleus, and lysosome. The nanosensors were composed of gold nanorods (AuNRs) functionalized with a pH-responsive molecule (4-mercaptopyridine, MPy) and peptides that could specifically deliver the AuNRs to the targeting subcellular organelles. The localization of our prepared nanoprobes in specific organelles was confirmed by super-high resolution fluorescence imaging and bio-transmission electron microscopy (TEM) methods. By the targeting ability, the pH values of the specific organelles can be determined by monitoring the vibrational spectral changes of MPy with different pH values. Compared to the cases of reported lysosome and cytoplasm SERS pH sensors, more accurate pH values of mitochondria and nucleus, which could be two additional intracellular tracers for subcellular microenvironments, were disclosed by this SERS approach, further improving the accuracy of discrimination of related diseases. Our sensitive SERS strategy can also be employed to explore crucial physiological and biological processes that are related to subcellular pH fluctuations.
Subcellular localization and cytoplasmic complex status of endogenous Keap1.

PubMed

Watai, Yoriko; Kobayashi, Akira; Nagase, Hiroko; Mizukami, Mio; McEvoy, Justina; Singer, Jeffrey D; Itoh, Ken; Yamamoto, Masayuki

2007-10-01

Keap1 acts as a sensor for oxidative/electrophilic stress, an adaptor for Cullin-3-based ubiquitin ligase, and a regulator of Nrf2 activity through the interaction with Nrf2 Neh2 domain. However, the mechanism(s) of Nrf2 migration into the nucleus in response to stress remains largely unknown due to the lack of a reliable antibody for the detection of endogenous Keap1 molecule. Here, we report the generation of a new monoclonal antibody for the detection of endogenous Keap1 molecules. Immunocytochemical analysis of mouse embryonic fibroblasts with the antibody revealed that under normal, unstressed condition, Keap1 is localized primarily in the cytoplasm with minimal amount in the nucleus and endoplasmic reticulum. This subcellular localization profile of Keap1 appears unchanged after treatment of cells with diethyl maleate, an electrophile, and/or Leptomycin B, a nuclear export inhibitor. Subcellular fractionation analysis of mouse liver cells showed similar results. No substantial change in the subcellular distribution profile could be observed in cells isolated from butylated hydroxyanisole-treated mice. Analyses of sucrose density gradient centrifugation of mouse liver cells indicated that Keap1 appears to form multiprotein complexes in the cytoplasm. These results demonstrate that endogenous Keap1 remains mostly in the cytoplasm, and electrophiles promote nuclear accumulation of Nrf2 without altering the subcellular localization of Keap1.
Distinct Cellular and Subcellular Distributions of G Protein-Coupled Receptor Kinase and Arrestin Isoforms in the Striatum

PubMed Central

Bychkov, Evgeny; Zurkovsky, Lilia; Garret, Mika B.; Ahmed, Mohamed R.; Gurevich, Eugenia V.

2012-01-01

G protein-coupled receptor kinases (GRKs) and arrestins mediate desensitization of G protein-coupled receptors (GPCR). Arrestins also mediate G protein-independent signaling via GPCRs. Since GRK and arrestins demonstrate no strict receptor specificity, their functions in the brain may depend on their cellular complement, expression level, and subcellular targeting. However, cellular expression and subcellular distribution of GRKs and arrestins in the brain is largely unknown. We show that GRK isoforms GRK2 and GRK5 are similarly expressed in direct and indirect pathway neurons in the rat striatum. Arrestin-2 and arrestin-3 are also expressed in neurons of both pathways. Cholinergic interneurons are enriched in GRK2, arrestin-3, and GRK5. Parvalbumin-positive interneurons express more of GRK2 and less of arrestin-2 than medium spiny neurons. The GRK5 subcellular distribution in the human striatal neurons is altered by its phosphorylation: unphosphorylated enzyme preferentially localizes to synaptic membranes, whereas phosphorylated GRK5 is found in plasma membrane and cytosolic fractions. Both GRK isoforms are abundant in the nucleus of human striatal neurons, whereas the proportion of both arrestins in the nucleus was equally low. However, overall higher expression of arrestin-2 yields high enough concentration in the nucleus to mediate nuclear functions. These data suggest cell type- and subcellular compartment-dependent differences in GRK/arrestin-mediated desensitization and signaling. PMID:23139825
Distinct cellular and subcellular distributions of G protein-coupled receptor kinase and arrestin isoforms in the striatum.

PubMed

Bychkov, Evgeny; Zurkovsky, Lilia; Garret, Mika B; Ahmed, Mohamed R; Gurevich, Eugenia V

2012-01-01

G protein-coupled receptor kinases (GRKs) and arrestins mediate desensitization of G protein-coupled receptors (GPCR). Arrestins also mediate G protein-independent signaling via GPCRs. Since GRK and arrestins demonstrate no strict receptor specificity, their functions in the brain may depend on their cellular complement, expression level, and subcellular targeting. However, cellular expression and subcellular distribution of GRKs and arrestins in the brain is largely unknown. We show that GRK isoforms GRK2 and GRK5 are similarly expressed in direct and indirect pathway neurons in the rat striatum. Arrestin-2 and arrestin-3 are also expressed in neurons of both pathways. Cholinergic interneurons are enriched in GRK2, arrestin-3, and GRK5. Parvalbumin-positive interneurons express more of GRK2 and less of arrestin-2 than medium spiny neurons. The GRK5 subcellular distribution in the human striatal neurons is altered by its phosphorylation: unphosphorylated enzyme preferentially localizes to synaptic membranes, whereas phosphorylated GRK5 is found in plasma membrane and cytosolic fractions. Both GRK isoforms are abundant in the nucleus of human striatal neurons, whereas the proportion of both arrestins in the nucleus was equally low. However, overall higher expression of arrestin-2 yields high enough concentration in the nucleus to mediate nuclear functions. These data suggest cell type- and subcellular compartment-dependent differences in GRK/arrestin-mediated desensitization and signaling.
ALA-mediated PDT of melanoma tumors: light-sensitizer interactions determined by a novel spectral imaging system

NASA Astrophysics Data System (ADS)

Malik, Zvi; Dishi, M.

1995-05-01

The subcellular localization of endogenous protoporphyrin (endo- PP) during photosensitization in B-16 melanoma cells was analyzed by a novel spectral imaging system, the SpectraCube 1000. The melanoma cells were incubated with 5-aminolevulinic acid (ALA), and then the fluorescence of endo-PP was recorded in individual living cells by three modes: conventional fluorescence imaging, multipixel point by point fluorescence spectroscopy, and image processing, by operating a function of spectral similarity mapping and reconstructing new images derived from spectral information. The fluorescence image of ALA-treated cells revealed vesicular distribution of endo-PP all over the cytosol, with mitochondrial, lysosomal, as well as endoplasmic reticulum cisternael accumulation. Two main spectral fluorescence peaks were demonstrated at 635 and 705 nm, with intensities that differed from one subcellular site to another. Photoirradiation of the cells included point-specific subcellular fluorescence spectrum changes and demonstrated photoproduct formation. Spectral image reconstruction revealed the local distribution of a chosen spectrum in the photosensitized cells. On the other hand, B 16 cells treated with exogenous protoporphyrin (exo-PP) showed a dominant fluorescence peak at 670 nm and a minor peak at 630 nm. Fluorescence was localized at a perinuclear=Golgi region. Light exposure induced photobleaching and photoproduct-spectral changes followed by relocalization. The new localization at subcellular compartments showed pH dependent spectral shifts and photoproduct formation on a subcellular level.
Synthetic fossilization of soft biological tissues and their shape-preserving transformation into silica or electron-conductive replicas

DOE PAGES

Townson, Jason L.; Lin, Yu-Shen; Chou, Stanley S.; ...

2014-12-08

Structural preservation of complex biological systems from the subcellular to whole organism level in robust forms, enabling dissection and imaging while preserving 3D context, represents an enduring grand challenge in biology. Here we report a simple immersion method for structurally preserving intact organisms via conformal stabilization within silica. This self-limiting process, which we refer to as silica bioreplication, occurs by condensation of water-soluble silicic acid proximally to biomolecular interfaces throughout the organism. Conformal nanoscopic silicification of all biomolecular features imparts structural rigidity enabling the preservation of shape and nano-to-macroscale dimensional features upon drying to form a biocomposite and further highmore » temperature oxidative calcination to form silica replicas or reductive pyrolysis to form electrically conductive carbon replicas of complete organisms. Ultimately, the simplicity and generalizability of this approach should facilitate efforts in biological preservation and analysis and could enable the development of new classes of biomimetic composite materials.« less
Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials

NASA Astrophysics Data System (ADS)

Radivojevic, Milos; Jäckel, David; Altermatt, Michael; Müller, Jan; Viswam, Vijay; Hierlemann, Andreas; Bakkum, Douglas J.

2016-08-01

A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.
Monitoring the process of pulmonary melanoma metastasis using large area and label-free nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Hua, Daozhu; Qi, Shuhong; Li, Hui; Zhang, Zhihong; Fu, Ling

2012-06-01

We performed large area nonlinear optical microscopy (NOM) for label-free monitoring of the process of pulmonary melanoma metastasis ex vivo with subcellular resolution in C57BL/6 mice. Multiphoton autofluorescence (MAF) and second harmonic generation (SHG) images of lung tissue are obtained in a volume of ~2.2 mm×2.2 mm×30 μm. Qualitative differences in morphologic features and quantitative measurement of pathological lung tissues at different time points are characterized. We find that combined with morphological features, the quantitative parameters, such as the intensity ratio of MAF and SHG between pathological tissue and normal tissue and the MAF to SHG index versus depth clearly shows the tissue physiological changes during the process of pulmonary melanoma metastasis. Our results demonstrate that large area NOM succeeds in monitoring the process of pulmonary melanoma metastasis, which can provide a powerful tool for the research in tumor pathophysiology and therapy evaluation.

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431
Sequential ALK Inhibitors Can Select for Lorlatinib-Resistant Compound ALK Mutations in ALK-Positive Lung Cancer.

PubMed

Yoda, Satoshi; Lin, Jessica J; Lawrence, Michael S; Burke, Benjamin J; Friboulet, Luc; Langenbucher, Adam; Dardaei, Leila; Prutisto-Chang, Kylie; Dagogo-Jack, Ibiayi; Timofeevski, Sergei; Hubbeling, Harper; Gainor, Justin F; Ferris, Lorin A; Riley, Amanda K; Kattermann, Krystina E; Timonina, Daria; Heist, Rebecca S; Iafrate, A John; Benes, Cyril H; Lennerz, Jochen K; Mino-Kenudson, Mari; Engelman, Jeffrey A; Johnson, Ted W; Hata, Aaron N; Shaw, Alice T

2018-06-01

The cornerstone of treatment for advanced ALK-positive lung cancer is sequential therapy with increasingly potent and selective ALK inhibitors. The third-generation ALK inhibitor lorlatinib has demonstrated clinical activity in patients who failed previous ALK inhibitors. To define the spectrum of ALK mutations that confer lorlatinib resistance, we performed accelerated mutagenesis screening of Ba/F3 cells expressing EML4-ALK. Under comparable conditions, N -ethyl- N -nitrosourea (ENU) mutagenesis generated numerous crizotinib-resistant but no lorlatinib-resistant clones harboring single ALK mutations. In similar screens with EML4-ALK containing single ALK resistance mutations, numerous lorlatinib-resistant clones emerged harboring compound ALK mutations. To determine the clinical relevance of these mutations, we analyzed repeat biopsies from lorlatinib-resistant patients. Seven of 20 samples (35%) harbored compound ALK mutations, including two identified in the ENU screen. Whole-exome sequencing in three cases confirmed the stepwise accumulation of ALK mutations during sequential treatment. These results suggest that sequential ALK inhibitors can foster the emergence of compound ALK mutations, identification of which is critical to informing drug design and developing effective therapeutic strategies. Significance: Treatment with sequential first-, second-, and third-generation ALK inhibitors can select for compound ALK mutations that confer high-level resistance to ALK-targeted therapies. A more efficacious long-term strategy may be up-front treatment with a third-generation ALK inhibitor to prevent the emergence of on-target resistance. Cancer Discov; 8(6); 714-29. ©2018 AACR. This article is highlighted in the In This Issue feature, p. 663 . ©2018 American Association for Cancer Research.
Isotope labeling of rubisco subunits provides in vivo information on subcellular biosynthesis and exchange of amino acids between compartments.

USDA-ARS?s Scientific Manuscript database

The architecture of plant metabolism includes substantial duplication of metabolite pools and enzyme catalyzed reactions in different subcellular compartments. This poses considerable challenges for understanding the regulation of metabolism particularly in primary metabolism and amino acid biosynth...
Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks

PubMed Central

Zhao, Rui; Yan, Ruqiang; Wang, Jinjiang; Mao, Kezhi

2017-01-01

In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM) has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks (LSTMs) are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods. PMID:28146106
Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks.

PubMed

Zhao, Rui; Yan, Ruqiang; Wang, Jinjiang; Mao, Kezhi

2017-01-30

In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classiﬁcation and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redeﬁne representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM) has been designed here to address raw sensory data. CBLSTM ﬁrstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks(LSTMs) are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods.
Multipurpose Prepregging Machine

NASA Technical Reports Server (NTRS)

Johnston, N. J.; Wilkinson, Steven; Marchello, J. M.; Dixon, D.

1995-01-01

Machine designed and built for variety of uses involving coating or impregnating ("prepregging") fibers, tows, yarns, or webs or tapes made of such fibrous materials with thermoplastic or thermosetting resins. Prepreg materials produced used to make matrix/fiber composite materials. Comprises modules operated individually, sequentially, or simultaneously, depending on nature of specific prepreg material and prepregging technique used. Machine incorporates number of safety features.
Randomized Sequential Individual Assignment in Social Experiments: Evaluating the Design Options Prospectively

ERIC Educational Resources Information Center

Lohr, Sharon L.; Zhu, Xiaoshu

2017-01-01

Many randomized experiments in the social sciences allocate subjects to treatment arms at the time the subjects enroll. Desirable features of the mechanism used to assign subjects to treatment arms are often (1) equal numbers of subjects in intervention and control arms, (2) balanced allocation for population subgroups and across covariates, (3)…
Pre-Modeling Ensures Accurate Solid Models

ERIC Educational Resources Information Center

Gow, George

2010-01-01

Successful solid modeling requires a well-organized design tree. The design tree is a list of all the object's features and the sequential order in which they are modeled. The solid-modeling process is faster and less prone to modeling errors when the design tree is a simple and geometrically logical definition of the modeled object. Few high…
Teen Sexual Behavior. A Leader's Resource of Practical Strategies with Youth.

ERIC Educational Resources Information Center

Berne, Linda A.; Wild, Pamela

The purpose of this book is to assist leaders in a variety of settings to address young people on the critical issues of teenage sexuality. The units are presented in a sequential pattern which covers teenage sexual behavior as it naturally evolves. Detailed information and precise directions for presenting the lessons are featured. The curriculum…
Mobile Guide System Using Problem-Solving Strategy for Museum Learning: A Sequential Learning Behavioural Pattern Analysis

ERIC Educational Resources Information Center

Sung, Y.-T.; Hou, H.-T.; Liu, C.-K.; Chang, K.-E.

2010-01-01

Mobile devices have been increasingly utilized in informal learning because of their high degree of portability; mobile guide systems (or electronic guidebooks) have also been adopted in museum learning, including those that combine learning strategies and the general audio-visual guide systems. To gain a deeper understanding of the features and…
Quantitative and qualitative features of heterologous virus-vector-induced antigen-specific CD8+ T cells against Trypanosoma cruzi infection.

PubMed

Takayama, Eiji; Ono, Takeshi; Carnero, Elena; Umemoto, Saori; Yamaguchi, Yoko; Kanayama, Atsuhiro; Oguma, Takemi; Takashima, Yasuhiro; Tadakuma, Takushi; García-Sastre, Adolfo; Miyahira, Yasushi

2010-11-01

We studied some aspects of the quantitative and qualitative features of heterologous recombinant (re) virus-vector-induced, antigen-specific CD8(+) T cells against Trypanosoma cruzi. We used three different, highly attenuated re-viruses, i.e., influenza virus, adenovirus and vaccinia virus, which all expressed a single, T. cruzi antigen-derived CD8(+) T-cell epitope. The use of two out of three vectors or the triple virus-vector vaccination regimen not only confirmed that the re-vaccinia virus, which was placed last in order for sequential immunisation, was an effective booster for the CD8(+) T-cell immunity in terms of the number of antigen-specific CD8(+) T cells, but also demonstrated that (i) the majority of cells exhibit the effector memory (T(EM)) phenotype, (ii) robustly secrete IFN-γ, (iii) express higher intensity of the CD122 molecule and (iv) present protective activity against T. cruzi infection. In contrast, placing the re-influenza virus last in sequential immunisation had a detrimental effect on the quantitative and qualitative features of CD8(+) T cells. The triple virus-vector vaccination was more effective at inducing a stronger CD8(+) T-cell immunity than using two re-viruses. The different quantitative and qualitative features of CD8(+) T cells induced by different immunisation regimens support the notion that the refinement of the best choice of multiple virus-vector combinations is indispensable for the induction of a maximum number of CD8(+) T cells of high quality. Copyright © 2010 Australian Society for Parasitology Inc. All rights reserved.
Conversation analysis can help to distinguish between epilepsy and non-epileptic seizure disorders: a case comparison.

PubMed

Plug, Leendert; Sharrack, Basil; Reuber, Markus

2009-01-01

Factual items in patients' histories are of limited discriminating value in the differential diagnosis of epilepsy and non-epileptic seizures (NES). A number of studies using a transcript-based sociolinguistic research method inspired by Conversation Analysis (CA) suggest that it is helpful to focus on how patients talk. Previous reports communicated these findings by using particularly clear examples of diagnostically relevant interactional, linguistic and topical features from different patients. They did not discuss the sequential display of different features although this is crucially important from a conversation analytic point of view. This case comparison aims to show clinicians how the discriminating features are displayed by individual patients over the course of a clinical encounter. CA-inspired brief sequential analysis of two first 30-min doctor-patient encounters by a linguist blinded to all medical information. A gold standard diagnosis was made by the recording of a typical seizure with video-EEG. The patient with epilepsy volunteered detailed first person accounts of seizures. The NES patient exhibited resistance to focusing on individual seizure episodes and only provided a detailed seizure description after repeated prompting towards the end of the interview. Although both patients also displayed some linguistic features favouring the alternative diagnosis, the linguist's final diagnostic hypothesis matched the diagnosis made by video-EEG in both cases. This study illustrates the importance of the time point at which patients share information with the doctor. It supports the notion that close attention to how patients communicate can help in the differential diagnosis of seizures.
Sequential Modular Position and Momentum Measurements of a Trapped Ion Mechanical Oscillator

NASA Astrophysics Data System (ADS)

Flühmann, C.; Negnevitsky, V.; Marinelli, M.; Home, J. P.

2018-04-01

The noncommutativity of position and momentum observables is a hallmark feature of quantum physics. However, this incompatibility does not extend to observables that are periodic in these base variables. Such modular-variable observables have been suggested as tools for fault-tolerant quantum computing and enhanced quantum sensing. Here, we implement sequential measurements of modular variables in the oscillatory motion of a single trapped ion, using state-dependent displacements and a heralded nondestructive readout. We investigate the commutative nature of modular variable observables by demonstrating no-signaling in time between successive measurements, using a variety of input states. Employing a different periodicity, we observe signaling in time. This also requires wave-packet overlap, resulting in quantum interference that we enhance using squeezed input states. The sequential measurements allow us to extract two-time correlators for modular variables, which we use to violate a Leggett-Garg inequality. Signaling in time and Leggett-Garg inequalities serve as efficient quantum witnesses, which we probe here with a mechanical oscillator, a system that has a natural crossover from the quantum to the classical regime.
Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958
NASA DOE POD NDE Capabilities Data Book

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2015-01-01

This data book contains the Directed Design of Experiments for Validating Probability of Detection (POD) Capability of NDE Systems (DOEPOD) analyses of the nondestructive inspection data presented in the NTIAC, Nondestructive Evaluation (NDE) Capabilities Data Book, 3rd ed., NTIAC DB-97-02. DOEPOD is designed as a decision support system to validate inspection system, personnel, and protocol demonstrating 0.90 POD with 95% confidence at critical flaw sizes, a90/95. The test methodology used in DOEPOD is based on the field of statistical sequential analysis founded by Abraham Wald. Sequential analysis is a method of statistical inference whose characteristic feature is that the number of observations required by the procedure is not determined in advance of the experiment. The decision to terminate the experiment depends, at each stage, on the results of the observations previously made. A merit of the sequential method, as applied to testing statistical hypotheses, is that test procedures can be constructed which require, on average, a substantially smaller number of observations than equally reliable test procedures based on a predetermined number of observations.
Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.
Ventromedial prefrontal and anterior cingulate cortex adopt choice and default reference frames during sequential multialternative choice

PubMed Central

Boorman, Erie D; Rushworth, Matthew F; Behrens, Tim E

2013-01-01

Although damage to medial frontal cortex causes profound decision-making impairments, it has been difficult to pinpoint the relative contributions of key anatomical subdivisions. Here we use fMRI to examine the contributions of human ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate cortex (dACC) during sequential choices between multiple alternatives – two key features of choices made in ecological settings. By carefully constructing options whose current value at any given decision was dissociable from their longer-term value, we were able to examine choices in current and long-term frames of reference. We present evidence showing that activity at choice and feedback in vmPFC and dACC was tied to the current choice and the best long-term option, respectively. vmPFC, mid-cingulate, and PCC encoded the relative value between the chosen and next-best option at each sequential decision, whereas dACC encoded the relative value of adapting choices from the option with the highest value in the longer-term. Furthermore, at feedback we identify temporally dissociable effects that predict repetition of the current choice and adaptation away from the long-term best option in vmPFC and dACC, respectively. These functional dissociations at choice and feedback suggest that sequential choices are subject to competing cortical mechanisms. PMID:23392656
The parallel-sequential field subtraction technique for coherent nonlinear ultrasonic imaging

NASA Astrophysics Data System (ADS)

Cheng, Jingwei; Potter, Jack N.; Drinkwater, Bruce W.

2018-06-01

Nonlinear imaging techniques have recently emerged which have the potential to detect cracks at a much earlier stage than was previously possible and have sensitivity to partially closed defects. This study explores a coherent imaging technique based on the subtraction of two modes of focusing: parallel, in which the elements are fired together with a delay law and sequential, in which elements are fired independently. In the parallel focusing a high intensity ultrasonic beam is formed in the specimen at the focal point. However, in sequential focusing only low intensity signals from individual elements enter the sample and the full matrix of transmit-receive signals is recorded and post-processed to form an image. Under linear elastic assumptions, both parallel and sequential images are expected to be identical. Here we measure the difference between these images and use this to characterise the nonlinearity of small closed fatigue cracks. In particular we monitor the change in relative phase and amplitude at the fundamental frequencies for each focal point and use this nonlinear coherent imaging metric to form images of the spatial distribution of nonlinearity. The results suggest the subtracted image can suppress linear features (e.g. back wall or large scatters) effectively when instrumentation noise compensation in applied, thereby allowing damage to be detected at an early stage (c. 15% of fatigue life) and reliably quantified in later fatigue life.
Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine.

PubMed

Qiu, Jian-Ding; Luo, San-Hua; Huang, Jian-Hua; Sun, Xing-Yu; Liang, Ru-Ping

2010-04-01

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. As a result of genome and other sequencing projects, the gap between the number of known apoptosis protein sequences and the number of known apoptosis protein structures is widening rapidly. Because of this extremely unbalanced state, it would be worthwhile to develop a fast and reliable method to identify their subcellular locations so as to gain better insight into their biological functions. In view of this, a new method, in which the support vector machine combines with discrete wavelet transform, has been developed to predict the subcellular location of apoptosis proteins. The results obtained by the jackknife test were quite promising, and indicated that the proposed method can remarkably improve the prediction accuracy of subcellular locations, and might also become a useful high-throughput tool in characterizing other attributes of proteins, such as enzyme class, membrane protein type, and nuclear receptor subfamily according to their sequences.
Subcellular RNA profiling links splicing and nuclear DICER1 to alternative cleavage and polyadenylation

PubMed Central

Neve, Jonathan; Burger, Kaspar; Li, Wencheng; Hoque, Mainul; Patel, Radhika; Tian, Bin; Gullerova, Monika; Furger, Andre

2016-01-01

Alternative cleavage and polyadenylation (APA) plays a crucial role in the regulation of gene expression across eukaryotes. Although APA is extensively studied, its regulation within cellular compartments and its physiological impact remains largely enigmatic. Here, we used a rigorous subcellular fractionation approach to compare APA profiles of cytoplasmic and nuclear RNA fractions from human cell lines. This approach allowed us to extract APA isoforms that are subjected to differential regulation and provided us with a platform to interrogate the molecular regulatory pathways that shape APA profiles in different subcellular locations. Here, we show that APA isoforms with shorter 3′ UTRs tend to be overrepresented in the cytoplasm and appear to be cell-type–specific events. Nuclear retention of longer APA isoforms occurs and is partly a result of incomplete splicing contributing to the observed cytoplasmic bias of transcripts with shorter 3′ UTRs. We demonstrate that the endoribonuclease III, DICER1, contributes to the establishment of subcellular APA profiles not only by expected cytoplasmic miRNA-mediated destabilization of APA mRNA isoforms, but also by affecting polyadenylation site choice. PMID:26546131

The sub-cellular fate of mercury in the liver of wild mullets (Liza aurata)--Contribution to the understanding of metal-induced cellular toxicity.

PubMed

Araújo, Olinda; Pereira, Patrícia; Cesário, Rute; Pacheco, Mário; Raimundo, Joana

2015-06-15

Mercury is a recognized harmful pollutant in aquatic systems but still little is known about its sub-cellular partitioning in wild fish. Mercury concentrations in liver homogenate (whole organ load) and in six sub-cellular compartments were determined in wild Liza aurata from two areas - contaminated (LAR) and reference. Water and sediment contamination was also assessed. Fish from LAR displayed higher total mercury (tHg) organ load as well as in sub-cellular compartments than those from the reference area, reflecting environmental differences. However, spatial differences in percentage of tHg were only observed for mitochondria (Mit) and lysosomes plus microsomes (Lys+Mic). At LAR, Lys+Mic exhibited higher levels of tHg than the other fractions. Interestingly, tHg in Mit, granules (Gran) and heat-denaturable proteins was linearly correlated with the whole organ. Low tHg concentrations in heat stable proteins and Gran suggests that accumulated levels might be below the physiological threshold to activate those detoxification fractions. Copyright © 2015 Elsevier Ltd. All rights reserved.
Phosphorylation of Tat-interactive protein 60 kDa by protein kinase C epsilon is important for its subcellular localisation.

PubMed

Sapountzi, Vasileia; Logan, Ian R; Nelson, Glyn; Cook, Susan; Robson, Craig N

2008-01-01

Tat-interactive protein 60 kDa is a nuclear acetyltransferase that both coactivates and corepresses transcription factors and has a definitive function in the DNA damage response. Here, we provide evidence that Tat-interactive protein 60 kDa is phosphorylated by protein kinase C epsilon. In vitro, protein kinase C epsilon phosphorylates Tat-interactive protein 60 kDa on at least two sites within the acetyltransferase domain. In whole cells, activation of protein kinase C increases the levels of phosphorylated Tat-interactive protein 60 kDa and the interaction of Tat-interactive protein 60 kDa with protein kinase C epsilon. A phosphomimetic mutant Tat-interactive protein 60 kDa has distinct subcellular localisation compared to the wild-type protein in whole cells. Taken together, these findings suggest that the protein kinase C epsilon phosphorylation sites on Tat-interactive protein 60 kDa are important for its subcellular localisation. Regulation of the subcellular localisation of Tat-interactive protein 60 kDa via phosphorylation provides a novel means of controlling Tat-interactive protein 60 kDa function.
Prediction of protein subcellular localization by weighted gene ontology terms.

PubMed

Chi, Sang-Mun

2010-08-27

We develop a new weighting approach of gene ontology (GO) terms for predicting protein subcellular localization. The weights of individual GO terms, corresponding to their contribution to the prediction algorithm, are determined by the term-weighting methods used in text categorization. We evaluate several term-weighting methods, which are based on inverse document frequency, information gain, gain ratio, odds ratio, and chi-square and its variants. Additionally, we propose a new term-weighting method based on the logarithmic transformation of chi-square. The proposed term-weighting method performs better than other term-weighting methods, and also outperforms state-of-the-art subcellular prediction methods. Our proposed method achieves 98.1%, 99.3%, 98.1%, 98.1%, and 95.9% overall accuracies for the animal BaCelLo independent dataset (IDS), fungal BaCelLo IDS, animal Höglund IDS, fungal Höglund IDS, and PLOC dataset, respectively. Furthermore, the close correlation between high-weighted GO terms and subcellular localizations suggests that our proposed method appropriately weights GO terms according to their relevance to the localizations. Copyright 2010 Elsevier Inc. All rights reserved.
Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh.

PubMed

Rizk, Aurélien; Paul, Grégory; Incardona, Pietro; Bugarski, Milica; Mansouri, Maysam; Niemann, Axel; Ziegler, Urs; Berger, Philipp; Sbalzarini, Ivo F

2014-03-01

Detection and quantification of fluorescently labeled molecules in subcellular compartments is a key step in the analysis of many cell biological processes. Pixel-wise colocalization analyses, however, are not always suitable, because they do not provide object-specific information, and they are vulnerable to noise and background fluorescence. Here we present a versatile protocol for a method named 'Squassh' (segmentation and quantification of subcellular shapes), which is used for detecting, delineating and quantifying subcellular structures in fluorescence microscopy images. The workflow is implemented in freely available, user-friendly software. It works on both 2D and 3D images, accounts for the microscope optics and for uneven image background, computes cell masks and provides subpixel accuracy. The Squassh software enables both colocalization and shape analyses. The protocol can be applied in batch, on desktop computers or computer clusters, and it usually requires <1 min and <5 min for 2D and 3D images, respectively. Basic computer-user skills and some experience with fluorescence microscopy are recommended to successfully use the protocol.
Smartphone-based imaging of the corneal endothelium at sub-cellular resolution

NASA Astrophysics Data System (ADS)

Toslak, Devrim; Thapa, Damber; Erol, Muhammet Kazim; Chen, Yanjun; Yao, Xincheng

2017-07-01

This aim of this study was to test the feasibility of smartphone-based specular microscopy of the corneal endothelium at a sub-cellular resolution. Quantitative examination of endothelial cells is essential for evaluating corneal disease such as determining a diagnosis, monitoring progression and assessing treatment. Smartphone-based technology promises a new opportunity to develop affordable devices to foster quantitative examination of endothelial cells in rural and underserved areas. In our study, we incorporated an iPhone 6 and a slit lamp to demonstrate the feasibility of smartphone-based microscopy of the corneal endothelium at a sub-cellular resolution. The sub-cellular resolution images allowed quantitative calculation of the endothelial cell density. Comparative measurements revealed a normal endothelial cell density of 2978 cells/mm2 in the healthy cornea, and a significantly reduced cell density of 1466 cells/mm2 in the diseased cornea with Fuchs' dystrophy. Our ultimate goal is to develop a smartphone-based telemedicine device for low-cost examination of the corneal endothelium, which can benefit patients in rural areas and underdeveloped countries to reduce health care disparities.
Systematic Analysis of Arabidopsis Organelles and a Protein Localization Database for Facilitating Fluorescent Tagging of Full-Length Arabidopsis Proteins1[W

PubMed Central

Li, Shijun; Ehrhardt, David W.; Rhee, Seung Y.

2006-01-01

Cells are organized into a complex network of subcellular compartments that are specialized for various biological functions. Subcellular location is an important attribute of protein function. To facilitate systematic elucidation of protein subcellular location, we analyzed experimentally verified protein localization data of 1,300 Arabidopsis (Arabidopsis thaliana) proteins. The 1,300 experimentally verified proteins are distributed among 40 different compartments, with most of the proteins localized to four compartments: mitochondria (36%), nucleus (28%), plastid (17%), and cytosol (13.3%). About 19% of the proteins are found in multiple compartments, in which a high proportion (36.4%) is localized to both cytosol and nucleus. Characterization of the overrepresented Gene Ontology molecular functions and biological processes suggests that the Golgi apparatus and peroxisome may play more diverse functions but are involved in more specialized processes than other compartments. To support systematic empirical determination of protein subcellular localization using a technology called fluorescent tagging of full-length proteins, we developed a database and Web application to provide preselected green fluorescent protein insertion position and primer sequences for all Arabidopsis proteins to study their subcellular localization and to store experimentally verified protein localization images, videos, and their annotations of proteins generated using the fluorescent tagging of full-length proteins technology. The database can be searched, browsed, and downloaded using a Web browser at http://aztec.stanford.edu/gfp/. The software can also be downloaded from the same Web site for local installation. PMID:16617091
Capillary electrophoretic analysis reveals subcellular binding between individual mitochondria and cytoskeleton

PubMed Central

Kostal, Vratislav; Arriaga, Edgar A.

2011-01-01

Interactions between the cytoskeleton and mitochondria are essential for normal cellular function. An assessment of such interactions is commonly based on bulk analysis of mitochondrial and cytoskeletal markers present in a given sample, which assumes complete binding between these two organelle types. Such measurements are biased because they rarely account for non-bound ‘free’ subcellular species. Here we report on the use of capillary electrophoresis with dual laser induced fluorescence detection (CE-LIF) to identify, classify, count and quantify properties of individual binding events of mitochondria and cytoskeleton. Mitochondria were fluorescently labeled with DsRed2 while F-actin, a major cytoskeletal component, was fluorescently labeled with Alexa488-phalloidin. In a typical subcellular fraction of L6 myoblasts, 79% of mitochondrial events did not have detectable levels of F-actin, while the rest had on average ~2 zeptomole F-actin, which theoretically represents a ~ 2.5-μm long network of actin filaments per event. Trypsin treatment of L6 subcellular fractions prior to analysis decreased the fraction of mitochondrial events with detectable levels of F-actin, which is expected from digestion of cytoskeletal proteins on the surface of mitochondria. The electrophoretic mobility distributions of the individual events were also used to further distinguish between cytoskeleton-bound from cytoskeleton-free mitochondrial events. The CE-LIF approach described here could be further developed to explore cytoskeleton interactions with other subcellular structures, the effects of cytoskeleton destabilizing drugs, and the progression of viral infections. PMID:21309532
Prion subcellular fractionation reveals infectivity spectrum, with a high titre-low PrPres level disparity

PubMed Central

2012-01-01

Background Prion disease transmission and pathogenesis are linked to misfolded, typically protease resistant (PrPres) conformers of the normal cellular prion protein (PrPC), with the former posited to be the principal constituent of the infectious 'prion'. Unexplained discrepancies observed between detectable PrPres and infectivity levels exemplify the complexity in deciphering the exact biophysical nature of prions and those host cell factors, if any, which contribute to transmission efficiency. In order to improve our understanding of these important issues, this study utilized a bioassay validated cell culture model of prion infection to investigate discordance between PrPres levels and infectivity titres at a subcellular resolution. Findings Subcellular fractions enriched in lipid rafts or endoplasmic reticulum/mitochondrial marker proteins were equally highly efficient at prion transmission, despite lipid raft fractions containing up to eight times the levels of detectable PrPres. Brain homogenate infectivity was not differentially enhanced by subcellular fraction-specific co-factors, and proteinase K pre-treatment of selected fractions modestly, but equally reduced infectivity. Only lipid raft associated infectivity was enhanced by sonication. Conclusions This study authenticates a subcellular disparity in PrPres and infectivity levels, and eliminates simultaneous divergence of prion strains as the explanation for this phenomenon. On balance, the results align best with the concept that transmission efficiency is influenced more by intrinsic characteristics of the infectious prion, rather than cellular microenvironment conditions or absolute PrPres levels. PMID:22534096
Determining the sub-cellular localization of proteins within Caenorhabditis elegans body wall muscle.

PubMed

Meissner, Barbara; Rogalski, Teresa; Viveiros, Ryan; Warner, Adam; Plastino, Lorena; Lorch, Adam; Granger, Laure; Segalat, Laurent; Moerman, Donald G

2011-01-01

Determining the sub-cellular localization of a protein within a cell is often an essential step towards understanding its function. In Caenorhabditis elegans, the relatively large size of the body wall muscle cells and the exquisite organization of their sarcomeres offer an opportunity to identify the precise position of proteins within cell substructures. Our goal in this study is to generate a comprehensive "localizome" for C. elegans body wall muscle by GFP-tagging proteins expressed in muscle and determining their location within the cell. For this project, we focused on proteins that we know are expressed in muscle and are orthologs or at least homologs of human proteins. To date we have analyzed the expression of about 227 GFP-tagged proteins that show localized expression in the body wall muscle of this nematode (e.g. dense bodies, M-lines, myofilaments, mitochondria, cell membrane, nucleus or nucleolus). For most proteins analyzed in this study no prior data on sub-cellular localization was available. In addition to discrete sub-cellular localization we observe overlapping patterns of localization including the presence of a protein in the dense body and the nucleus, or the dense body and the M-lines. In total we discern more than 14 sub-cellular localization patterns within nematode body wall muscle. The localization of this large set of proteins within a muscle cell will serve as an invaluable resource in our investigation of muscle sarcomere assembly and function.
Subcellular targeting and interactions among the Potato virus X TGB proteins.

PubMed

Samuels, Timmy D; Ju, Ho-Jong; Ye, Chang-Ming; Motes, Christy M; Blancaflor, Elison B; Verchot-Lubicz, Jeanmarie

2007-10-25

Potato virus X (PVX) encodes three proteins named TGBp1, TGBp2, and TGBp3 which are required for virus cell-to-cell movement. To determine whether PVX TGB proteins interact during virus cell-cell movement, GFP was fused to each TGB coding sequence within the viral genome. Confocal microscopy was used to study subcellular accumulation of each protein in virus-infected plants and protoplasts. GFP:TGBp2 and TGBp3:GFP were both seen in the ER, ER-associated granular vesicles, and perinuclear X-bodies suggesting that these proteins interact in the same subdomains of the endomembrane network. When plasmids expressing CFP:TGBp2 and TGBp3:GFP were co-delivered to tobacco leaf epidermal cells, the fluorescent signals overlapped in ER-associated granular vesicles indicating that these proteins colocalize in this subcellular compartment. GFP:TGBp1 was seen in the nucleus, cytoplasm, rod-like inclusion bodies, and in punctate sites embedded in the cell wall. The puncta were reminiscent of previous reports showing viral proteins in plasmodesmata. Experiments using CFP:TGBp1 and YFP:TGBp2 or TGBp3:GFP showed CFP:TGBp1 remained in the cytoplasm surrounding the endomembrane network. There was no evidence that the granular vesicles contained TGBp1. Yeast two hybrid experiments showed TGBp1 self associates but failed to detect interactions between TGBp1 and TGBp2 or TGBp3. These experiments indicate that the PVX TGB proteins have complex subcellular accumulation patterns and likely cooperate across subcellular compartments to promote virus infection.
PhosphoregDB: The tissue and sub-cellular distribution of mammalian protein kinases and phosphatases

PubMed Central

Forrest, Alistair RR; Taylor, Darrin F; Fink, J Lynn; Gongora, M Milena; Flegg, Cameron; Teasdale, Rohan D; Suzuki, Harukazu; Kanamori, Mutsumi; Kai, Chikatoshi; Hayashizaki, Yoshihide; Grimmond, Sean M

2006-01-01

Background Protein kinases and protein phosphatases are the fundamental components of phosphorylation dependent protein regulatory systems. We have created a database for the protein kinase-like and phosphatase-like loci of mouse that integrates protein sequence, interaction, classification and pathway information with the results of a systematic screen of their sub-cellular localization and tissue specific expression data mined from the GNF tissue atlas of mouse. Results The database lets users query where a specific kinase or phosphatase is expressed at both the tissue and sub-cellular levels. Similarly the interface allows the user to query by tissue, pathway or sub-cellular localization, to reveal which components are co-expressed or co-localized. A review of their expression reveals 30% of these components are detected in all tissues tested while 70% show some level of tissue restriction. Hierarchical clustering of the expression data reveals that expression of these genes can be used to separate the samples into tissues of related lineage, including 3 larger clusters of nervous tissue, developing embryo and cells of the immune system. By overlaying the expression, sub-cellular localization and classification data we examine correlations between class, specificity and tissue restriction and show that tyrosine kinases are more generally expressed in fewer tissues than serine/threonine kinases. Conclusion Together these data demonstrate that cell type specific systems exist to regulate protein phosphorylation and that for accurate modelling and for determination of enzyme substrate relationships the co-location of components needs to be considered. PMID:16504016
Rational Design of Semiconductor Nanostructures for Functional Subcellular Interfaces.

PubMed

Parameswaran, Ramya; Tian, Bozhi

2018-05-15

One of the fundamental questions guiding research in the biological sciences is how cellular systems process complex physical and environmental cues and communicate with each other across multiple length scales. Importantly, aberrant signal processing in these systems can lead to diseases that can have devastating impacts on human lives. Biophysical studies in the past several decades have demonstrated that cells can respond to not only biochemical cues but also mechanical and electrical ones. Thus, the development of new materials that can both sense and modulate all of these pathways is necessary. Semiconducting nanostructures are an emerging class of discovery platforms and tools that can push the limits of our ability to modulate and sense biological behaviors for both fundamental research and clinical applications. These materials are of particular interest for interfacing with cellular systems due to their matched dimension with subcellular components (e.g., cytoskeletal filaments), and easily tunable properties in the electrical, optical and mechanical regimes. Rational design via traditional or new approaches, such as nanocasting and mesoscale chemical lithography, can allow us to control micro- and nanoscale features in nanowires to achieve new biointerfaces. Both processes endogenous to the target cell and properties of the material surface dictate the character of these interfaces. In this Account, we focus on (1) approaches for the rational design of semiconducting nanowires that exhibit unique structures for biointerfaces, (2) recent fundamental discoveries that yield robust biointerfaces at the subcellular level, (3) intracellular electrical and mechanical sensing, and (4) modulation of cellular behaviors through material topography and remote physical stimuli. In the first section, we discuss new approaches for the synthetic control of micro- and nanoscale features of these materials. In the second section, we focus on achieving biointerfaces with these rationally designed materials either intra- or extracellularly. We last delve into the use of these materials in sensing mechanical forces and electrical signals in various cellular systems as well as in instructing cellular behaviors. Future research in this area may shift the paradigm in fundamental biophysical research and biomedical applications through (1) the design and synthesis of new semiconductor-based materials and devices that interact specifically with targeted cells, (2) the clarification of many developmental, physiological, and anatomical aspects of cellular communications, (3) an understanding of how signaling between cells regulates synaptic development (e.g., information like this would offer new insight into how the nervous system works and provide new targets for the treatment of neurological diseases), (4) and the creation of new cellular materials that have the potential to open up completely new areas of application, such as in hybrid information processing systems.
Correlation of N-myc downstream-regulated gene 1 subcellular localization and lymph node metastases of colorectal neoplasms

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

Song, Yan; Lv, Liyang; Du, Juan

2013-09-20

Highlights: •We clarified NDRG1 subcellular location in colorectal cancer. •We found the changes of NDRG1 distribution during colorectal cancer progression. •We clarified the correlation between NDRG1 distribution and lymph node metastasis. •It is possible that NDRG1 subcellular localization may determine its function. •Maybe NDRG1 is valuable early diagnostic markers for metastasis. -- Abstract: In colorectal neoplasms, N-myc downstream-regulated gene 1 (NDRG1) is a primarily cytoplasmic protein, but it is also expressed on the cell membrane and in the nucleus. NDRG1 is involved in various stages of tumor development in colorectal cancer, and it is possible that the different subcellular localizationsmore » may determine the function of NDRG1 protein. Here, we attempt to clarify the characteristics of NDRG1 protein subcellular localization during the progression of colorectal cancer. We examined NDRG1 expression in 49 colorectal cancer patients in cancerous, non-cancerous, and corresponding lymph node tissues. Cytoplasmic and membrane NDRG1 expression was higher in the lymph nodes with metastases than in those without metastases (P < 0.01). Nuclear NDRG1 expression in colorectal neoplasms was significantly higher than in the normal colorectal mucosa, and yet the normal colorectal mucosa showed no nuclear expression. Furthermore, our results showed higher cytoplasmic NDRG1 expression was better for differentiation, and higher membrane NDRG1 expression resulted in a greater possibility of lymph node metastasis. These data indicate that a certain relationship between the cytoplasmic and membrane expression of NDRG1 in lymph nodes exists with lymph node metastasis. NDRG1 expression may translocate from the membrane of the colorectal cancer cells to the nucleus, where it is involved in lymph node metastasis. Combination analysis of NDRG1 subcellular expression and clinical variables will help predict the incidence of lymph node metastasis.« less
Sequential Modelling of Building Rooftops by Integrating Airborne LIDAR Data and Optical Imagery: Preliminary Results

NASA Astrophysics Data System (ADS)

Sohn, G.; Jung, J.; Jwa, Y.; Armenakis, C.

2013-05-01

This paper presents a sequential rooftop modelling method to refine initial rooftop models derived from airborne LiDAR data by integrating it with linear cues retrieved from single imagery. A cue integration between two datasets is facilitated by creating new topological features connecting between the initial model and image lines, with which new model hypotheses (variances to the initial model) are produced. We adopt Minimum Description Length (MDL) principle for competing the model candidates and selecting the optimal model by considering the balanced trade-off between the model closeness and the model complexity. Our preliminary results, combined with the Vaihingen data provided by ISPRS WGIII/4 demonstrate the image-driven modelling cues can compensate the limitations posed by LiDAR data in rooftop modelling.
Quantum Dot Platform for Single-Cell Molecular Profiling

NASA Astrophysics Data System (ADS)

Zrazhevskiy, Pavel S.

In-depth understanding of the nature of cell physiology and ability to diagnose and control the progression of pathological processes heavily rely on untangling the complexity of intracellular molecular mechanisms and pathways. Therefore, comprehensive molecular profiling of individual cells within the context of their natural tissue or cell culture microenvironment is essential. In principle, this goal can be achieved by tagging each molecular target with a unique reporter probe and detecting its localization with high sensitivity at sub-cellular resolution, primarily via microscopy-based imaging. Yet, neither widely used conventional methods nor more advanced nanoparticle-based techniques have been able to address this task up to date. High multiplexing potential of fluorescent probes is heavily restrained by the inability to uniquely match probes with corresponding molecular targets. This issue is especially relevant for quantum dot probes---while simultaneous spectral imaging of up to 10 different probes is possible, only few can be used concurrently for staining with existing methods. To fully utilize multiplexing potential of quantum dots, it is necessary to design a new staining platform featuring unique assignment of each target to a corresponding quantum dot probe. This dissertation presents two complementary versatile approaches towards achieving comprehensive single-cell molecular profiling and describes engineering of quantum dot probes specifically tailored for each staining method. Analysis of expanded molecular profiles is achieved through augmenting parallel multiplexing capacity with performing several staining cycles on the same specimen in sequential manner. In contrast to other methods utilizing quantum dots or other nanoparticles, which often involve sophisticated probe synthesis, the platform technology presented here takes advantage of simple covalent bioconjugation and non-covalent self-assembly mechanisms for straightforward probe preparation and specimen labeling, requiring no advanced technical skills and being directly applicable for a wide range of molecular profiling studies. Utilization of quantum dot platform for single-cell molecular profiling promises to greatly benefit both biomedical research and clinical diagnostics by providing a tool for addressing phenotypic heterogeneity within large cell populations, opening access to studying low-abundance events often masked or completely erased by batch processing, and elucidating biomarker signatures of diseases critical for accurate diagnostics and targeted therapy.
Aircrew Training Devices: Fidelity Features.

DTIC Science & Technology

1981-01-01

providing artificial cues for glideslope and lineup . He found that an adaptive strategy for using augmenting cues, where the presence or absence of the...with continuously available sources of augmented information for lineup and glideslope in the simulatot, they performed more poorly on test trials...flown: fighting wing, barrel roll attack, sequential attack, free engagement, aileron roll and loop. Results indicated higher ratings of realism for
Precision of working memory for visual motion sequences and transparent motion surfaces

PubMed Central

Zokaei, Nahid; Gorgoraptis, Nikos; Bahrami, Bahador; Bays, Paul M; Husain, Masud

2012-01-01

Recent studies investigating working memory for location, colour and orientation support a dynamic resource model. We examined whether this might also apply to motion, using random dot kinematograms (RDKs) presented sequentially or simultaneously. Mean precision for motion direction declined as sequence length increased, with precision being lower for earlier RDKs. Two alternative models of working memory were compared specifically to distinguish between the contributions of different sources of error that corrupt memory (Zhang & Luck (2008) vs. Bays et al (2009)). The latter provided a significantly better fit for the data, revealing that decrease in memory precision for earlier items is explained by an increase in interference from other items in a sequence, rather than random guessing or a temporal decay of information. Misbinding feature attributes is an important source of error in working memory. Precision of memory for motion direction decreased when two RDKs were presented simultaneously as transparent surfaces, compared to sequential RDKs. However, precision was enhanced when one motion surface was prioritized, demonstrating that selective attention can improve recall precision. These results are consistent with a resource model that can be used as a general conceptual framework for understanding working memory across a range of visual features. PMID:22135378
Gene expression profiling gut microbiota in different races of humans

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong

2016-03-01

The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome.
Gene expression profiling gut microbiota in different races of humans

PubMed Central

Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong

2016-01-01

The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome. PMID:26975620
Coordination and interpretation of vocal and visible resources: 'trail-off' conjunctions.

PubMed

Walker, Gareth

2012-03-01

The empirical focus of this paper is a conversational turn-taking phenomenon in which conjunctions produced immediately after a point of possible syntactic and pragmatic completion are treated by co-participants as points of possible completion and transition relevance. The data for this study are audio-video recordings of 5 unscripted face-to-face interactions involving native speakers of US English, yielding 28 'trail-off' conjunctions. Detailed sequential analysis of talk is combined with analysis of visible features (including gaze, posture, gesture and involvement with material objects) and technical phonetic analysis. A range of phonetic and visible features are shown to regularly co-occur in the production of 'trail-off' conjunctions. These features distinguish them from other conjunctions followed by the cessation of talk.

The human brain processes repeated auditory feature conjunctions of low sequential probability.

PubMed

Ruusuvirta, Timo; Huotilainen, Minna

2004-01-23

The human brain is known to preattentively trace repeated sounds as holistic entities. It is not clear, however, whether the same holds true if these sounds are rare among other repeated sounds. Adult humans passively listened to a repeated tone with frequent (standard) and rare (deviant) conjunctions of its three features. Six equiprobable variants per conjunction type were assigned from a space built from these features so that the standard variants (P=0.15 each) were not inseparably traceable by means of their linear alignment in this space. Differential scalp-recorded event-related potentials to deviants indicate that the standard variants were traced as repeated wholes despite their preperceptual distinctiveness and resulting rarity among one another.
SUMO proteases as potential targets for cancer therapy.

PubMed

Bialik, Piotr; Woźniak, Katarzyna

2017-12-08

Sumoylation is one of the post-translational modifications of proteins, responsible for the regulation of many cellular processes, such as DNA replication and repair, transcription, signal transduction and nuclear transport. During sumoylation, SUMO proteins are covalently attached to the ε-amino group of lysine in target proteins via an enzymatic cascade that requires the sequential action of E1, E2 and E3 enzymes. An important aspect of sumoylation is its reversibility, which involves SUMO-specific proteases called SENPs. SENPs (sentrin/SUMO-specific proteases) catalyze the deconjugation of SUMO proteins using their isopeptidase activity. These enzymes participate through hydrolase activity in the reaction of SUMO protein maturation, which involves the removal of a short fragment on the C-terminus of SUMO inactive form and exposure two glycine residues. SENPs are important for maintaining the balance between sumoylated and desumoylated proteins required for normal cellular physiology. Six SENP isoforms (SENP1, SENP2, SENP3, SENP5, SENP6 and SENP7) have been identified in mammals. These SENPs can be divided into three subfamilies based on their sequence homology, substrate specificity and subcellular localization. Results of studies indicate the role of SUMO proteases in the development of human diseases including cancer, suggesting that these proteins may be attractive targets for new drugs.
Programming chemistry in DNA-addressable bioreactors

PubMed Central

Fellermann, Harold; Cardelli, Luca

2014-01-01

We present a formal calculus, termed the chemtainer calculus, able to capture the complexity of compartmentalized reaction systems such as populations of possibly nested vesicular compartments. Compartments contain molecular cargo as well as surface markers in the form of DNA single strands. These markers serve as compartment addresses and allow for their targeted transport and fusion, thereby enabling reactions of previously separated chemicals. The overall system organization allows for the set-up of programmable chemistry in microfluidic or other automated environments. We introduce a simple sequential programming language whose instructions are motivated by state-of-the-art microfluidic technology. Our approach integrates electronic control, chemical computing and material production in a unified formal framework that is able to mimic the integrated computational and constructive capabilities of the subcellular matrix. We provide a non-deterministic semantics of our programming language that enables us to analytically derive the computational and constructive power of our machinery. This semantics is used to derive the sets of all constructable chemicals and supermolecular structures that emerge from different underlying instruction sets. Because our proofs are constructive, they can be used to automatically infer control programs for the construction of target structures from a limited set of resource molecules. Finally, we present an example of our framework from the area of oligosaccharide synthesis. PMID:25121647
The Monitoring and Affinity Purification of Proteins Using Dual Tags with Tetracysteine Motifs

NASA Astrophysics Data System (ADS)

Giannone, Richard J.; Liu, Yie; Wang, Yisong

Identification and characterization of protein-protein interaction networks is essential for the elucidation of biochemical mechanisms and cellular function. Affinity purification in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as a very powerful tactic for the identification of specific protein-protein interactions. In this chapter, we describe a comprehensive methodology that uses our recently developed dual-tag affinity purification system for the enrichment and identification of mammalian protein complexes. The protocol covers a series of separate but sequentially related techniques focused on the facile monitoring and purification of a dual-tagged protein of interest and its interacting partners via a system built with tetracysteine motifs and various combinations of affinity tags. Using human telomeric repeat binding factor 2 (TRF2) as an example, we demonstrate the power of the system in terms of bait protein recovery after dual-tag affinity purification, detection of bait protein subcellular localization and expression, and successful identification of known and potentially novel TRF2 interacting proteins. Although the protocol described here has been optimized for the identification and characterization of TRF2-associated proteins, it is, in principle, applicable to the study of any other mammalian protein complexes that may be of interest to the research community.
Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.
Internalization of aggregated photosensitizers by tumor cells: subcellular time-resolved fluorescence spectroscopy on derivatives of pyropheophorbide-a ethers and chlorin e6 under femtosecond one- and two-photon excitations.

PubMed

Kelbauskas, L; Dietel, W

2002-12-01

Amphiphilic sensitizers self-associate in aqueous environments and form aggregated species that exhibit no or only negligible photodynamic activity. However, amphiphilic photosensitizers number among the most potent agents of photodynamic therapy. The processes by which these sensitizers are internalized into tumor cells have yet to be fully elucidated and thus remain the subject of debate. In this study the uptake of photosensitizer aggregates into tumor cells was examined directly using subcellular time-resolved fluorescence spectroscopy with a high temporal resolution (20-30 ps) and high sensitivity (time-correlated single-photon counting). The investigations were performed on selected sensitizers that exhibit short fluorescence decay times (< 50 ps) in aggregated form. Derivatives of pyropheophorbide-a ether and chlorin e6 with varying lipophilicity were used for the study. The characteristic fluorescence decay times and spectroscopic features of the sensitizer aggregates measured in aqueous solution also could be observed in A431 human endothelial carcinoma cells administered with these photosensitizers. This shows that tumor cells can internalize sensitizers in aggregated form. Uptake of aggregates and their monomerization inside cells were demonstrated directly for the first time by means of fluorescence lifetime imaging with a high temporal resolution. Internalization of the aggregates seems to be endocytosis mediated. The degree of their monomerization in tumor cells is strongly influenced by the lipophilicity of the compounds.
Identification of a New Modulator of the Intercalated Disc in a Zebrafish Model of Arrhythmogenic Cardiomyopathy

PubMed Central

Asimaki, Angeliki; Kapoor, Sudhir; Plovie, Eva; Arndt, Anne Karin; Adams, Edward; Liu, ZhenZhen; James, Cynthia A.; Judge, Daniel P.; Calkins, Hugh; Churko, Jared; Wu, Joseph C.; MacRae, Calum A.; Kléber, André G.; Saffitz, Jeffrey E.

2015-01-01

Arrhythmogenic cardiomyopathy (ACM) is characterized by frequent cardiac arrhythmias. To elucidate the underlying mechanisms and discover potential chemical modifiers, we created a zebrafish model of ACM with cardiac myocyte–specific expression of the human 2057del2 mutation in the gene encoding plakoglobin. A high-throughput screen identified SB216763 as a suppressor of the disease phenotype. Early SB216763 therapy prevented heart failure and reduced mortality in the fish model. Zebrafish ventricular myocytes that expressed 2057del2 plakoglobin exhibited 70 to 80% reductions in INa and IK1 current densities, which were normalized by SB216763. Neonatal rat ventricular myocytes that expressed 2057del2 plakoglobin recapitulated pathobiological features seen in patients with ACM, all of which were reversed or prevented by SB216763. The reverse remodeling observed with SB216763 involved marked subcellular redistribution of plakoglobin, connexin 43, and Nav1.5, but without changes in their total cellular content, implicating a defect in protein trafficking to intercalated discs. In further support of this mechanism, we observed SB216763-reversible, abnormal subcellular distribution of SAP97 (a protein known to mediate forward trafficking of Nav1.5 and Kir2.1) in rat cardiac myocytes expressing 2057del2 plakoglobin and in cardiac myocytes derived from induced pluripotent stem cells from two ACM probands with plakophilin-2 mutations. These observations pinpoint aberrant trafficking of intercalated disc proteins as a central mechanism in ACM myocyte injury and electrical abnormalities. PMID:24920660
The phospholipase PNPLA7 functions as a lysophosphatidylcholine hydrolase and interacts with lipid droplets through its catalytic domain.

PubMed

Heier, Christoph; Kien, Benedikt; Huang, Feifei; Eichmann, Thomas O; Xie, Hao; Zechner, Rudolf; Chang, Ping-An

2017-11-17

Mammalian patatin-like phospholipase domain-containing proteins (PNPLAs) are lipid-metabolizing enzymes with essential roles in energy metabolism, skin barrier development, and brain function. A detailed annotation of enzymatic activities and structure-function relationships remains an important prerequisite to understand PNPLA functions in (patho-)physiology, for example, in disorders such as neutral lipid storage disease, non-alcoholic fatty liver disease, and neurodegenerative syndromes. In this study, we characterized the structural features controlling the subcellular localization and enzymatic activity of PNPLA7, a poorly annotated phospholipase linked to insulin signaling and energy metabolism. We show that PNPLA7 is an endoplasmic reticulum (ER) transmembrane protein that specifically promotes hydrolysis of lysophosphatidylcholine in mammalian cells. We found that transmembrane and regulatory domains in the PNPLA7 N-terminal region cooperate to regulate ER targeting but are dispensable for substrate hydrolysis. Enzymatic activity is instead mediated by the C-terminal domain, which maintains full catalytic competence even in the absence of N-terminal regions. Upon elevated fatty acid flux, the catalytic domain targets cellular lipid droplets and promotes interactions of PNPLA7 with these organelles in response to increased cAMP levels. We conclude that PNPLA7 acts as an ER-anchored lysophosphatidylcholine hydrolase that is composed of specific functional domains mediating catalytic activity, subcellular positioning, and interactions with cellular organelles. Our study provides critical structural insights into an evolutionarily conserved class of phospholipid-metabolizing enzymes. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
Approaches for Studying the Subcellular Localization, Interactions, and Regulation of Histone Deacetylase 5 (HDAC5)

PubMed Central

Guise, Amanda J.; Cristea, Ileana M.

2017-01-01

As a member of the class IIa family of histone deacetylases, the histone deacetylase 5 (HDAC5) is known to undergo nuclear–cytoplasmic shuttling and to be a critical transcriptional regulator. Its misregulation has been linked to prominent human diseases, including cardiac diseases and tumorigenesis. In this chapter, we describe several experimental methods that have proven effective for studying the functions and regulatory features of HDAC5. We present methods for assessing the subcellular localization, protein interactions, posttranslational modifications (PTMs), and activity of HDAC5 from the standpoint of investigating either the endogenous protein or tagged protein forms in human cells. Specifically, given that at the heart of HDAC5 regulation lie its dynamic localization, interactions, and PTMs, we present methods for assessing HDAC5 localization in fixed and live cells, for isolating HDAC5-containing protein complexes to identify its interactions and modifications, and for determining how these PTMs map to predicted HDAC5 structural motifs. Lastly, we provide examples of approaches for studying HDAC5 functions with a focus on its regulation during cell-cycle progression. These methods can readily be adapted for the study of other HDACs or non-HDAC-proteins of interest. Individually, these techniques capture temporal and spatial snapshots of HDAC5 functions; yet together, these approaches provide powerful tools for investigating both the regulation and regulatory roles of HDAC5 in different cell contexts relevant to health and disease. PMID:27246208
Domain-general neural correlates of dependency formation: Using complex tones to simulate language.

PubMed

Brilmayer, Ingmar; Sassenhagen, Jona; Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias

2017-08-01

There is an ongoing debate whether the P600 event-related potential component following syntactic anomalies reflects syntactic processes per se, or if it is an instance of the P300, a domain-general ERP component associated with attention and cognitive reorientation. A direct comparison of both components is challenging because of the huge discrepancy in experimental designs and stimulus choice between language and 'classic' P300 experiments. In the present study, we develop a new approach to mimic the interplay of sequential position as well as categorical and relational information in natural language syntax (word category and agreement) in a non-linguistic target detection paradigm using musical instruments. Participants were instructed to (covertly) detect target tones which were defined by instrument change and pitch rise between subsequent tones at the last two positions of four-tone sequences. We analysed the EEG using event-related averaging and time-frequency decomposition. Our results show striking similarities to results obtained from linguistic experiments. We found a P300 that showed sensitivity to sequential position and a late positivity sensitive to stimulus type and position. A time-frequency decomposition revealed significant effects of sequential position on the theta band and a significant influence of stimulus type on the delta band. Our results suggest that the detection of non-linguistic targets defined via complex feature conjunctions in the present study and the detection of syntactic anomalies share the same underlying processes: attentional shift and memory based matching processes that act upon multi-feature conjunctions. We discuss the results as supporting domain-general accounts of the P600 during natural language comprehension. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bioaccumulation of Zn and Ag Nanoparticles in the Earthworms (Eisenia fetida)

NASA Astrophysics Data System (ADS)

Ha, Lee Seung; Sung-Dae, Kim; Yi, Yang Song; Byeong-Gweon, Lee

2014-05-01

Many studies are carried out to evaluate environmental effects of engineered nanoparticles (ENPs). Most of the previous studies primarily focused on the effects of nanoparticles into the aquatic environment and human. Model studies predict that ENPs released into environment would transferred primarily to the soil of the terrestrial environment. Despite this prediction, biogeochemical behavior of ENPs in soil environment as well as bioavailability of ENPs to soil-dwelling organisms such as earthworm, springtail, isopod and nematodes are poorly understood. The main goal of this study was to compare the bioaccumulation factor (BAFs) and subcellular partitioning of nanoparticles in the soil-dwelling earthworm (Eisenia fetida) from ENP (ZnO and Ag nanoparticles) or ionic metal (Zn2+, Ag+) contaminated soil. And the sequential extraction was also used to determine the mobility of metals in soil which could be used as to predict bioavailability and compare that with bioaccumulation factor. The radiotracer method was employed to trace the transfer of ENPs and ionic metal among different environmental media and animals. Radiolabeled 65ZnO, 110mAgNPs coated with PVP or citrate were synthesized in the laboratory and their chemical and biological behavior was compared to ionic 65Zn and 110mAg. The BAFs of Zn and Ag in the earthworms were determined after animals exposed to the contaminated soils. After the 7 days of elimination phase, subcellular partitioning of metals were also obtained. BAF for ZnO(0.06) was 31 times lower than that for Zn ion (1.86), suggesting that ZnO was less bioavailable than its ionic form from contaminated soil. On the other hands, BAFs for AgNPs coated with PVP (0.12) or with citrate (0.11) were comparable to those for Ag ion (0.17), indicating that Ag from contaminated soil was bioavailable in a similar rate regardless of chemical forms. The subcellular partitioning results showed that bioaccumulated Zn from Zn ion and ZnO contaminated soil were present mainly in HSP (heat-sensitive protein) while cellullar Ag from Ag ion and AgNPs (Ag/PVP, Ag/citrate) treatments were found mostly in cellular debris. No statistical difference in partitioning of metals among different subcelluar pools was found between the metal forms. Zn from ZnO contaminated solis was found largely in carbonate fraction (41%), while Zn from Zn ion treatment was found in Fe-Mn Oxide (29%). Association of Zn to mobile fractions (ZnO; 65%, Zn ion; 35%) suggest that Zn from ZnO contaminated soil would be more bioavailable than that from Zn ion treatment. However, the BAFs for Zn in the animals did not follow this prediction. Majority of Ag from AgNPs or Ag ion contaminated soil was bound mainly to biologically inert fractions mainly in organic matter, surphide fractions, and residual fractions. Consistent with these findings, the BAFs of Ag in the worms exposed to Ag contaminated soils were generally lower than those for Zn treatments.
Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

PubMed

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.
DeepLoc: prediction of protein subcellular localization using deep learning.

PubMed

Almagro Armenteros, José Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae; Nielsen, Henrik; Winther, Ole

2017-11-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict protein subcellular localization relying only on sequence information. At its core, the prediction model uses a recurrent neural network that processes the entire protein sequence and an attention mechanism identifying protein regions important for the subcellular localization. The model was trained and tested on a protein dataset extracted from one of the latest UniProt releases, in which experimentally annotated proteins follow more stringent criteria than previously. We demonstrate that our model achieves a good accuracy (78% for 10 categories; 92% for membrane-bound or soluble), outperforming current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc. Example code is available at https://github.com/JJAlmagro/subcellular_localization. The dataset is available at http://www.cbs.dtu.dk/services/DeepLoc/data.php. jjalma@dtu.dk. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Mercury speciation and subcellular distribution in experimentally dosed and wild birds.

PubMed

Perkins, Marie; Barst, Benjamin D; Hadrava, Justine; Basu, Niladri

2017-12-01

Many bird species are exposed to methylmercury (MeHg) at levels shown to cause sublethal effects. Although MeHg sensitivity and assimilation can vary among species and developmental stages, the underlying reasons (such as MeHg toxicokinetics) are poorly understood. We investigated Hg distribution at the tissue and cellular levels in birds by examining Hg speciation in blood, brain, and liver and Hg subcellular distribution in liver. We used MeHg egg injection of white leghorn chicken (Gallus gallus domesticus), sampled at 3 early developmental stages, and embryonic ring-billed gulls (Larus delawarensis) exposed to maternally deposited MeHg. The percentage of MeHg (relative to total Hg [THg]) in blood, brain, and liver ranged from 94 to 121%, indicating little MeHg demethylation. A liver subcellular partitioning procedure was used to determine how THg was distributed between potentially sensitive and detoxified compartments. The distributions of THg among subcellular fractions were similar among chicken time points, and between embryonic chicken and ring-billed gulls. A greater proportion of THg was associated with metal-sensitive fractions than detoxified fractions. Within the sensitive compartment, THg was found predominately in heat-denatured proteins (∼42-46%), followed by mitochondria (∼15-18%). A low rate of MeHg demethylation and high proportion of THg in metal-sensitive subcellular fractions further indicates that embryonic and hatchling time points are Hg-sensitive developmental stages, although further work is needed across a range of additional species and life stages. Environ Toxicol Chem 2017;36:3289-3298. © 2017 SETAC. © 2017 SETAC.
pLoc-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC.

PubMed

Cheng, Xiang; Xiao, Xuan; Chou, Kuo-Chen

2017-10-06

Information of the proteins' subcellular localization is crucially important for revealing their biological functions in a cell, the basic unit of life. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop computational tools for timely identifying their subcellular locations based on the sequence information alone. The current study is focused on the Gram-negative bacterial proteins. Although considerable efforts have been made in protein subcellular prediction, the problem is far from being solved yet. This is because mounting evidences have indicated that many Gram-negative bacterial proteins exist in two or more location sites. Unfortunately, most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions important for both basic research and drug design. In this study, by using the multi-label theory, we developed a new predictor called "pLoc-mGneg" for predicting the subcellular localization of Gram-negative bacterial proteins with both single and multiple locations. Rigorous cross-validation on a high quality benchmark dataset indicated that the proposed predictor is remarkably superior to "iLoc-Gneg", the state-of-the-art predictor for the same purpose. For the convenience of most experimental scientists, a user-friendly web-server for the novel predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGneg/, by which users can easily get their desired results without the need to go through the complicated mathematics involved. Copyright © 2017 Elsevier Inc. All rights reserved.
Subcellular Localized Chemical Imaging of Benthic Algal Nutritional Content via HgCdTe Array FT-IR

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

Wetzel, D.; Murdock, J; Dodds, W

2008-01-01

Algae respond rapidly and uniquely to changes in nutrient availability by adjusting pigment, storage product, and organelle content and quality. Cellular and subcellular variability of the relative abundance of macromolecular pools (e.g. protein, lipid, carbohydrate, and phosphodiesters) within the benthic (bottom dwelling) alga Cladophora glomerata (a common nuisance species in fresh and saline waters) was revealed by FT-IR microspectroscopic imaging. Nutrient heterogeneity was compared at the filament, cellular, and subcellular level, and localized nutrient uptake kinetics were studied by detecting the gradual incorporation of isotopically labeled nitrogen (N) (as K15NO3) from surrounding water into cellular proteins. Nutritional content differed substantiallymore » among filament cells, with differences driven by protein and lipid abundance. Whole cell imaging showed high subcellular macromolecular variability in all cells, including adjacent cells on a filament that developed clonally. N uptake was also very heterogeneous, both within and among cells, and did not appear to coincide with subcellular protein distribution. Despite high intercellular variability, some patterns emerged. Cells acquired more 15N the further they were away from the filament attachment point, and 15N incorporation was more closely correlated with phosphodiester content than protein, lipid, or carbohydrate content. Benthic algae are subject to substantial environmental heterogeneity induced by microscale hydrodynamic factors and spatial variability in nutrient availability. Species specific responses to nutrient heterogeneity are central to understanding this key component of aquatic ecosystems. FT-IR microspectroscopy, modified for benthic algae, allows determination of algal physiological responses at scales not available using current techniques.« less
Subcellular localization of the Hpa RxLR effector repertoire identifies a tonoplast-associated protein HaRxL17 that confers enhanced plant susceptibility.

PubMed

Caillaud, Marie-Cécile; Piquerez, Sophie J M; Fabro, Georgina; Steinbrenner, Jens; Ishaque, Naveed; Beynon, Jim; Jones, Jonathan D G

2012-01-01

Filamentous phytopathogens form sophisticated intracellular feeding structures called haustoria in plant cells. Pathogen effectors are likely to play a role in the establishment and maintenance of haustoria in addition to their better-characterized role in suppressing plant defence. However, the specific mechanisms by which these effectors promote virulence remain unclear. To address this question, we examined changes in subcellular architecture using live-cell imaging during the compatible interaction between the oomycete Hyaloperonospora arabidopsidis (Hpa) and its host Arabidopsis. We monitored host-cell restructuring of subcellular compartments within plant mesophyll cells during haustoria ontogenesis. Live-cell imaging highlighted rearrangements in plant cell membranes upon infection, in particular to the tonoplast, which was located close to the extra-haustorial membrane surrounding the haustorium. We also investigated the subcellular localization patterns of Hpa RxLR effector candidates (HaRxLs) in planta. We identified two major classes of HaRxL effector based on localization: nuclear-localized effectors and membrane-localized effectors. Further, we identified a single effector, HaRxL17, that associated with the tonoplast in uninfected cells and with membranes around haustoria, probably the extra-haustorial membrane, in infected cells. Functional analysis of selected effector candidates in planta revealed that HaRxL17 enhances plant susceptibility. The roles of subcellular changes and effector localization, with specific reference to the potential role of HaRxL17 in plant cell membrane trafficking, are discussed with respect to Hpa virulence. © 2011 The Authors. The Plant Journal © 2011 Blackwell Publishing Ltd.
Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

PubMed

Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

2011-08-21

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.
Distinct domains within the NITROGEN LIMITATION ADAPTATION protein mediate its subcellular localization and function in the nitrate-dependent phosphate homeostasis pathway

USDA-ARS?s Scientific Manuscript database

The NITROGEN LIMITATION ADAPTATION (NLA) protein is a RING-type E3 ubiquitin ligase that plays an essential role in the regulation of nitrogen and phosphate homeostasis. NLA is localized to two distinct subcellular sites, the plasma membrane and nucleus, and contains four distinct domains: i) a RING...
Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

PubMed

Peng, Tao; Bonamy, Ghislain M C; Glory-Afshar, Estelle; Rines, Daniel R; Chanda, Sumit K; Murphy, Robert F

2010-02-16

Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amount of fluorescence they contain. Unfortunately, this approach requires extensive hand-tuning of algorithms and is often cell type-dependent. Here we describe a machine-learning approach for estimating the amount of fluorescent signal in different subcellular compartments without hand tuning, requiring only the acquisition of separate training images of markers for each compartment. In testing on images of cells stained with mixtures of probes for different organelles, we achieved a 93% correlation between estimated and expected amounts of probes in each compartment. We also demonstrated that the method can be used to quantify drug-dependent protein translocations. The method enables automated and unbiased determination of the distributions of protein across cellular compartments, and will significantly improve imaging-based high-throughput assays and facilitate proteome-scale localization efforts.

Intracellular And Subcellular Partitioning Of Nickel In Aureococcus Anophagefferens

NASA Astrophysics Data System (ADS)

Wang, B.; Axe, L.; Wei, L.; Bagheri, S.; Michalopoulou, Z.

2008-12-01

Brown tides are caused by Aureococcus anophagefferens, a species of Pelagophyceae, and have been observed in NY/NJ waterways effecting ecosystems by attenuating light, changing water color, reducing eelgrass beds, decreasing shellfisheries, and further impacting the food web by reducing phytoplankton. Although the impact of macronutrients and iron on A. anophagefferens has been well studied, contaminants, and specifically trace metals have not. In long-term experiments designed to investigate the growth and toxicity, Cd, Cu, Ni, and Zn exposure was evaluated over 10-13 to 10-7 M for the free metal ion. While growth was inhibited or terminated from exposure to Cd and Cu, nickel addition ([Ni2+]: 10-11.23 to 10-10.23 M) promoted A. anophagefferens growth. Short-term experiments are being conducted to better understand mechanistically nickel speciation and distribution. Both total intracellular and subcellular metal concentrations are being assessed with radio-labeled 63Ni. Subcellular fractions are defined as metal-sensitive fractions (MSF) constituting organelles, cell debris, and heat-denatured protein [HDP] and biologically detoxified metal comprising heat-stabilized protein [HSP] and metal-rich granules [MRG]. Based on subcellular distribution, aqueous [Ni2+] concentrations, and A. anophagefferens growth rates, potential reaction pathways promoting A. anophagefferens growth can be addressed.
Trafficking of plant plasma membrane aquaporins: multiple regulation levels and complex sorting signals.

PubMed

Chevalier, Adrien S; Chaumont, François

2015-05-01

Aquaporins are small channel proteins which facilitate the diffusion of water and small neutral molecules across biological membranes. Compared with animals, plant genomes encode numerous aquaporins, which display a large variety of subcellular localization patterns. More specifically, plant aquaporins of the plasma membrane intrinsic protein (PIP) subfamily were first described as plasma membrane (PM)-resident proteins, but recent research has demonstrated that the trafficking and subcellular localization of these proteins are complex and highly regulated. In the past few years, PIPs emerged as new model proteins to study subcellular sorting and membrane dynamics in plant cells. At least two distinct sorting motifs (one cytosolic, the other buried in the membrane) are required to direct PIPs to the PM. Hetero-oligomerization and interaction with SNAREs (soluble N-ethylmaleimide-sensitive factor protein attachment protein receptors) also influence the subcellular trafficking of PIPs. In addition to these constitutive processes, both the progression of PIPs through the secretory pathway and their dynamics at the PM are responsive to changing environmental conditions. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Quantitative imaging with fluorescent biosensors.

PubMed

Okumoto, Sakiko; Jones, Alexander; Frommer, Wolf B

2012-01-01

Molecular activities are highly dynamic and can occur locally in subcellular domains or compartments. Neighboring cells in the same tissue can exist in different states. Therefore, quantitative information on the cellular and subcellular dynamics of ions, signaling molecules, and metabolites is critical for functional understanding of organisms. Mass spectrometry is generally used for monitoring ions and metabolites; however, its temporal and spatial resolution are limited. Fluorescent proteins have revolutionized many areas of biology-e.g., fluorescent proteins can report on gene expression or protein localization in real time-yet promoter-based reporters are often slow to report physiologically relevant changes such as calcium oscillations. Therefore, novel tools are required that can be deployed in specific cells and targeted to subcellular compartments in order to quantify target molecule dynamics directly. We require tools that can measure enzyme activities, protein dynamics, and biophysical processes (e.g., membrane potential or molecular tension) with subcellular resolution. Today, we have an extensive suite of tools at our disposal to address these challenges, including translocation sensors, fluorescence-intensity sensors, and Förster resonance energy transfer sensors. This review summarizes sensor design principles, provides a database of sensors for more than 70 different analytes/processes, and gives examples of applications in quantitative live cell imaging.
Long-working-distance fluorescence microscope with high-numerical-aperture objectives for variable-magnification imaging in live mice from macro- to subcellular

NASA Astrophysics Data System (ADS)

Kimura, Hiroaki; Momiyama, Masashi; Tomita, Katsuro; Tsuchiya, Hiroyuki; Hoffman, Robert M.

2010-11-01

We demonstrate the development of a long-working-distance fluorescence microscope with high-numerical-aperture objectives for variable-magnification imaging in live mice from macro- to subcellular. To observe cytoplasmic and nuclear dynamics of cancer cells in the living mouse, 143B human osteosarcoma cells are labeled with green fluorescent protein in the nucleus and red fluorescent protein in the cytoplasm. These dual-color cells are injected by a vascular route in an abdominal skin flap in nude mice. The mice are then imaged with the Olympus MVX10 macroview fluorescence microscope. With the MVX10, the nuclear and cytoplasmic behavior of cancer cells trafficking in blood vessels of live mice is observed. We also image lung metastases in live mice from the macro- to the subcellular level by opening the chest wall and imaging the exposed lung in live mice. Injected splenocytes, expressing cyan fluorescent protein, could also be imaged on the lung of live mice. We demonstrate that the MVX10 microscope offers the possibility of full-range in vivo fluorescence imaging from macro- to subcellular and should enable widespread use of powerful imaging technologies enabled by genetic reporters and other fluorophores.
A Comprehensive Subcellular Proteomic Survey of Salmonella Grown under Phagosome-Mimicking versus Standard Laboratory Conditions

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

Brown, Roslyn N.; Sanford, James A.; Park, Jea H.

Towards developing a systems-level pathobiological understanding of Salmonella enterica, we performed a subcellular proteomic analysis of this pathogen grown under standard laboratory and infection-mimicking conditions in vitro. Analysis of proteins from cytoplasmic, inner membrane, periplasmic, and outer membrane fractions yielded coverage of over 30% of the theoretical proteome. Confident subcellular location could be assigned to over 1000 proteins, with good agreement between experimentally observed location and predicted/known protein properties. Comparison of protein location under the different environmental conditions provided insight into dynamic protein localization and possible moonlighting (multiple function) activities. Notable examples of dynamic localization were the response regulators ofmore » two-component regulatory systems (e.g., ArcB, PhoQ). The DNA-binding protein Dps that is generally regarded as cytoplasmic was significantly enriched in the outer membrane for all growth conditions examined, suggestive of moonlighting activities. These observations imply the existence of unknown transport mechanisms and novel functions for a subset of Salmonella proteins. Overall, this work provides a catalog of experimentally verified subcellular protein location for Salmonella and a framework for further investigations using computational modeling.« less
Internalization and Subcellular Trafficking of Poly-l-lysine Dendrimers Are Impacted by the Site of Fluorophore Conjugation.

PubMed

Avaritt, Brittany R; Swaan, Peter W

2015-06-01

Internalization and intracellular trafficking of dendrimer-drug conjugates play an important role in achieving successful drug delivery. In this study, we aimed to elucidate the endocytosis mechanisms and subcellular localization of poly-l-lysine (PLL) dendrimers in Caco-2 cells. We also investigated the impact of fluorophore conjugation on cytotoxicity, uptake, and transepithelial transport. Oregon green 514 (OG) was conjugated to PLL G3 at either the dendrimer periphery or the core. Chemical inhibitors of clathrin-, caveolin-, cholesterol-, and dynamin-mediated endocytosis pathways and macropinocytosis were employed to establish internalization mechanisms, while colocalization with subcellular markers was used to determine dendrimer trafficking. Cell viability, internalization, and uptake were all influenced by the site of fluorophore conjugation. Uptake was found to be highly dependent on cholesterol- and dynamin-mediated endocytosis as well as macropinocytosis. Dendrimers were trafficked to endosomes and lysosomes, and subcellular localization was impacted by the fluorophore conjugation site. The results of this study indicate that PLL dendrimers exploit multiple pathways for cellular entry, and internalization and trafficking can be impacted by conjugation. Therefore, design of dendrimer-drug conjugates requires careful consideration to achieve successful drug delivery.
Differential subcellular distribution of ion channels and the diversity of neuronal function.

PubMed

Nusser, Zoltan

2012-06-01

Following the astonishing molecular diversity of voltage-gated ion channels that was revealed in the past few decades, the ion channel repertoire expressed by neurons has been implicated as the major factor governing their functional heterogeneity. Although the molecular structure of ion channels is a key determinant of their biophysical properties, their subcellular distribution and densities on the surface of nerve cells are just as important for fulfilling functional requirements. Recent results obtained with high resolution quantitative localization techniques revealed complex, subcellular compartment-specific distribution patterns of distinct ion channels. Here I suggest that within a given neuron type every ion channel has a unique cell surface distribution pattern, with the functional consequence that this dramatically increases the computational power of nerve cells. Copyright © 2011 Elsevier Ltd. All rights reserved.
A Toddler's Treatment of "Mm" and "Mm Hm" in Talk with a Parent

ERIC Educational Resources Information Center

Filipi, Anna

2007-01-01

The study to be reported in this paper examined the work accomplished by "mm" and "mm hm" in the interactions of a parent and his daughter aged 0;10-2;0. Using the findings of Gardner (2001) for adults, the analysis shows that "mm" accomplished a range of functions based on its sequential placement and prosodic features, whereas "mm hm" was much…
EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

PubMed

Kortelainen, Jukka; Seppänen, Tapio

2013-01-01

Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.
Simultaneous and sequential hemorrhage of multiple cerebral cavernous malformations: a case report.

PubMed

Louis, Nundia; Marsh, Robert

2016-02-09

The etiology of cerebral cavernous malformation hemorrhage is not well understood. Causative physiologic parameters preceding hemorrhagic cavernous malformation events are often not reported. We present a case of an individual with sequential simultaneous hemorrhages in multiple cerebral cavernous malformations with a new onset diagnosis of hypertension. A 42-year-old white man was admitted to our facility with worsening headache, left facial and tongue numbness, dizziness, diplopia, and elevated blood pressure. His past medical history was significant for new onset diagnosis of hypertension and chronic seasonal allergies. Serial imaging over the ensuing 8 days revealed sequential hemorrhagic lesions. He underwent suboccipital craniotomy for resection of the lesions located in the fourth ventricle and right cerebellum. One month after surgery, he had near complete resolution of his symptoms with mild residual vertigo but symptomatic chronic hypertension. Many studies have focused on genetic and inflammatory mechanisms contributing to cerebral cavernous malformation rupture, but few have reported on the potential of hemodynamic changes contributing to cerebral cavernous malformation rupture. Systemic blood pressure changes clearly have an effect on angioma pressures. When considering the histopathological features of cerebral cavernous malformation architecture, changes in arterial pressure could cause meaningful alterations in hemorrhage propensity and patterns.
Sequential programmable self-assembly: Role of cooperative interactions

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

Jonathan D. Halverson; Tkachenko, Alexei V.

Here, we propose a general strategy of “sequential programmable self-assembly” that enables a bottom-up design of arbitrary multi-particle architectures on nano- and microscales. We show that a naive realization of this scheme, based on the pairwise additive interactions between particles, has fundamental limitations that lead to a relatively high error rate. This can be overcome by using cooperative interparticle binding. The cooperativity is a well known feature of many biochemical processes, responsible, e.g., for signaling and regulations in living systems. Here we propose to utilize a similar strategy for high precision self-assembly, and show that DNA-mediated interactions provide a convenientmore » platform for its implementation. In particular, we outline a specific design of a DNA-based complex which we call “DNA spider,” that acts as a smart interparticle linker and provides a built-in cooperativity of binding. We demonstrate versatility of the sequential self-assembly based on spider-functionalized particles by designing several mesostructures of increasing complexity and simulating their assembly process. This includes a number of finite and repeating structures, in particular, the so-called tetrahelix and its several derivatives. Due to its generality, this approach allows one to design and successfully self-assemble virtually any structure made of a “GEOMAG” magnetic construction toy, out of nanoparticles. According to our results, once the binding cooperativity is strong enough, the sequential self-assembly becomes essentially error-free.« less
Sequential programmable self-assembly: Role of cooperative interactions

DOE PAGES

Jonathan D. Halverson; Tkachenko, Alexei V.

2016-03-04

Here, we propose a general strategy of “sequential programmable self-assembly” that enables a bottom-up design of arbitrary multi-particle architectures on nano- and microscales. We show that a naive realization of this scheme, based on the pairwise additive interactions between particles, has fundamental limitations that lead to a relatively high error rate. This can be overcome by using cooperative interparticle binding. The cooperativity is a well known feature of many biochemical processes, responsible, e.g., for signaling and regulations in living systems. Here we propose to utilize a similar strategy for high precision self-assembly, and show that DNA-mediated interactions provide a convenientmore » platform for its implementation. In particular, we outline a specific design of a DNA-based complex which we call “DNA spider,” that acts as a smart interparticle linker and provides a built-in cooperativity of binding. We demonstrate versatility of the sequential self-assembly based on spider-functionalized particles by designing several mesostructures of increasing complexity and simulating their assembly process. This includes a number of finite and repeating structures, in particular, the so-called tetrahelix and its several derivatives. Due to its generality, this approach allows one to design and successfully self-assemble virtually any structure made of a “GEOMAG” magnetic construction toy, out of nanoparticles. According to our results, once the binding cooperativity is strong enough, the sequential self-assembly becomes essentially error-free.« less
Polymeric microchip for the simultaneous determination of anions and cations by hydrodynamic injection using a dual-channel sequential injection microchip electrophoresis system.

PubMed

Gaudry, Adam J; Nai, Yi Heng; Guijt, Rosanne M; Breadmore, Michael C

2014-04-01

A dual-channel sequential injection microchip capillary electrophoresis system with pressure-driven injection is demonstrated for simultaneous separations of anions and cations from a single sample. The poly(methyl methacrylate) (PMMA) microchips feature integral in-plane contactless conductivity detection electrodes. A novel, hydrodynamic "split-injection" method utilizes background electrolyte (BGE) sheathing to gate the sample flows, while control over the injection volume is achieved by balancing hydrodynamic resistances using external hydrodynamic resistors. Injection is realized by a unique flow-through interface, allowing for automated, continuous sampling for sequential injection analysis by microchip electrophoresis. The developed system was very robust, with individual microchips used for up to 2000 analyses with lifetimes limited by irreversible blockages of the microchannels. The unique dual-channel geometry was demonstrated by the simultaneous separation of three cations and three anions in individual microchannels in under 40 s with limits of detection (LODs) ranging from 1.5 to 24 μM. From a series of 100 sequential injections the %RSDs were determined for every fifth run, resulting in %RSDs for migration times that ranged from 0.3 to 0.7 (n = 20) and 2.3 to 4.5 for peak area (n = 20). This system offers low LODs and a high degree of reproducibility and robustness while the hydrodynamic injection eliminates electrokinetic bias during injection, making it attractive for a wide range of rapid, sensitive, and quantitative online analytical applications.
Imaging sequential dehydrogenation of methanol on Cu(110) with a scanning tunneling microscope.

PubMed

Kitaguchi, Y; Shiotari, A; Okuyama, H; Hatta, S; Aruga, T

2011-05-07

Adsorption of methanol and its dehydrogenation on Cu(110) were studied by using a scanning tunneling microscope (STM). Upon adsorption at 12 K, methanol preferentially forms clusters on the surface. The STM could induce dehydrogenation of methanol sequentially to methoxy and formaldehyde. This enabled us to study the binding structures of these products in a single-molecule limit. Methoxy was imaged as a pair of protrusion and depression along the [001] direction. This feature is fully consistent with the previous result that it adsorbs on the short-bridge site with the C-O axis tilted along the [001] direction. The axis was induced to flip back and forth by vibrational excitations with the STM. Two configurations were observed for formaldehyde, whose structures were proposed based on their characteristic images and motions.
Research on sparse feature matching of improved RANSAC algorithm

NASA Astrophysics Data System (ADS)

Kong, Xiangsi; Zhao, Xian

2018-04-01

In this paper, a sparse feature matching method based on modified RANSAC algorithm is proposed to improve the precision and speed. Firstly, the feature points of the images are extracted using the SIFT algorithm. Then, the image pair is matched roughly by generating SIFT feature descriptor. At last, the precision of image matching is optimized by the modified RANSAC algorithm,. The RANSAC algorithm is improved from three aspects: instead of the homography matrix, this paper uses the fundamental matrix generated by the 8 point algorithm as the model; the sample is selected by a random block selecting method, which ensures the uniform distribution and the accuracy; adds sequential probability ratio test(SPRT) on the basis of standard RANSAC, which cut down the overall running time of the algorithm. The experimental results show that this method can not only get higher matching accuracy, but also greatly reduce the computation and improve the matching speed.
Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features.

PubMed

Sun, Ming-An; Zhang, Qing; Wang, Yejun; Ge, Wei; Guo, Dianjing

2016-08-24

Reactive oxygen species can modify the structure and function of proteins and may also act as important signaling molecules in various cellular processes. Cysteine thiol groups of proteins are particularly susceptible to oxidation. Meanwhile, their reversible oxidation is of critical roles for redox regulation and signaling. Recently, several computational tools have been developed for predicting redox-sensitive cysteines; however, those methods either only focus on catalytic redox-sensitive cysteines in thiol oxidoreductases, or heavily depend on protein structural data, thus cannot be widely used. In this study, we analyzed various sequence-based features potentially related to cysteine redox-sensitivity, and identified three types of features for efficient computational prediction of redox-sensitive cysteines. These features are: sequential distance to the nearby cysteines, PSSM profile and predicted secondary structure of flanking residues. After further feature selection using SVM-RFE, we developed Redox-Sensitive Cysteine Predictor (RSCP), a SVM based classifier for redox-sensitive cysteine prediction using primary sequence only. Using 10-fold cross-validation on RSC758 dataset, the accuracy, sensitivity, specificity, MCC and AUC were estimated as 0.679, 0.602, 0.756, 0.362 and 0.727, respectively. When evaluated using 10-fold cross-validation with BALOSCTdb dataset which has structure information, the model achieved performance comparable to current structure-based method. Further validation using an independent dataset indicates it is robust and of relatively better accuracy for predicting redox-sensitive cysteines from non-enzyme proteins. In this study, we developed a sequence-based classifier for predicting redox-sensitive cysteines. The major advantage of this method is that it does not rely on protein structure data, which ensures more extensive application compared to other current implementations. Accurate prediction of redox-sensitive cysteines not only enhances our understanding about the redox sensitivity of cysteine, it may also complement the proteomics approach and facilitate further experimental investigation of important redox-sensitive cysteines.
Self-folding with shape memory composites at the millimeter scale

NASA Astrophysics Data System (ADS)

Felton, S. M.; Becker, K. P.; Aukes, D. M.; Wood, R. J.

2015-08-01

Self-folding is an effective method for creating 3D shapes from flat sheets. In particular, shape memory composites—laminates containing shape memory polymers—have been used to self-fold complex structures and machines. To date, however, these composites have been limited to feature sizes larger than one centimeter. We present a new shape memory composite capable of folding millimeter-scale features. This technique can be activated by a global heat source for simultaneous folding, or by resistive heaters for sequential folding. It is capable of feature sizes ranging from 0.5 to 40 mm, and is compatible with multiple laminate compositions. We demonstrate the ability to produce complex structures and mechanisms by building two self-folding pieces: a model ship and a model bumblebee.
Multi-sensor image registration based on algebraic projective invariants.

PubMed

Li, Bin; Wang, Wei; Ye, Hao

2013-04-22

A new automatic feature-based registration algorithm is presented for multi-sensor images with projective deformation. Contours are firstly extracted from both reference and sensed images as basic features in the proposed method. Since it is difficult to design a projective-invariant descriptor from the contour information directly, a new feature named Five Sequential Corners (FSC) is constructed based on the corners detected from the extracted contours. By introducing algebraic projective invariants, we design a descriptor for each FSC that is ensured to be robust against projective deformation. Further, no gray scale related information is required in calculating the descriptor, thus it is also robust against the gray scale discrepancy between the multi-sensor image pairs. Experimental results utilizing real image pairs are presented to show the merits of the proposed registration method.
Trading efficiency for effectiveness in similarity-based indexing for image databases

NASA Astrophysics Data System (ADS)

Barros, Julio E.; French, James C.; Martin, Worthy N.; Kelly, Patrick M.

1995-11-01

Image databases typically manage feature data that can be viewed as points in a feature space. Some features, however, can be better expressed as a collection of points or described by a probability distribution function (PDF) rather than as a single point. In earlier work we introduced a similarity measure and a method for indexing and searching the PDF descriptions of these items that guarantees an answer equivalent to sequential search. Unfortunately, certain properties of the data can restrict the efficiency of that method. In this paper we extend that work and examine trade-offs between efficiency and answer quality or effectiveness. These trade-offs reduce the amount of work required during a search by reducing the number of undesired items fetched without excluding an excessive number of the desired ones.
Multi-location gram-positive and gram-negative bacterial protein subcellular localization using gene ontology and multi-label classifier ensemble.

PubMed

Wang, Xiao; Zhang, Jun; Li, Guo-Zheng

2015-01-01

It has become a very important and full of challenge task to predict bacterial protein subcellular locations using computational methods. Although there exist a lot of prediction methods for bacterial proteins, the majority of these methods can only deal with single-location proteins. But unfortunately many multi-location proteins are located in the bacterial cells. Moreover, multi-location proteins have special biological functions capable of helping the development of new drugs. So it is necessary to develop new computational methods for accurately predicting subcellular locations of multi-location bacterial proteins. In this article, two efficient multi-label predictors, Gpos-ECC-mPLoc and Gneg-ECC-mPLoc, are developed to predict the subcellular locations of multi-label gram-positive and gram-negative bacterial proteins respectively. The two multi-label predictors construct the GO vectors by using the GO terms of homologous proteins of query proteins and then adopt a powerful multi-label ensemble classifier to make the final multi-label prediction. The two multi-label predictors have the following advantages: (1) they improve the prediction performance of multi-label proteins by taking the correlations among different labels into account; (2) they ensemble multiple CC classifiers and further generate better prediction results by ensemble learning; and (3) they construct the GO vectors by using the frequency of occurrences of GO terms in the typical homologous set instead of using 0/1 values. Experimental results show that Gpos-ECC-mPLoc and Gneg-ECC-mPLoc can efficiently predict the subcellular locations of multi-label gram-positive and gram-negative bacterial proteins respectively. Gpos-ECC-mPLoc and Gneg-ECC-mPLoc can efficiently improve prediction accuracy of subcellular localization of multi-location gram-positive and gram-negative bacterial proteins respectively. The online web servers for Gpos-ECC-mPLoc and Gneg-ECC-mPLoc predictors are freely accessible at http://biomed.zzuli.edu.cn/bioinfo/gpos-ecc-mploc/ and http://biomed.zzuli.edu.cn/bioinfo/gneg-ecc-mploc/ respectively.

Rapid Construction of a Benzo-Fused Indoxamycin Core Enabled by Site-Selective C-H Functionalizations.

PubMed

Bedell, T Aaron; Hone, Graham A B; Valette, Damien; Yu, Jin-Quan; Davies, Huw M L; Sorensen, Erik J

2016-07-11

Methods for functionalizing carbon-hydrogen bonds are featured in a new synthesis of the tricyclic core architecture that characterizes the indoxamycin family of secondary metabolites. A unique collaboration between three laboratories has engendered a design for synthesis featuring two sequential C-H functionalization reactions, namely a diastereoselective dirhodium carbene insertion followed by an ester-directed oxidative Heck cyclization, to rapidly assemble the congested tricyclic core of the indoxamycins. This project exemplifies how multi-laboratory collaborations can foster conceptually novel approaches to challenging problems in chemical synthesis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Algorithm, applications and evaluation for protein comparison by Ramanujan Fourier transform.

PubMed

Zhao, Jian; Wang, Jiasong; Hua, Wei; Ouyang, Pingkai

2015-12-01

The amino acid sequence of a protein determines its chemical properties, chain conformation and biological functions. Protein sequence comparison is of great importance to identify similarities of protein structures and infer their functions. Many properties of a protein correspond to the low-frequency signals within the sequence. Low frequency modes in protein sequences are linked to the secondary structures, membrane protein types, and sub-cellular localizations of the proteins. In this paper, we present Ramanujan Fourier transform (RFT) with a fast algorithm to analyze the low-frequency signals of protein sequences. The RFT method is applied to similarity analysis of protein sequences with the Resonant Recognition Model (RRM). The results show that the proposed fast RFT method on protein comparison is more efficient than commonly used discrete Fourier transform (DFT). RFT can detect common frequencies as significant feature for specific protein families, and the RFT spectrum heat-map of protein sequences demonstrates the information conservation in the sequence comparison. The proposed method offers a new tool for pattern recognition, feature extraction and structural analysis on protein sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.
Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.
On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.
Polymeric nanoparticles for targeted drug delivery system for cancer therapy.

PubMed

Masood, Farha

2016-03-01

A targeted delivery system based on the polymeric nanoparticles as a drug carrier represents a marvelous avenue for cancer therapy. The pivotal characteristics of this system include biodegradability, biocompatibility, non-toxicity, prolonged circulation and a wide payload spectrum of a therapeutic agent. Other outstanding features are their distinctive size and shape properties for tissue penetration via an active and passive targeting, specific cellular/subcellular trafficking pathways and facile control of cargo release by sophisticated material engineering. In this review, the current implications of encapsulation of anticancer agents within polyhydroxyalkanoates, poly-(lactic-co-glycolic acid) and cyclodextrin based nanoparticles to precisely target the tumor site, i.e., cell, tissue and organ are highlighted. Furthermore, the promising perspectives in this emerging field are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.
Molecular Regulation of Lumen Morphogenesis Review

PubMed Central

Datta, Anirban; Bryant, David M.; Mostov, Keith E.

2013-01-01

The asymmetric polarization of cells allows specialized functions to be performed at discrete subcellular locales. Spatiotemporal coordination of polarization between groups of cells allowed the evolution of metazoa. For instance, coordinated apical-basal polarization of epithelial and endothelial cells allows transport of nutrients and metabolites across cell barriers and tissue microenvironments. The defining feature of such tissues is the presence of a central, interconnected luminal network. Although tubular networks are present in seemingly different organ systems, such as the kidney, lung, and blood vessels, common underlying principles govern their formation. Recent studies using in vivo and in vitro models of lumen formation have shed new light on the molecular networks regulating this fundamental process. We here discuss progress in understanding common design principles underpinning de novo lumen formation and expansion. PMID:21300279
Separate responses of karyopherins to glucose and amino acid availability regulate nucleocytoplasmic transport.

PubMed

Huang, Hsiao-Yun; Hopper, Anita K

2014-09-15

The importin-β family members (karyopherins) mediate the majority of nucleocytoplasmic transport. Msn5 and Los1, members of the importin-β family, function in tRNA nuclear export. tRNAs move bidirectionally between the nucleus and the cytoplasm. Nuclear tRNA accumulation occurs upon amino acid (aa) or glucose deprivation. To understand the mechanisms regulating tRNA subcellular trafficking, we investigated whether Msn5 and Los1 are regulated in response to nutrient availability. We provide evidence that tRNA subcellular trafficking is regulated by distinct aa-sensitive and glucose-sensitive mechanisms. Subcellular distributions of Msn5 and Los1 are altered upon glucose deprivation but not aa deprivation. Redistribution of tRNA exportins from the nucleus to the cytoplasm likely provides one mechanism for tRNA nuclear distribution upon glucose deprivation. We extended our studies to other members of the importin-β family and found that all tested karyopherins invert their subcellular distributions upon glucose deprivation but not aa deprivation. Glucose availability regulates the subcellular distributions of karyopherins likely due to alteration of the RanGTP gradient since glucose deprivation causes redistribution of Ran. Thus nuclear-cytoplasmic distribution of macromolecules is likely generally altered upon glucose deprivation due to collapse of the RanGTP gradient and redistribution of karyopherins between the nucleus and the cytoplasm. © 2014 Huang and Hopper. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
PLPD: reliable protein localization prediction from imbalanced and overlapped datasets

PubMed Central

Lee, KiYoung; Kim, Dae-Won; Na, DoKyun; Lee, Kwang H.; Lee, Doheon

2006-01-01

Subcellular localization is one of the key functional characteristics of proteins. An automatic and efficient prediction method for the protein subcellular localization is highly required owing to the need for large-scale genome analysis. From a machine learning point of view, a dataset of protein localization has several characteristics: the dataset has too many classes (there are more than 10 localizations in a cell), it is a multi-label dataset (a protein may occur in several different subcellular locations), and it is too imbalanced (the number of proteins in each localization is remarkably different). Even though many previous works have been done for the prediction of protein subcellular localization, none of them tackles effectively these characteristics at the same time. Thus, a new computational method for protein localization is eventually needed for more reliable outcomes. To address the issue, we present a protein localization predictor based on D-SVDD (PLPD) for the prediction of protein localization, which can find the likelihood of a specific localization of a protein more easily and more correctly. Moreover, we introduce three measurements for the more precise evaluation of a protein localization predictor. As the results of various datasets which are made from the experiments of Huh et al. (2003), the proposed PLPD method represents a different approach that might play a complimentary role to the existing methods, such as Nearest Neighbor method and discriminate covariant method. Finally, after finding a good boundary for each localization using the 5184 classified proteins as training data, we predicted 138 proteins whose subcellular localizations could not be clearly observed by the experiments of Huh et al. (2003). PMID:16966337
Immature morphological properties in subcellular-scale structures in the dentate gyrus of Schnurri-2 knockout mice: a model for schizophrenia and intellectual disability.

PubMed

Nakao, Akito; Miyazaki, Naoyuki; Ohira, Koji; Hagihara, Hideo; Takagi, Tsuyoshi; Usuda, Nobuteru; Ishii, Shunsuke; Murata, Kazuyoshi; Miyakawa, Tsuyoshi

2017-12-12

Accumulating evidence suggests that subcellular-scale structures such as dendritic spine and mitochondria may be involved in the pathogenesis/pathophysiology of schizophrenia and intellectual disability. Previously, we proposed mice lacking Schnurri-2 (Shn2; also called major histocompatibility complex [MHC]-binding protein 2 [MBP-2], or human immunodeficiency virus type I enhancer binding protein 2 [HIVEP2]) as a schizophrenia and intellectual disability model with mild chronic inflammation. In the mutants' brains, there are increases in C4b and C1q genes, which are considered to mediate synapse elimination during postnatal development. However, morphological properties of subcellular-scale structures such as dendritic spine in Shn2 knockout (KO) mice remain unknown. In this study, we conducted three-dimensional morphological analyses in subcellular-scale structures in dentate gyrus granule cells of Shn2 KO mice by serial block-face scanning electron microscopy. Shn2 KO mice showed immature dendritic spine morphology characterized by increases in spine length and decreases in spine diameter. There was a non-significant tendency toward decrease in spine density of Shn2 KO mice over wild-type mice, and spine volume was indistinguishable between genotypes. Shn2 KO mice exhibited a significant reduction in GluR1 expression and a nominally significant decrease in SV2 expression, while PSD95 expression had a non-significant tendency to decrease in Shn2 KO mice. There were significant decreases in dendrite diameter, nuclear volume, and the number of constricted mitochondria in the mutants. Additionally, neuronal density was elevated in Shn2 KO mice. These results suggest that Shn2 KO mice serve as a unique tool for investigating morphological abnormalities of subcellular-scale structures in schizophrenia, intellectual disability, and its related disorders.
Limited Efficiency of Drug Delivery to Specific Intracellular Organelles Using Subcellularly "Targeted" Drug Delivery Systems.

PubMed

Maity, Amit Ranjan; Stepensky, David

2016-01-04

Many drugs have been designed to act on intracellular targets and to affect intracellular processes inside target cells. For the desired effects to be exerted, these drugs should permeate target cells and reach specific intracellular organelles. This subcellular drug targeting approach has been proposed for enhancement of accumulation of these drugs in target organelles and improved efficiency. This approach is based on drug encapsulation in drug delivery systems (DDSs) and/or their decoration with specific targeting moieties that are intended to enhance the drug/DDS accumulation in the intracellular organelle of interest. During recent years, there has been a constant increase in interest in DDSs targeted to specific intracellular organelles, and many different approaches have been proposed for attaining efficient drug delivery to specific organelles of interest. However, it appears that in many studies insufficient efforts have been devoted to quantitative analysis of the major formulation parameters of the DDSs disposition (efficiency of DDS endocytosis and endosomal escape, intracellular trafficking, and efficiency of DDS delivery to the target organelle) and of the resulting pharmacological effects. Thus, in many cases, claims regarding efficient delivery of drug/DDS to a specific organelle and efficient subcellular targeting appear to be exaggerated. On the basis of the available experimental data, it appears that drugs/DDS decoration with specific targeting residues can affect their intracellular fate and result in preferential drug accumulation within an organelle of interest. However, it is not clear whether these approaches will be efficient in in vivo settings and be translated into preclinical and clinical applications. Studies that quantitatively assess the mechanisms, barriers, and efficiencies of subcellular drug delivery and of the associated toxic effects are required to determine the therapeutic potential of subcellular DDS targeting.
Cdc2/cyclin B1 regulates centrosomal Nlp proteolysis and subcellular localization.

PubMed

Zhao, Xuelian; Jin, Shunqian; Song, Yongmei; Zhan, Qimin

2010-11-01

The formation of proper mitotic spindles is required for appropriate chromosome segregation during cell division. Aberrant spindle formation often causes aneuploidy and results in tumorigenesis. However, the underlying mechanism of regulating spindle formation and chromosome separation remains to be further defined. Centrosomal Nlp (ninein-like protein) is a recently characterized BRCA1-regulated centrosomal protein and plays an important role in centrosome maturation and spindle formation. In this study, we show that Nlp can be phosphorylated by cell cycle protein kinase Cdc2/cyclin B1. The phosphorylation sites of Nlp are mapped at Ser185 and Ser589. Interestingly, the Cdc2/cyclin B1 phosphorylation site Ser185 of Nlp is required for its recognition by PLK1, which enable Nlp depart from centrosomes to allow the establishment of a mitotic scaffold at the onset of mitosis . PLK1 fails to dissociate the Nlp mutant lacking Ser185 from centrosome, suggesting that Cdc2/cyclin B1 might serve as a primary kinase of PLK1 in regulating Nlp subcellular localization. However, the phosphorylation at the site Ser589 by Cdc2/cyclin B1 plays an important role in Nlp protein stability probably due to its effect on protein degradation. Furthermore, we show that deregulated expression or subcellular localization of Nlp lead to multinuclei in cells, indicating that scheduled levels of Nlp and proper subcellular localization of Nlp are critical for successful completion of normal cell mitosis, These findings demonstrate that Cdc2/cyclin B1 is a key regulator in maintaining appropriate degradation and subcellular localization of Nlp, providing novel insights into understanding on the role of Cdc2/cyclin B1 in mitotic progression.
Emergent cell and tissue dynamics from subcellular modeling of active biomechanical processes

NASA Astrophysics Data System (ADS)

Sandersius, S. A.; Weijer, C. J.; Newman, T. J.

2011-08-01

Cells and the tissues they form are not passive material bodies. Cells change their behavior in response to external biochemical and biomechanical cues. Behavioral changes, such as morphological deformation, proliferation and migration, are striking in many multicellular processes such as morphogenesis, wound healing and cancer progression. Cell-based modeling of these phenomena requires algorithms that can capture active cell behavior and their emergent tissue-level phenotypes. In this paper, we report on extensions of the subcellular element model to model active biomechanical subcellular processes. These processes lead to emergent cell and tissue level phenotypes at larger scales, including (i) adaptive shape deformations in cells responding to slow stretching, (ii) viscous flow of embryonic tissues, and (iii) streaming patterns of chemotactic cells in epithelial-like sheets. In each case, we connect our simulation results to recent experiments.
Biomechanics of subcellular structures by non-invasive Brillouin microscopy

NASA Astrophysics Data System (ADS)

Antonacci, Giuseppe; Braakman, Sietse

2016-11-01

Cellular biomechanics play a pivotal role in the pathophysiology of several diseases. Unfortunately, current methods to measure biomechanical properties are invasive and mostly limited to the surface of a cell. As a result, the mechanical behaviour of subcellular structures and organelles remains poorly characterised. Here, we show three-dimensional biomechanical images of single cells obtained with non-invasive, non-destructive Brillouin microscopy with an unprecedented spatial resolution. Our results quantify the longitudinal elastic modulus of subcellular structures. In particular, we found the nucleoli to be stiffer than both the nuclear envelope (p < 0.0001) and the surrounding cytoplasm (p < 0.0001). Moreover, we demonstrate the mechanical response of cells to Latrunculin-A, a drug that reduces cell stiffness by preventing cytoskeletal assembly. Our technique can therefore generate valuable insights into cellular biomechanics and its role in pathophysiology.
Mapping the subcellular localization of Fe3O4@TiO2 nanoparticles by X-ray Fluorescence Microscopy.

PubMed

Yuan, Y; Chen, S; Gleber, S C; Lai, B; Brister, K; Flachenecker, C; Wanzer, B; Paunesku, T; Vogt, S; Woloschak, G E

The targeted delivery of Fe 3 O 4 @TiO2 nanoparticles to cancer cells is an important step in their development as nanomedicines. We have synthesized nanoparticles that can bind the Epidermal Growth Factor Receptor, a cell surface protein that is overexpressed in many epithelial type cancers. In order to study the subcellular distribution of these nanoparticles, we have utilized the sub-micron resolution of X-ray Fluorescence Microscopy to map the locationof Fe 3 O4@TiO 2 NPs and other trace metal elements within HeLa cervical cancer cells. Here we demonstrate how the higher resolution of the newly installed Bionanoprobe at the Advanced Photon Source at Argonne National Laboratory can greatly improve our ability to distinguish intracellular nanoparticles and their spatial relationship with subcellular compartments.
Solid State Television Camera (CID)

NASA Technical Reports Server (NTRS)

Steele, D. W.; Green, W. T.

1976-01-01

The design, development and test are described of a charge injection device (CID) camera using a 244x248 element array. A number of video signal processing functions are included which maximize the output video dynamic range while retaining the inherently good resolution response of the CID. Some of the unique features of the camera are: low light level performance, high S/N ratio, antiblooming, geometric distortion, sequential scanning and AGC.
ISS EPS Orbital Replacement Unit Block Diagrams

NASA Technical Reports Server (NTRS)

Schmitz, Gregory V.

2001-01-01

The attached documents are being provided to Switching Power Magazine for information purposes. This magazine is writing a feature article on the International Space Station Electrical Power System, focusing on the switching power processors. These units include the DC-DC Converter Unit (DDCU), the Bi-directional Charge/Discharge Unit (BCDU), and the Sequential Shunt Unit (SSU). These diagrams are high-level schematics/block diagrams depicting the overall functionality of each unit.
Precision of working memory for visual motion sequences and transparent motion surfaces.

PubMed

Zokaei, Nahid; Gorgoraptis, Nikos; Bahrami, Bahador; Bays, Paul M; Husain, Masud

2011-12-01

Recent studies investigating working memory for location, color, and orientation support a dynamic resource model. We examined whether this might also apply to motion, using random dot kinematograms (RDKs) presented sequentially or simultaneously. Mean precision for motion direction declined as sequence length increased, with precision being lower for earlier RDKs. Two alternative models of working memory were compared specifically to distinguish between the contributions of different sources of error that corrupt memory (W. Zhang & S. J. Luck, 2008 vs. P. M. Bays, R. F. G. Catalao, & M. Husain, 2009). The latter provided a significantly better fit for the data, revealing that decrease in memory precision for earlier items is explained by an increase in interference from other items in a sequence rather than random guessing or a temporal decay of information. Misbinding feature attributes is an important source of error in working memory. Precision of memory for motion direction decreased when two RDKs were presented simultaneously as transparent surfaces, compared to sequential RDKs. However, precision was enhanced when one motion surface was prioritized, demonstrating that selective attention can improve recall precision. These results are consistent with a resource model that can be used as a general conceptual framework for understanding working memory across a range of visual features.
SHORT-TERM SOLAR FLARE PREDICTION USING MULTIRESOLUTION PREDICTORS

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

Yu Daren; Huang Xin; Hu Qinghua

2010-01-20

Multiresolution predictors of solar flares are constructed by a wavelet transform and sequential feature extraction method. Three predictors-the maximum horizontal gradient, the length of neutral line, and the number of singular points-are extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. A maximal overlap discrete wavelet transform is used to decompose the sequence of predictors into four frequency bands. In each band, four sequential features-the maximum, the mean, the standard deviation, and the root mean square-are extracted. The multiresolution predictors in the low-frequency band reflect trends in the evolution of newly emerging fluxes. The multiresolution predictors in the high-frequencymore » band reflect the changing rates in emerging flux regions. The variation of emerging fluxes is decoupled by wavelet transform in different frequency bands. The information amount of these multiresolution predictors is evaluated by the information gain ratio. It is found that the multiresolution predictors in the lowest and highest frequency bands contain the most information. Based on these predictors, a C4.5 decision tree algorithm is used to build the short-term solar flare prediction model. It is found that the performance of the short-term solar flare prediction model based on the multiresolution predictors is greatly improved.« less
Visual feature binding in younger and older adults: encoding and suffix interference effects.

PubMed

Brown, Louise A; Niven, Elaine H; Logie, Robert H; Rhodes, Stephen; Allen, Richard J

2017-02-01

Three experiments investigated younger (18-25 yrs) and older (70-88 yrs) adults' temporary memory for colour-shape combinations (binding). We focused upon estimating the magnitude of the binding cost for each age group across encoding time (Experiment 1; 900/1500 ms), presentation format (Experiment 2; simultaneous/sequential), and interference (Experiment 3; control/suffix) conditions. In Experiment 1, encoding time did not differentially influence binding in the two age groups. In Experiment 2, younger adults exhibited poorer binding performance with sequential relative to simultaneous presentation, and serial position analyses highlighted a particular age-related difficulty remembering the middle item of a series (for all memory conditions). Experiments 1-3 demonstrated small to medium binding effect sizes in older adults across all encoding conditions, with binding less accurate than shape memory. However, younger adults also displayed negative effects of binding (small to large) in two of the experiments. Even when older adults exhibited a greater suffix interference effect in Experiment 3, this was for all memory types, not just binding. We therefore conclude that there is no consistent evidence for a visual binding deficit in healthy older adults. This relative preservation contrasts with the specific and substantial deficits in visual feature binding found in several recent studies of Alzheimer's disease.
Ion Movements in Shock in Relation to Survival and Its Modifications

DTIC Science & Technology

1985-01-01

from normal to irreversibly injured are initiated and modified by primary and/or secondary effects of ion redistributions taking place between the...reactions to injury by the shock state has become possible. However, spcclflc aspects concerning effects at the cellular and subcellular levels need...to be further clarified. Therefore, the aim of this study was to characterize the cellular and subcellular effects of hemorrhagic and bacteremic shock

Subcellular Responses to Narrowband and Wideband Radiofrequency Radiation

DTIC Science & Technology

2008-02-15

nanosecond pulses. This release is most likely also due to subcellular electromanipulation. Platelets are rich in alpha granule growth factors (i.e. platelet ... platelets (for advanced wound healing), and e) has opened the possibility of using antennas with intense electrical pulses in the subnanosecond range...development. The results of this study show that an increase in plasma membrane conductivity occurs within a few nanoseconds (less than the temporal
Distribution of physostigmine and metabolites in brain subcellular fractions of the rat

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

King, B.F.; Somani, S.M.

1987-10-26

The distribution of /sup 3/H-physostigmine (Phy) has been studied in the rat brain subcellular fractions at various time intervals following i.v. injection. /sup 3/H-Phy or its metabolites rapidly accumulate into the cytoplasm of cells and penetrates the intracellular compartments. Kinetic studies of the subcellular distribution of radioactivity (RA) per gm of rat brain following i.v. injection of /sup 3/H-Phy show peak concentrations at 30 min in all subcellular fractions with the exception of mitochondria. In the mitochondrial fraction the RA levels continue to rise from 4682 +/- 875 DPM/gm at 5 min to 27,474 +/- 2825 DPM/gm at 60 minmore » (P < .05). The cytosol contains the highest RA: 223,341 +/- 21,044 DPM/gm at 30 min which declined to 53,475 +/- 3756 DPM/gm at 60 min. RA in synaptosome, microsomes and myelin increases from 5 to 30 min, and declines at 60 min. In vitro studies did not show a greater uptake of RA by the mitochondrial or synaptosomal fractions. The finding of relatively high concentrations of RA in the mitochondrial fraction at 60 min increases the likelihood that Phy or its metabolites could interfere with the physiological function of the organelle. 21 references, 1 figure, 2 tables.« less
Studies on the turnover and subcellular localization of membrane gangliosides in cultured neuroblastoma cells

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

Clarke, J.T.; Cook, H.W.; Spence, M.W.

1985-03-01

To compare the subcellular distribution of endogenously synthesized and exogenous gangliosides, cultured murine neuroblastoma cells (N1E-115) were incubated in suspension for 22 h in the presence of D-(1-/sup 3/H)galactose or (/sup 3/H)GM1 ganglioside, transferred to culture medium containing no radioisotope for periods of up to 72 hr, and then subjected to subcellular fractionation and analysis of lipid-sialic acid and radiolabeled ganglioside levels. The results indicated that GM2 and GM3 were the principal gangliosides in the cells with only traces of GM1 and small amounts of disialogangliosides present. About 50% of the endogenously synthesized radiolabelled ganglioside in the four major subcellularmore » membrane fractions studied was recovered from plasma membrane and only 10-15% from the crude mitochondrial membrane fraction. In contrast, 45% of the exogenous (/sup 3/H)GM1 taken up into the same subcellular membrane fractions was recovered from the crude mitochondrial fraction; less than 15% was localized in the plasma membrane fraction. The results are similar to those obtained from previously reported studies on membrane phospholipid turnover. They suggest that exogenous GM1 ganglioside, like exogenous phosphatidylcholine, does not intermix freely with any quantitatively major pool of endogenous membrane lipid.« less
Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis

NASA Astrophysics Data System (ADS)

Lan, Tian; Cheng, Kai; Ren, Tina; Arce, Stephen Hugo; Tseng, Yiider

2016-09-01

Cell migration is an essential process in organism development and physiological maintenance. Although current methods permit accurate comparisons of the effects of molecular manipulations and drug applications on cell motility, effects of alterations in subcellular activities on motility cannot be fully elucidated from those methods. Here, we develop a strategy termed cell-nuclear (CN) correlation to parameterize represented dynamic subcellular activities and to quantify their contributions in mesenchymal-like migration. Based on the biophysical meaning of the CN correlation, we propose a cell migration potential index (CMPI) to measure cell motility. When the effectiveness of CMPI was evaluated with respect to one of the most popular cell migration analysis methods, Persistent Random Walk, we found that the cell motility estimates among six cell lines used in this study were highly consistent between these two approaches. Further evaluations indicated that CMPI can be determined using a shorter time period and smaller cell sample size, and it possesses excellent reliability and applicability, even in the presence of a wide range of noise, as might be generated from individual imaging acquisition systems. The novel approach outlined here introduces a robust strategy through an analysis of subcellular locomotion activities for single cell migration assessment.
Single-cell analysis of pyroptosis dynamics reveals conserved GSDMD-mediated subcellular events that precede plasma membrane rupture.

PubMed

de Vasconcelos, Nathalia M; Van Opdenbosch, Nina; Van Gorp, Hanne; Parthoens, Eef; Lamkanfi, Mohamed

2018-04-17

Pyroptosis is rapidly emerging as a mechanism of anti-microbial host defense, and of extracellular release of the inflammasome-dependent cytokines interleukin (IL)-1β and IL-18, which contributes to autoinflammatory pathology. Caspases 1, 4, 5 and 11 trigger this regulated form of necrosis by cleaving the pyroptosis effector gasdermin D (GSDMD), causing its pore-forming amino-terminal domain to oligomerize and perforate the plasma membrane. However, the subcellular events that precede pyroptotic cell lysis are ill defined. In this study, we triggered primary macrophages to undergo pyroptosis from three inflammasome types and recorded their dynamics and morphology using high-resolution live-cell spinning disk confocal laser microscopy. Based on quantitative analysis of single-cell subcellular events, we propose a model of pyroptotic cell disintegration that is initiated by opening of GSDMD-dependent ion channels or pores that are more restrictive than recently proposed GSDMD pores, followed by osmotic cell swelling, commitment of mitochondria and other membrane-bound organelles prior to sudden rupture of the plasma membrane and full permeability to intracellular proteins. This study provides a dynamic framework for understanding cellular changes that occur during pyroptosis, and charts a chronological sequence of GSDMD-mediated subcellular events that define pyroptotic cell death at the single-cell level.
The UL24 protein of herpes simplex virus 1 affects the sub-cellular distribution of viral glycoproteins involved in fusion

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

Ben Abdeljelil, Nawel; Rochette, Pierre-Alexandre; Pearson, Angela, E-mail: angela.pearson@iaf.inrs.ca

2013-09-15

Mutations in UL24 of herpes simplex virus type 1 can lead to a syncytial phenotype. We hypothesized that UL24 affects the sub-cellular distribution of viral glycoproteins involved in fusion. In non-immortalized human foreskin fibroblasts (HFFs) we detected viral glycoproteins B (gB), gD, gH and gL present in extended blotches throughout the cytoplasm with limited nuclear membrane staining; however, in HFFs infected with a UL24-deficient virus (UL24X), staining for the viral glycoproteins appeared as long, thin streaks running across the cell. Interestingly, there was a decrease in co-localized staining of gB and gD with F-actin at late times in UL24X-infected HFFs.more » Treatment with chemical agents that perturbed the actin cytoskeleton hindered the formation of UL24X-induced syncytia in these cells. These data support a model whereby the UL24 syncytial phenotype results from a mislocalization of viral glycoproteins late in infection. - Highlights: • UL24 affects the sub-cellular distribution of viral glycoproteins required for fusion. • Sub-cellular distribution of viral glycoproteins varies in cell-type dependent manner. • Drugs targeting actin microfilaments affect formation of UL24-related syncytia in HFFs.« less
Analysis of the subcellular localization of the human histone methyltransferase SETDB1

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

Tachibana, Keisuke, E-mail: nya@phs.osaka-u.ac.jp; Gotoh, Eiko; Kawamata, Natsuko

2015-10-02

SET domain, bifurcated 1 (SETDB1) is a histone methyltransferase that methylates lysine 9 on histone H3. Although it is important to know the localization of proteins to elucidate their physiological function, little is known of the subcellular localization of human SETDB1. In the present study, to investigate the subcellular localization of hSETDB1, we established a human cell line constitutively expressing enhanced green fluorescent protein fused to hSETDB1. We then generated a monoclonal antibody against the hSETDB1 protein. Expression of both exogenous and endogenous hSETDB1 was observed mainly in the cytoplasm of various human cell lines. Combined treatment with the nuclearmore » export inhibitor leptomycin B and the proteasome inhibitor MG132 led to the accumulation of hSETDB1 in the nucleus. These findings suggest that hSETDB1, localized in the nucleus, might undergo degradation by the proteasome and be exported to the cytosol, resulting in its detection mainly in the cytosol. - Highlights: • Endogenous human SETDB1 was localized mainly in the cytoplasm. • Combined treatment with LMB and MG132 led to accumulation of human SETDB1 in the nucleus. • HeLa cells expressing EFGP-hSETDB1 are useful for subcellular localization analyses.« less
Investigation of the subcellular architecture of L7 neurons of Aplysia californica using magnetic resonance microscopy (MRM) at 7.8 microns.

PubMed

Lee, Choong H; Flint, Jeremy J; Hansen, Brian; Blackband, Stephen J

2015-06-10

Magnetic resonance microscopy (MRM) is a non-invasive diagnostic tool which is well-suited to directly resolve cellular structures in ex vivo and in vitro tissues without use of exogenous contrast agents. Recent advances in its capability to visualize mammalian cellular structure in intact tissues have reinvigorated analytical interest in aquatic cell models whose previous findings warrant up-to-date validation of subcellular components. Even if the sensitivity of MRM is less than other microscopic technologies, its strength lies in that it relies on the same image contrast mechanisms as clinical MRI which make it a unique tool for improving our ability to interpret human diagnostic imaging through high resolution studies of well-controlled biological model systems. Here, we investigate the subcellular MR signal characteristics of isolated cells of Aplysia californica at an in-plane resolution of 7.8 μm. In addition, direct correlation and positive identification of subcellular architecture in the cells is achieved through well-established histology. We hope this methodology will serve as the groundwork for studying pathophysiological changes through perturbation studies and allow for development of disease-specific cellular modeling tools. Such an approach promises to reveal the MR contrast changes underlying cellular mechanisms in various human diseases, for example in ischemic stroke.
Delivery of drugs to intracellular organelles using drug delivery systems: Analysis of research trends and targeting efficiencies.

PubMed

Maity, Amit Ranjan; Stepensky, David

2015-12-30

Targeting of drug delivery systems (DDSs) to specific intracellular organelles (i.e., subcellular targeting) has been investigated in numerous publications, but targeting efficiency of these systems is seldom reported. We searched scientific publications in the subcellular DDS targeting field and analyzed targeting efficiency and major formulation parameters that affect it. We identified 77 scientific publications that matched the search criteria. In the majority of these studies nanoparticle-based DDSs were applied, while liposomes, quantum dots and conjugates were used less frequently. The nucleus was the most common intracellular target, followed by mitochondrion, endoplasmic reticulum and Golgi apparatus. In 65% of the publications, DDSs surface was decorated with specific targeting residues, but the efficiency of this surface decoration was not analyzed in predominant majority of the studies. Moreover, only 23% of the analyzed publications contained quantitative data on DDSs subcellular targeting efficiency, while the majority of publications reported qualitative results only. From the analysis of publications in the subcellular targeting field, it appears that insufficient efforts are devoted to quantitative analysis of the major formulation parameters and of the DDSs' intracellular fate. Based on these findings, we provide recommendations for future studies in the field of organelle-specific drug delivery and targeting. Copyright © 2015 Elsevier B.V. All rights reserved.
Distribution of Single-Wall Carbon Nanotubes in the Xenopus laevis Embryo after Microinjection

PubMed Central

Holt, Brian D.; Shawky, Joseph H.; Dahl, Kris Noel; Davidson, Lance A.; Islam, Mohammad F.

2016-01-01

Single-wall carbon nanotubes (SWCNTs) are advanced materials with the potential for a myriad of diverse applications, including biological technologies and largescale usage with the potential for environmental impacts. SWCNTs have been exposed to developing organisms to determine their effects on embryogenesis, and results have been inconsistent arising, in part, from differing material quality, dispersion status, material size, impurity from catalysts, and stability. For this study, we utilized highly purified SWCNT samples with short, uniform lengths (145 ± 17 nm) well dispersed in solution. To test high exposure doses, we microinjected > 500 μg mL-1 SWCNT concentrations into the well-established embryogenesis model, Xenopus laevis, and determined embryo compatibility and sub-cellular localization during development. SWCNTs localized within cellular progeny of the microinjected cells, but heterogeneously distributed throughout the target-injected tissue. Co-registering unique Raman spectral intensity of SWCNTs with images of fluorescently labelled sub-cellular compartments demonstrated that even at the regions of highest SWCNT concentration, there were no gross alterations to sub-cellular microstructures, including filamentous actin, endoplasmic reticulum and vesicles. Furthermore, SWCNTs did not aggregate or localize to the perinuclear sub-cellular region. Combined, these results suggest that purified and dispersed SWCNTs are not toxic to X. laevis animal cap ectoderm and may be suitable candidate materials for biological applications. PMID:26510384
Influences of calcium silicate on chemical forms and subcellular distribution of cadmium in Amaranthus hypochondriacus L.

NASA Astrophysics Data System (ADS)

Lu, Huanping; Li, Zhian; Wu, Jingtao; Shen, Yong; Li, Yingwen; Zou, Bi; Tang, Yetao; Zhuang, Ping

2017-01-01

A pot experiment was conducted to investigate the effects of calcium silicate (CS) on the subcellular distribution and chemical forms of cadmium (Cd) in grain amaranths (Amaranthus hypochondriacus L. Cv. ‘K112’) grown in a Cd contaminated soil. Results showed that the dry weight and the photosynthetic pigments contents in grain amaranths increased significantly with the increasing doses of CS treatments, with the highest value found for the treatment of CS3 (1.65 g/kg). Compared with the control, application of CS4 (3.31 g/kg) significantly reduced Cd concentrations in the roots, stems and leaves of grain amaranths by 68%, 87% and 89%, respectively. At subcellular level, CS treatment resulted in redistribution of Cd, higher percentages of Cd in the chloroplast and soluble fractions in leaves of grain amaranths were found, while lower proportions of Cd were located at the cell wall of the leaves. The application of CS enhanced the proportions of pectate and protein integrated forms of Cd and decreased the percentages of water soluble Cd potentially associated with toxicity in grain amaranths. Changes of free Cd ions into inactive forms sequestered in subcellular compartments may indicate an important mechanism of CS for alleviating Cd toxicity and accumulation in plants.
Reinstatement after human feature-positive discrimination learning.

PubMed

Franssen, Mathijs; Claes, Nathalie; Vervliet, Bram; Beckers, Tom; Hermans, Dirk; Baeyens, Frank

2017-04-01

In two experiments, using an online conditioned suppression task, we investigated the possibility of reinstatement of extinguished feature-target compound presentations after sequential feature-positive discrimination training in humans. Furthermore, given a hierarchical account of Pavlovian modulation (e.g., Bonardi, 1998; Bonardi and Jennings, 2009), we predicted A-US reinstatement to be stronger than US-only reinstatement. In Experiment 1, participants learned a sequential feature-positive discrimination (X→A + |A - ), which was subsequently extinguished (X→A - ). During the following reinstatement phase, group US-only received US-only presentations (not signalled), group A-US received A-US presentations, and the Control group received exposure to the context, but no CSs or USs, for an equal amount of time. Reinstatement of differential X→A/A responding was observed in the US-only group but not in the Control or A-US groups. Although differential X→A/A responding was not significant in group A-US, responding to the X→A compound was significantly stronger compared to that in group US-only. Hence, it could be the case the group A-US showed stronger reinstatement, but that differential responding was abolished due to excitation gained by A. Experiment 2 was set up to circumvent the acquired excitation of A by testing transfer of the feature after A-US reinstatement to a different target, B. Participants acquired two discriminations, X→A/A and Y→B/B, of which X→A was then extinguished. Subsequently, group A-US received reinforced presentations of A during a reinstatement phase while group Control received exposure to the context. Final testing of the novel X→B compound was hypothesized to show higher responding in group A-US than in group Control, but findings of this approach were limited due to acquired equivalence and/or perceptual factors causing a secondary extinction effect. We conclude to have obtained clear evidence in favour of reinstatement of differential responding after human Feature-Positive discrimination training and subsequent compound extinction, but no evidence in favour of A-US presentations being a stronger trigger for reinstatement than are US-only presentations. Copyright © 2017 Elsevier B.V. All rights reserved.
Decoding of finger trajectory from ECoG using deep learning.

PubMed

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.
Decoding of finger trajectory from ECoG using deep learning

NASA Astrophysics Data System (ADS)

Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek

2018-06-01

Objective. Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. Approach. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. Main results. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. Significance. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the state transitions. The discussed network eliminated the need to separately train the model at each step in the decoding pipeline. The whole system can be jointly optimized using stochastic gradient descent and is capable of online learning.
Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

PubMed

Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

2013-01-01

The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumor grading.
Associative cueing of attention through implicit feature-location binding.

PubMed

Girardi, Giovanna; Nico, Daniele

2017-09-01

In order to assess associative learning between two task-irrelevant features in cueing spatial attention, we devised a task in which participants have to make an identity comparison between two sequential visual stimuli. Unbeknownst to them, location of the second stimulus could be predicted by the colour of the first or a concurrent sound. Albeit unnecessary to perform the identity-matching judgment the predictive features thus provided an arbitrary association favouring the spatial anticipation of the second stimulus. A significant advantage was found with faster responses at predicted compared to non-predicted locations. Results clearly demonstrated an associative cueing of attention via a second-order arbitrary feature/location association but with a substantial discrepancy depending on the sensory modality of the predictive feature. With colour as predictive feature, significant advantages emerged only after the completion of three blocks of trials. On the contrary, sound affected responses from the first block of trials and significant advantages were manifest from the beginning of the second. The possible mechanisms underlying the associative cueing of attention in both conditions are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

PubMed

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.
Sequential visibility-graph motifs

NASA Astrophysics Data System (ADS)

Iacovacci, Jacopo; Lacasa, Lucas

2016-04-01

Visibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge between nonlinear dynamics and network science. In this work we introduce and study the concept of sequential visibility-graph motifs, smaller substructures of n consecutive nodes that appear with characteristic frequencies. We develop a theory to compute in an exact way the motif profiles associated with general classes of deterministic and stochastic dynamics. We find that this simple property is indeed a highly informative and computationally efficient feature capable of distinguishing among different dynamics and robust against noise contamination. We finally confirm that it can be used in practice to perform unsupervised learning, by extracting motif profiles from experimental heart-rate series and being able, accordingly, to disentangle meditative from other relaxation states. Applications of this general theory include the automatic classification and description of physical, biological, and financial time series.
Children's sequential information search is sensitive to environmental probabilities.

PubMed

Nelson, Jonathan D; Divjak, Bojana; Gudmundsdottir, Gudny; Martignon, Laura F; Meder, Björn

2014-01-01

We investigated 4th-grade children's search strategies on sequential search tasks in which the goal is to identify an unknown target object by asking yes-no questions about its features. We used exhaustive search to identify the most efficient question strategies and evaluated the usefulness of children's questions accordingly. Results show that children have good intuitions regarding questions' usefulness and search adaptively, relative to the statistical structure of the task environment. Search was especially efficient in a task environment that was representative of real-world experiences. This suggests that children may use their knowledge of real-world environmental statistics to guide their search behavior. We also compared different related search tasks. We found positive transfer effects from first doing a number search task on a later person search task. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.
Simultaneous activation of parallel sensory pathways promotes a grooming sequence in Drosophila

PubMed Central

Hampel, Stefanie; McKellar, Claire E

2017-01-01

A central model that describes how behavioral sequences are produced features a neural architecture that readies different movements simultaneously, and a mechanism where prioritized suppression between the movements determines their sequential performance. We previously described a model whereby suppression drives a Drosophila grooming sequence that is induced by simultaneous activation of different sensory pathways that each elicit a distinct movement (Seeds et al., 2014). Here, we confirm this model using transgenic expression to identify and optogenetically activate sensory neurons that elicit specific grooming movements. Simultaneous activation of different sensory pathways elicits a grooming sequence that resembles the naturally induced sequence. Moreover, the sequence proceeds after the sensory excitation is terminated, indicating that a persistent trace of this excitation induces the next grooming movement once the previous one is performed. This reveals a mechanism whereby parallel sensory inputs can be integrated and stored to elicit a delayed and sequential grooming response. PMID:28887878

Optical flip-flops in a polarization-encoded optical shadow-casting scheme.

PubMed

Rizvi, R A; Zubairy, M S

1994-06-10

We propose a novel scheme that optically implements various types of binary sequential logic elements. This is based on a polarization-encoded optical shadow-casting system. The proposed system architecture is capable of implementing synchronous as well as asynchronous sequential circuits owing to the inherent structural flexibility of optical shadow casting. By employing the proposed system, we present the design and implementation schemes of a J-K flip-flop and clocked R-S and D latches. The main feature of these flip-flops is that the propagation of the signal from the input plane to the output (i.e., processing) and from the output plane to the source plane (i.e., feedback) is all optical. Consequently the efficiency of these elements in terms of speed is increased. The only electronic part in the system is the detection of the outputs and the switching of the source plane.
Prosody and alignment: a sequential perspective

NASA Astrophysics Data System (ADS)

Szczepek Reed, Beatrice

2010-12-01

In their analysis of a corpus of classroom interactions in an inner city high school, Roth and Tobin describe how teachers and students accomplish interactional alignment by prosodically matching each other's turns. Prosodic matching, and specific prosodic patterns are interpreted as signs of, and contributions to successful interactional outcomes and positive emotions. Lack of prosodic matching, and other specific prosodic patterns are interpreted as features of unsuccessful interactions, and negative emotions. This forum focuses on the article's analysis of the relation between interpersonal alignment, emotion and prosody. It argues that prosodic matching, and other prosodic linking practices, play a primarily sequential role, i.e. one that displays the way in which participants place and design their turns in relation to other participants' turns. Prosodic matching, rather than being a conversational action in itself, is argued to be an interactional practice (Schegloff 1997), which is not always employed for the accomplishment of `positive', or aligning actions.
Energy storage and deposition in a solar flare

NASA Technical Reports Server (NTRS)

Vorpahl, J. A.

1976-01-01

X-ray pictures of a solar flare taken with the S-056 X-ray telescope aboard Skylab are interpreted in terms of flare energy deposition and storage. The close similarity between calculated magnetic-field lines and the overall structure of the X-ray core is shown to suggest that the flare occurred in an entire arcade of loops. It is found that different X-ray features brightened sequentially as the flare evolved, indicating that some triggering disturbance moved from one side to the other in the flare core. A propagation velocity of 180 to 280 km/s is computed, and it is proposed that the geometry of the loop arcade strongly influenced the propagation of the triggering disturbance as well as the storage and site of the subsequent energy deposition. Some possible physical causes for the sequential X-ray brightening are examined, and a magnetosonic wave is suggested as the triggering disturbance. 'Correct' conditions for energy release are considered
Sequential data access with Oracle and Hadoop: a performance comparison

NASA Astrophysics Data System (ADS)

Baranowski, Zbigniew; Canali, Luca; Grancher, Eric

2014-06-01

The Hadoop framework has proven to be an effective and popular approach for dealing with "Big Data" and, thanks to its scaling ability and optimised storage access, Hadoop Distributed File System-based projects such as MapReduce or HBase are seen as candidates to replace traditional relational database management systems whenever scalable speed of data processing is a priority. But do these projects deliver in practice? Does migrating to Hadoop's "shared nothing" architecture really improve data access throughput? And, if so, at what cost? Authors answer these questions-addressing cost/performance as well as raw performance- based on a performance comparison between an Oracle-based relational database and Hadoop's distributed solutions like MapReduce or HBase for sequential data access. A key feature of our approach is the use of an unbiased data model as certain data models can significantly favour one of the technologies tested.
New insights into globoids of protein storage vacuoles in wheat aleurone using synchrotron soft X-ray microscopy

PubMed Central

Regvar, Marjana; Eichert, Diane; Kaulich, Burkhard; Gianoncelli, Alessandra; Pongrac, Paula; Vogel-Mikuš, Katarina; Kreft, Ivan

2011-01-01

Mature developed seeds are physiologically and biochemically committed to store nutrients, principally as starch, protein, oils, and minerals. The composition and distribution of elements inside the aleurone cell layer reflect their biogenesis, structural characteristics, and physiological functions. It is therefore of primary importance to understand the mechanisms underlying metal ion accumulation, distribution, storage, and bioavailability in aleurone subcellular organelles for seed fortification purposes. Synchrotron radiation soft X-ray full-field imaging mode (FFIM) and low-energy X-ray fluorescence (LEXRF) spectromicroscopy were applied to characterize major structural features and the subcellular distribution of physiologically important elements (Zn, Fe, Na, Mg, Al, Si, and P). These direct imaging methods reveal the accumulation patterns between the apoplast and symplast, and highlight the importance of globoids with phytic acid mineral salts and walls as preferential storage structures. C, N, and O chemical topographies are directly linked to the structural backbone of plant substructures. Zn, Fe, Na, Mg, Al, and P were linked to globoid structures within protein storage vacuoles with variable levels of co-localization. Si distribution was atypical, being contained in the aleurone apoplast and symplast, supporting a physiological role for Si in addition to its structural function. These results reveal that the immobilization of metals within the observed endomembrane structures presents a structural and functional barrier and affects bioavailability. The combination of high spatial and chemical X-ray microscopy techniques highlights how in situ analysis can yield new insights into the complexity of the wheat aleurone layer, whose precise biochemical composition, morphology, and structural characteristics are still not unequivocally resolved. PMID:21447756
Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins

PubMed Central

Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

2013-01-01

Purpose To develop a robust tool for quantitative in situ pathology that allows visualization of heterogeneous tissue morphology and segmentation and quantification of image features. Materials and Methods Tissue excised from a genetically engineered mouse model of sarcoma was imaged using a subcellular resolution microendoscope after topical application of a fluorescent anatomical contrast agent: acriflavine. An algorithm based on sparse component analysis (SCA) and the circle transform (CT) was developed for image segmentation and quantification of distinct tissue types. The accuracy of our approach was quantified through simulations of tumor and muscle images. Specifically, tumor, muscle, and tumor+muscle tissue images were simulated because these tissue types were most commonly observed in sarcoma margins. Simulations were based on tissue characteristics observed in pathology slides. The potential clinical utility of our approach was evaluated by imaging excised margins and the tumor bed in a cohort of mice after surgical resection of sarcoma. Results Simulation experiments revealed that SCA+CT achieved the lowest errors for larger nuclear sizes and for higher contrast ratios (nuclei intensity/background intensity). For imaging of tumor margins, SCA+CT effectively isolated nuclei from tumor, muscle, adipose, and tumor+muscle tissue types. Differences in density were correctly identified with SCA+CT in a cohort of ex vivo and in vivo images, thus illustrating the diagnostic potential of our approach. Conclusion The combination of a subcellular-resolution microendoscope, acriflavine staining, and SCA+CT can be used to accurately isolate nuclei and quantify their density in anatomical images of heterogeneous tissue. PMID:23824589
Nipah Virus V Protein Evades Alpha and Gamma Interferons by Preventing STAT1 and STAT2 Activation and Nuclear Accumulation

PubMed Central

Rodriguez, Jason J.; Parisien, Jean-Patrick; Horvath, Curt M.

2002-01-01

Characterization of recent outbreaks of fatal encephalitis in southeast Asia identified the causative agent to be a previously unrecognized enveloped negative-strand RNA virus of the Paramyxoviridae family, Nipah virus. One feature linking Nipah virus to this family is a conserved cysteine-rich domain that is the hallmark of paramyxovirus V proteins. The V proteins of other paramyxovirus species have been linked with evasion of host cell interferon (IFN) signal transduction and subsequent antiviral responses by inducing proteasomal degradation of the IFN-responsive transcription factors, STAT1 or STAT2. Here we demonstrate that Nipah virus V protein escapes IFN by a distinct mechanism involving direct inhibition of STAT protein function. Nipah virus V protein differs from other paramyxovirus V proteins in its subcellular distribution but not in its ability to inhibit cellular IFN responses. Nipah virus V protein does not induce STAT degradation but instead inhibits IFN responses by forming high-molecular-weight complexes with both STAT1 and STAT2. We demonstrate that Nipah virus V protein accumulates in the cytoplasm by a Crm1-dependent mechanism, alters the STAT protein subcellular distribution in the steady state, and prevents IFN-stimulated STAT redistribution. Consistent with the formation of complexes, STAT protein tyrosine phosphorylation is inhibited in cells expressing the Nipah virus V protein. As a result, Nipah virus V protein efficiently prevents STAT1 and STAT2 nuclear translocation in response to IFN, inhibiting cellular responses to both IFN-α and IFN-γ. PMID:12388709
Repairing oxidized proteins in the bacterial envelope using respiratory chain electrons

PubMed Central

Henry, Camille; Agrebi, Rym; Vergnes, Alexandra; Oheix, Emmanuel; Bos, Julia; Leverrier, Pauline; Espinosa, Leon; Szewczyk, Joanna; Vertommen, Didier; Iranzo, Olga; Collet, Jean-François; Barras, Frédéric

2015-01-01

The reactive species of oxygen (ROS) and chlorine (RCS) damage cellular components, potentially leading to cell death. In proteins, the sulfur-containing amino acid methionine (Met) is converted to methionine sulfoxide (Met-O), which can cause a loss of biological activity. To rescue proteins with Met-O residues, living cells express methionine sulfoxide reductases (Msrs) in most subcellular compartments, including the cytosol, mitochondria and chloroplasts 1-3. Here, we report the identification of an enzymatic system, MsrPQ, repairing Met-O containing proteins in the bacterial cell envelope, a compartment particularly exposed to the ROS and RCS generated by the host defense mechanisms. MsrP, a molybdo-enzyme, and MsrQ, a heme-binding membrane protein, are widely conserved throughout Gram-negative bacteria, including major human pathogens. MsrPQ synthesis is induced by hypochlorous acid (HOCl), a powerful antimicrobial released by neutrophils. Consistently, MsrPQ is essential for the maintenance of envelope integrity under bleach stress, rescuing a wide series of structurally unrelated periplasmic proteins from Met oxidation, including the primary periplasmic chaperone SurA. For this activity, MsrPQ uses electrons from the respiratory chain, which represents a novel mechanism to import reducing equivalents into the bacterial cell envelope. A remarkable feature of MsrPQ is its capacity to reduce both R- and S- diastereoisomers of Met-O, making this oxidoreductase complex functionally different from previously identified Msrs. The discovery that a large class of bacteria contain a single, non-stereospecific enzymatic complex fully protecting Met residues from oxidation should prompt search for similar systems in eukaryotic subcellular oxidizing compartments, including the endoplasmic reticulum (ER). PMID:26641313
Repairing oxidized proteins in the bacterial envelope using respiratory chain electrons.

PubMed

Gennaris, Alexandra; Ezraty, Benjamin; Henry, Camille; Agrebi, Rym; Vergnes, Alexandra; Oheix, Emmanuel; Bos, Julia; Leverrier, Pauline; Espinosa, Leon; Szewczyk, Joanna; Vertommen, Didier; Iranzo, Olga; Collet, Jean-François; Barras, Frédéric

2015-12-17

The reactive species of oxygen and chlorine damage cellular components, potentially leading to cell death. In proteins, the sulfur-containing amino acid methionine is converted to methionine sulfoxide, which can cause a loss of biological activity. To rescue proteins with methionine sulfoxide residues, living cells express methionine sulfoxide reductases (Msrs) in most subcellular compartments, including the cytosol, mitochondria and chloroplasts. Here we report the identification of an enzymatic system, MsrPQ, repairing proteins containing methionine sulfoxide in the bacterial cell envelope, a compartment particularly exposed to the reactive species of oxygen and chlorine generated by the host defence mechanisms. MsrP, a molybdo-enzyme, and MsrQ, a haem-binding membrane protein, are widely conserved throughout Gram-negative bacteria, including major human pathogens. MsrPQ synthesis is induced by hypochlorous acid, a powerful antimicrobial released by neutrophils. Consistently, MsrPQ is essential for the maintenance of envelope integrity under bleach stress, rescuing a wide series of structurally unrelated periplasmic proteins from methionine oxidation, including the primary periplasmic chaperone SurA. For this activity, MsrPQ uses electrons from the respiratory chain, which represents a novel mechanism to import reducing equivalents into the bacterial cell envelope. A remarkable feature of MsrPQ is its capacity to reduce both rectus (R-) and sinister (S-) diastereoisomers of methionine sulfoxide, making this oxidoreductase complex functionally different from previously identified Msrs. The discovery that a large class of bacteria contain a single, non-stereospecific enzymatic complex fully protecting methionine residues from oxidation should prompt a search for similar systems in eukaryotic subcellular oxidizing compartments, including the endoplasmic reticulum.
Quantitative Segmentation of Fluorescence Microscopy Images of Heterogeneous Tissue: Application to the Detection of Residual Disease in Tumor Margins.

PubMed

Mueller, Jenna L; Harmany, Zachary T; Mito, Jeffrey K; Kennedy, Stephanie A; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G; Willett, Rebecca M; Brown, J Quincy; Ramanujam, Nimmi

2013-01-01

To develop a robust tool for quantitative in situ pathology that allows visualization of heterogeneous tissue morphology and segmentation and quantification of image features. TISSUE EXCISED FROM A GENETICALLY ENGINEERED MOUSE MODEL OF SARCOMA WAS IMAGED USING A SUBCELLULAR RESOLUTION MICROENDOSCOPE AFTER TOPICAL APPLICATION OF A FLUORESCENT ANATOMICAL CONTRAST AGENT: acriflavine. An algorithm based on sparse component analysis (SCA) and the circle transform (CT) was developed for image segmentation and quantification of distinct tissue types. The accuracy of our approach was quantified through simulations of tumor and muscle images. Specifically, tumor, muscle, and tumor+muscle tissue images were simulated because these tissue types were most commonly observed in sarcoma margins. Simulations were based on tissue characteristics observed in pathology slides. The potential clinical utility of our approach was evaluated by imaging excised margins and the tumor bed in a cohort of mice after surgical resection of sarcoma. Simulation experiments revealed that SCA+CT achieved the lowest errors for larger nuclear sizes and for higher contrast ratios (nuclei intensity/background intensity). For imaging of tumor margins, SCA+CT effectively isolated nuclei from tumor, muscle, adipose, and tumor+muscle tissue types. Differences in density were correctly identified with SCA+CT in a cohort of ex vivo and in vivo images, thus illustrating the diagnostic potential of our approach. The combination of a subcellular-resolution microendoscope, acriflavine staining, and SCA+CT can be used to accurately isolate nuclei and quantify their density in anatomical images of heterogeneous tissue.
Biochemical localization of a protein involved in Gluconacetobacter hansenii cellulose synthesis

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

Iyer, Prashanti R; Catchmark, Jeffrey M; Brown, Nicole Robitaille

2011-02-08

Using subcellular fractionation and Western blot methods, we have shown that AcsD, one of the proteins encoded by the Acetobacter cellulose synthase (acs) operon, is localized in the periplasmic region of the cell. AcsD protein was heterologously expressed in Escherichia coli and purified using histidine tag affinity methods. The purified protein was used to obtain rabbit polyclonal antibodies. The purity of the subcellular fractions was assessed by marker enzyme assays.
A meta-analysis of response-time tests of the sequential two-systems model of moral judgment.

PubMed

Baron, Jonathan; Gürçay, Burcu

2017-05-01

The (generalized) sequential two-system ("default interventionist") model of utilitarian moral judgment predicts that utilitarian responses often arise from a system-two correction of system-one deontological intuitions. Response-time (RT) results that seem to support this model are usually explained by the fact that low-probability responses have longer RTs. Following earlier results, we predicted response probability from each subject's tendency to make utilitarian responses (A, "Ability") and each dilemma's tendency to elicit deontological responses (D, "Difficulty"), estimated from a Rasch model. At the point where A = D, the two responses are equally likely, so probability effects cannot account for any RT differences between them. The sequential two-system model still predicts that many of the utilitarian responses made at this point will result from system-two corrections of system-one intuitions, hence should take longer. However, when A = D, RT for the two responses was the same, contradicting the sequential model. Here we report a meta-analysis of 26 data sets, which replicated the earlier results of no RT difference overall at the point where A = D. The data sets used three different kinds of moral judgment items, and the RT equality at the point where A = D held for all three. In addition, we found that RT increased with A-D. This result holds for subjects (characterized by Ability) but not for items (characterized by Difficulty). We explain the main features of this unanticipated effect, and of the main results, with a drift-diffusion model.
HNCA-TOCSY-CANH experiments with alternate 13C-12C labeling: a set of 3D experiment with unique supra-sequential information for mainchain resonance assignment

PubMed Central

Takeuchi, Koh; Gal, Maayan; Takahashi, Hideo; Shimada, Ichio

2011-01-01

Described here is a set of three-dimensional (3D) NMR experiments that rely on CACA-TOCSY magnetization transfer via the weak 3JCαCα coupling. These pulse sequences, which resemble recently described 13C detected CACA-TOCSY (Takeuchi et al. 2010) experiments, are recorded in 1H2O, and use 1H excitation and detection. These experiments require alternate 13C-12C labeling together with perdeuteration, which allows utilizing the small 3JCαCα scalar coupling that is otherwise masked by the stronger 1JCC couplings in uniformly 13C labeled samples. These new experiments provide a unique assignment ladder-mark that yields bidirectional supra-sequential information and can readily straddle proline residues. Unlike the conventional HNCA experiment, which contains only sequential information to the 13Cα of the preceding residue, the 3D hnCA-TOCSY-caNH experiment can yield sequential correlations to alpha carbons in positions i−1, i + 1 and i−2. Furthermore, the 3D hNca-TOCSY-caNH and Hnca-TOC-SY-caNH experiments, which share the same magnetization pathway but use a different chemical shift encoding, directly couple the 15N-1H spin pair of residue i to adjacent amide protons and nitrogens at positions i−2, i−1, i + 1 and i + 2, respectively. These new experimental features make protein backbone assignments more robust by reducing the degeneracy problem associated with the conventional 3D NMR experiments. PMID:21110064
Adapted cuing technique: facilitating sequential phoneme production.

PubMed

Klick, S L

1994-09-01

ACT is a visual cuing technique designed to facilitate dyspraxic speech by highlighting the sequential production of phonemes. In using ACT, cues are presented in such a way as to suggest sequential, coarticulatory movement in an overall pattern of motion. While using ACT, the facilitator's hand moves forward and back along the side of her (or his) own face. Finger movements signal specific speech sounds in formations loosely based on the manual alphabet for the hearing impaired. The best movements suggest the flowing, interactive nature of coarticulated phonemes. The synergistic nature of speech is suggested by coordinated hand motions which tighten and relax, move quickly or slowly, reflecting the motions of the vocal tract at various points during production of phonemic sequences. General principles involved in using ACT include a primary focus on speech-in-motion, the monitoring and fading of cues, and the presentation of stimuli based on motor-task analysis of phonemic sequences. Phonemic sequences are cued along three dimensions: place, manner, and vowel-related mandibular motion. Cuing vowels is a central feature of ACT. Two parameters of vowel production, focal point of resonance and mandibular closure, are cued. The facilitator's hand motions reflect the changing shape of the vocal tract and the trajectory of the tongue that result from the coarticulation of vowels and consonants. Rigid presentation of the phonemes is secondary to the facilitator's primary focus on presenting the overall sequential movement. The facilitator's goal is to self-tailor ACT in response to the changing needs and abilities of the client.(ABSTRACT TRUNCATED AT 250 WORDS)
Site of Fluoride Accumulation in Navel Orange Leaves 1

PubMed Central

Chang, Chong W.; Thompson, C. Ray

1966-01-01

Fluoride-polluted navel orange leaves, Citrus sinensis (Linn.) Osbeck, were fractionated into the subcellular components in hexane/carbon tetrachloride mixtures having various densities. Fluoride was determined at each fraction. Analyses were also made for the subcellular distribution of chlorophyll, nitrogen, and DNA to assess the extent of cross-contamination of each component. The fraction containing cell wall, nuclei, and partly broken cells apparently contained a major amount of fluoride. However, if allowance was made for the cross-contamination of chloroplasts and chloroplast fragments, the fraction of chloroplasts was found to be the site of the highest fluoride accumulation. When each particulate component was washed with water after drying, the combined washings contained more than 50% of the total fluoride of the isolated fractions. The usual method of subcellular fractionation with aqueous solvent shifted the major site of fluoride accumulation from the fraction of chloroplasts to that of the supernatant. PMID:5908632
Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms.

PubMed

Liu, Tsung-Li; Upadhyayula, Srigokul; Milkie, Daniel E; Singh, Ved; Wang, Kai; Swinburne, Ian A; Mosaliganti, Kishore R; Collins, Zach M; Hiscock, Tom W; Shea, Jamien; Kohrman, Abraham Q; Medwig, Taylor N; Dambournet, Daphne; Forster, Ryan; Cunniff, Brian; Ruan, Yuan; Yashiro, Hanako; Scholpp, Steffen; Meyerowitz, Elliot M; Hockemeyer, Dirk; Drubin, David G; Martin, Benjamin L; Matus, David Q; Koyama, Minoru; Megason, Sean G; Kirchhausen, Tom; Betzig, Eric

2018-04-20

True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Subcellular Nanoparticle Distribution from Light Transmission Spectroscopy

NASA Astrophysics Data System (ADS)

Deatsch, Alison; Sun, Nan; Johnson, Jeffrey; Stack, Sharon; Tanner, Carol; Ruggiero, Steven

We have measured the particle-size distribution (PSD) of subcellular structures in plant and animal cells. We have employed a new technique developed by our group, Light Transmission Spectroscopy-combined with cell fractionation-to accurately measure PSDs over a wide size range: from 10 nm to 3000nm, which includes objects from the size of individual proteins to organelles. To date our experiments have included cultured human oral cells and spinach cells. These results show a power-law dependence of particle density with particle diameter, implying a universality of the packing distribution. We discuss modeling the cell as a self-similar (fractal) body comprised of spheres on all size scales. This goal of this work is to obtain a better understanding of the fundamental nature of particle packing within cells in order to enrich our knowledge of the structure, function, and interactions of sub-cellular nanostructures across cell types.
RNA deep sequencing as a tool for selection of cell lines for systematic subcellular localization of all human proteins.

PubMed

Danielsson, Frida; Wiking, Mikaela; Mahdessian, Diana; Skogs, Marie; Ait Blal, Hammou; Hjelmare, Martin; Stadler, Charlotte; Uhlén, Mathias; Lundberg, Emma

2013-01-04

One of the major challenges of a chromosome-centric proteome project is to explore in a systematic manner the potential proteins identified from the chromosomal genome sequence, but not yet characterized on a protein level. Here, we describe the use of RNA deep sequencing to screen human cell lines for RNA profiles and to use this information to select cell lines suitable for characterization of the corresponding gene product. In this manner, the subcellular localization of proteins can be analyzed systematically using antibody-based confocal microscopy. We demonstrate the usefulness of selecting cell lines with high expression levels of RNA transcripts to increase the likelihood of high quality immunofluorescence staining and subsequent successful subcellular localization of the corresponding protein. The results show a path to combine transcriptomics with affinity proteomics to characterize the proteins in a gene- or chromosome-centric manner.
Nanodiamond Landmarks for Subcellular Multimodal Optical and Electron Imaging

PubMed Central

Zurbuchen, Mark A.; Lake, Michael P.; Kohan, Sirus A.; Leung, Belinda; Bouchard, Louis-S.

2013-01-01

There is a growing need for biolabels that can be used in both optical and electron microscopies, are non-cytotoxic, and do not photobleach. Such biolabels could enable targeted nanoscale imaging of sub-cellular structures, and help to establish correlations between conjugation-delivered biomolecules and function. Here we demonstrate a sub-cellular multi-modal imaging methodology that enables localization of inert particulate probes, consisting of nanodiamonds having fluorescent nitrogen-vacancy centers. These are functionalized to target specific structures, and are observable by both optical and electron microscopies. Nanodiamonds targeted to the nuclear pore complex are rapidly localized in electron-microscopy diffraction mode to enable “zooming-in” to regions of interest for detailed structural investigations. Optical microscopies reveal nanodiamonds for in-vitro tracking or uptake-confirmation. The approach is general, works down to the single nanodiamond level, and can leverage the unique capabilities of nanodiamonds, such as biocompatibility, sensitive magnetometry, and gene and drug delivery. PMID:24036840
Mechanosensitive subcellular rheostasis drives emergent single-cell mechanical homeostasis

NASA Astrophysics Data System (ADS)

Weng, Shinuo; Shao, Yue; Chen, Weiqiang; Fu, Jianping

2016-09-01

Mechanical homeostasis--a fundamental process by which cells maintain stable states under environmental perturbations--is regulated by two subcellular mechanotransducers: cytoskeleton tension and integrin-mediated focal adhesions (FAs). Here, we show that single-cell mechanical homeostasis is collectively driven by the distinct, graduated dynamics (rheostasis) of subcellular cytoskeleton tension and FAs. Such rheostasis involves a mechanosensitive pattern wherein ground states of cytoskeleton tension and FA determine their distinct reactive paths through either relaxation or reinforcement. Pharmacological perturbations of the cytoskeleton and molecularly modulated integrin catch-slip bonds biased the rheostasis and induced non-homeostasis of FAs, but not of cytoskeleton tension, suggesting a unique sensitivity of FAs in regulating homeostasis. Theoretical modelling revealed myosin-mediated cytoskeleton contractility and catch-slip-bond-like behaviours in FAs and the cytoskeleton as sufficient and necessary mechanisms for quantitatively recapitulating mechanosensitive rheostasis. Our findings highlight the previously underappreciated physical nature of the mechanical homeostasis of cells.

Status epilepticus-induced changes in the subcellular distribution and activity of calcineurin in rat forebrain.

PubMed

Kurz, Jonathan E; Rana, Annu; Parsons, J Travis; Churn, Severn B

2003-12-01

This study was performed to determine the effect of prolonged status epilepticus on the activity and subcellular location of a neuronally enriched, calcium-regulated enzyme, calcineurin. Brain fractions isolated from control animals and rats subjected to pilocarpine-induced status epilepticus were subjected to differential centrifugation. Specific subcellular fractions were tested for both calcineurin activity and enzyme content. Significant, status epilepticus-induced increases in calcineurin activity were found in homogenates, nuclear fractions, and crude synaptic membrane-enriched fractions isolated from both cortex and hippocampus. Additionally, significant increases in enzyme levels were observed in crude synaptic fractions as measured by Western analysis. Immunohistochemical studies revealed a status epilepticus-induced increase in calcineurin immunoreactivity in dendritic structures of pyramidal neurons of the hippocampus. The data demonstrate a status epilepticus-induced increase in calcineurin activity and concentration in the postsynaptic region of forebrain pyramidal neurons.
Subcellular localization of Mitf in monocytic cells.

PubMed

Lu, Ssu-Yi; Wan, Hsiao-Ching; Li, Mengtao; Lin, Yi-Ling

2010-06-01

Microphthalmia-associated transcription factor (Mitf) is a transcription factor that plays an important role in regulating the development of several cell lineages. The subcellular localization of Mitf is dynamic and is associated with its transcription activity. In this study, we examined factors that affect its subcellular localization in cells derived from the monocytic lineage since Mitf is present abundantly in these cells. We identified a domain encoded by Mitf exon 1B1b to be important for Mitf to commute between the cytoplasm and the nucleus. Deletion of this domain disrupts the shuttling of Mitf to the cytoplasm and results in its retention in the nucleus. M-CSF and RANKL both induce nuclear translocation of Mitf. We showed that Mitf nuclear transport is greatly influenced by ratio of M-CSF/Mitf protein expression. In addition, cell attachment to a solid surface also is needed for the nuclear transport of Mitf.
Subcellular characteristics of functional intracellular renin–angiotensin systems☆

PubMed Central

Abadir, Peter M.; Walston, Jeremy D.; Carey, Robert M.

2013-01-01

The renin–angio tensin system (RAS) is now regarded as an integral component in not only the development of hypertension, but also in physiologic and pathophysiologic mechanisms in multiple tissues and chronic disease states. While many of the endocrine (circulating), paracrine (cell-to-different cell) and autacrine (cell-to-same cell) effects of the RAS are believed to be mediated through the canonical extracellular RAS, a complete, independent and differentially regulated intracellular RAS (iRAS) has also been proposed. Angiotensinogen, the enzymes renin and angiotensin-converting enzyme (ACE) and the angiotensin peptides can all be synthesized and retained intracellularly. Angiotensin receptors (types I and 2) are also abundant intracellularly mainly at the nuclear and mitochondrial levels. The aim of this review is to focus on the most recent information concerning the subcellular localization, distribution and functions of the iRAS and to discuss the potential consequences of activation of the subcellular RAS on different organ systems. PMID:23032352
Apparatus and method for measuring single cell and sub-cellular photosynthetic efficiency

DOEpatents

Davis, Ryan Wesley; Singh, Seema; Wu, Huawen

2013-07-09

Devices for measuring single cell changes in photosynthetic efficiency in algal aquaculture are disclosed that include a combination of modulated LED trans-illumination of different intensities with synchronized through objective laser illumination and confocal detection. Synchronization and intensity modulation of a dual illumination scheme were provided using a custom microcontroller for a laser beam block and constant current LED driver. Therefore, single whole cell photosynthetic efficiency, and subcellular (diffraction limited) photosynthetic efficiency measurement modes are permitted. Wide field rapid light scanning actinic illumination is provided for both by an intensity modulated 470 nm LED. For the whole cell photosynthetic efficiency measurement, the same LED provides saturating pulses for generating photosynthetic induction curves. For the subcellular photosynthetic efficiency measurement, a switched through objective 488 nm laser provides saturating pulses for generating photosynthetic induction curves. A second near IR LED is employed to generate dark adapted states in the system under study.
Robust Sensing of Approaching Vehicles Relying on Acoustic Cues

PubMed Central

Mizumachi, Mitsunori; Kaminuma, Atsunobu; Ono, Nobutaka; Ando, Shigeru

2014-01-01

The latest developments in automobile design have allowed them to be equipped with various sensing devices. Multiple sensors such as cameras and radar systems can be simultaneously used for active safety systems in order to overcome blind spots of individual sensors. This paper proposes a novel sensing technique for catching up and tracking an approaching vehicle relying on an acoustic cue. First, it is necessary to extract a robust spatial feature from noisy acoustical observations. In this paper, the spatio-temporal gradient method is employed for the feature extraction. Then, the spatial feature is filtered out through sequential state estimation. A particle filter is employed to cope with a highly non-linear problem. Feasibility of the proposed method has been confirmed with real acoustical observations, which are obtained by microphones outside a cruising vehicle. PMID:24887038
Biaxially mechanical tuning of 2-D reversible and irreversible surface topologies through simultaneous and sequential wrinkling.

PubMed

Yin, Jie; Yagüe, Jose Luis; Boyce, Mary C; Gleason, Karen K

2014-02-26

Controlled buckling is a facile means of structuring surfaces. The resulting ordered wrinkling topologies provide surface properties and features desired for multifunctional applications. Here, we study the biaxially dynamic tuning of two-dimensional wrinkled micropatterns under cyclic mechanical stretching/releasing/restretching simultaneously or sequentially. A biaxially prestretched PDMS substrate is coated with a stiff polymer deposited by initiated chemical vapor deposition (iCVD). Applying a mechanical release/restretch cycle in two directions loaded simultaneously or sequentially to the wrinkled system results in a variety of dynamic and tunable wrinkled geometries, the evolution of which is investigated using in situ optical profilometry, numerical simulations, and theoretical modeling. Results show that restretching ordered herringbone micropatterns, created through sequential release of biaxial prestrain, leads to reversible and repeatable surface topography. The initial flat surface and the same wrinkled herringbone pattern are obtained alternatively after cyclic release/restretch processes, owing to the highly ordered structure leaving no avenue for trapping irregular topological regions during cycling as further evidenced by the uniformity of strains distributions and negligible residual strain. Conversely, restretching disordered labyrinth micropatterns created through simultaneous release shows an irreversible surface topology whether after sequential or simultaneous restretching due to creation of irregular surface topologies with regions of highly concentrated strain upon formation of the labyrinth which then lead to residual strains and trapped topologies upon cycling; furthermore, these trapped topologies depend upon the subsequent strain histories as well as the cycle. The disordered labyrinth pattern varies after each cyclic release/restretch process, presenting residual shallow patterns instead of achieving a flat state. The ability to dynamically tune the highly ordered herringbone patterning through mechanical stretching or other actuation makes these wrinkles excellent candidates for tunable multifunctional surfaces properties such as reflectivity, friction, anisotropic liquid flow or boundary layer control.
Apocrine Secretion in Drosophila Salivary Glands: Subcellular Origin, Dynamics, and Identification of Secretory Proteins

PubMed Central

Farkaš, Robert; Ďatková, Zuzana; Mentelová, Lucia; Löw, Péter; Beňová-Liszeková, Denisa; Beňo, Milan; Sass, Miklós; Řehulka, Pavel; Řehulková, Helena; Raška, Otakar; Kováčik, Lubomír; Šmigová, Jana; Raška, Ivan; Mechler, Bernard M.

2014-01-01

In contrast to the well defined mechanism of merocrine exocytosis, the mechanism of apocrine secretion, which was first described over 180 years ago, remains relatively uncharacterized. We identified apocrine secretory activity in the late prepupal salivary glands of Drosophila melanogaster just prior to the execution of programmed cell death (PCD). The excellent genetic tools available in Drosophila provide an opportunity to dissect for the first time the molecular and mechanistic aspects of this process. A prerequisite for such an analysis is to have pivotal immunohistochemical, ultrastructural, biochemical and proteomic data that fully characterize the process. Here we present data showing that the Drosophila salivary glands release all kinds of cellular proteins by an apocrine mechanism including cytoskeletal, cytosolic, mitochondrial, nuclear and nucleolar components. Surprisingly, the apocrine release of these proteins displays a temporal pattern with the sequential release of some proteins (e.g. transcription factor BR-C, tumor suppressor p127, cytoskeletal β-tubulin, non-muscle myosin) earlier than others (e.g. filamentous actin, nuclear lamin, mitochondrial pyruvate dehydrogenase). Although the apocrine release of proteins takes place just prior to the execution of an apoptotic program, the nuclear DNA is never released. Western blotting indicates that the secreted proteins remain undegraded in the lumen. Following apocrine secretion, the salivary gland cells remain quite vital, as they retain highly active transcriptional and protein synthetic activity. PMID:24732043
Programming chemistry in DNA-addressable bioreactors.

PubMed

Fellermann, Harold; Cardelli, Luca

2014-10-06

We present a formal calculus, termed the chemtainer calculus, able to capture the complexity of compartmentalized reaction systems such as populations of possibly nested vesicular compartments. Compartments contain molecular cargo as well as surface markers in the form of DNA single strands. These markers serve as compartment addresses and allow for their targeted transport and fusion, thereby enabling reactions of previously separated chemicals. The overall system organization allows for the set-up of programmable chemistry in microfluidic or other automated environments. We introduce a simple sequential programming language whose instructions are motivated by state-of-the-art microfluidic technology. Our approach integrates electronic control, chemical computing and material production in a unified formal framework that is able to mimic the integrated computational and constructive capabilities of the subcellular matrix. We provide a non-deterministic semantics of our programming language that enables us to analytically derive the computational and constructive power of our machinery. This semantics is used to derive the sets of all constructable chemicals and supermolecular structures that emerge from different underlying instruction sets. Because our proofs are constructive, they can be used to automatically infer control programs for the construction of target structures from a limited set of resource molecules. Finally, we present an example of our framework from the area of oligosaccharide synthesis. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Localization to Mature Melanosomes by Virtue of Cytoplasmic Dileucine Motifs Is Required for Human OCA2 Function

PubMed Central

Sitaram, Anand; Piccirillo, Rosanna; Palmisano, Ilaria; Harper, Dawn C.; Dell'Angelica, Esteban C.; Schiaffino, M. Vittoria

2009-01-01

Oculocutaneous albinism type 2 is caused by defects in the gene OCA2, encoding a pigment cell-specific, 12-transmembrane domain protein with homology to ion permeases. The function of the OCA2 protein remains unknown, and its subcellular localization is under debate. Here, we show that endogenous OCA2 in melanocytic cells rapidly exits the endoplasmic reticulum (ER) and thus does not behave as a resident ER protein. Consistently, exogenously expressed OCA2 localizes within melanocytes to melanosomes, and, like other melanosomal proteins, localizes to lysosomes when expressed in nonpigment cells. Mutagenized OCA2 transgenes stimulate melanin synthesis in OCA2-deficient cells when localized to melanosomes but not when specifically retained in the ER, contradicting a proposed primary function for OCA2 in the ER. Steady-state melanosomal localization requires a conserved consensus acidic dileucine-based sorting motif within the cytoplasmic N-terminal region of OCA2. A second dileucine signal within this region confers steady-state lysosomal localization in melanocytes, suggesting that OCA2 might traverse multiple sequential or parallel trafficking routes. The two dileucine signals physically interact in a differential manner with cytoplasmic adaptors known to function in trafficking other proteins to melanosomes. We conclude that OCA2 is targeted to and functions within melanosomes but that residence within melanosomes may be regulated by secondary or alternative targeting to lysosomes. PMID:19116314
Extremely accurate sequential verification of RELAP5-3D

DOE PAGES

Mesina, George L.; Aumiller, David L.; Buschman, Francis X.

2015-11-19

Large computer programs like RELAP5-3D solve complex systems of governing, closure and special process equations to model the underlying physics of nuclear power plants. Further, these programs incorporate many other features for physics, input, output, data management, user-interaction, and post-processing. For software quality assurance, the code must be verified and validated before being released to users. For RELAP5-3D, verification and validation are restricted to nuclear power plant applications. Verification means ensuring that the program is built right by checking that it meets its design specifications, comparing coding to algorithms and equations and comparing calculations against analytical solutions and method ofmore » manufactured solutions. Sequential verification performs these comparisons initially, but thereafter only compares code calculations between consecutive code versions to demonstrate that no unintended changes have been introduced. Recently, an automated, highly accurate sequential verification method has been developed for RELAP5-3D. The method also provides to test that no unintended consequences result from code development in the following code capabilities: repeating a timestep advancement, continuing a run from a restart file, multiple cases in a single code execution, and modes of coupled/uncoupled operation. In conclusion, mathematical analyses of the adequacy of the checks used in the comparisons are provided.« less
Alexia and agraphia with lesions of the angular and supramarginal gyri: evidence for the disruption of sequential processing.

PubMed

Sakurai, Yasuhisa; Asami, Masahiko; Mannen, Toru

2010-01-15

To determine the features of alexia or agraphia with a left angular or supramarginal gyrus lesion. We assessed the reading and writing abilities of three patients using kanji (Japanese morphograms) and kana (Japanese syllabograms). Patient 1 showed kana alexia and kanji agraphia following a hemorrhage in the left angular gyrus and the adjacent lateral occipital gyri. Patient 2 presented with minimal pure agraphia for both kanji and kana after an infarction in the left angular gyrus involving part of the supramarginal gyrus. Patient 3 also showed moderate pure agraphia for both kanji and kana after an infarction in the left supramarginal and postcentral gyri. All three patients made transposition errors (changing of sequential order of kana characters) in reading. Patient 1 showed letter-by-letter reading and a word-length effect and made substitution errors (changing hiragana [one form of kana] characters in a word to katakana [another form of kana] characters and vice versa) in writing. Alexia occurs as "angular" alexia only when the lesion involves the adjacent lateral occipital gyri. Transposition errors suggest disrupted sequential phonological processing from the angular and lateral occipital gyri to the supramarginal gyrus. Substitution errors suggest impaired allographic conversion between hiragana and katakana attributable to a dysfunction in the angular/lateral occipital gyri.
Promotion of chloroplast proliferation upon enhanced post-mitotic cell expansion in leaves.

PubMed

Kawade, Kensuke; Horiguchi, Gorou; Ishikawa, Naoko; Hirai, Masami Yokota; Tsukaya, Hirokazu

2013-09-28

Leaves are determinate organs; hence, precise control of cell proliferation and post-mitotic cell expansion is essential for their growth. A defect in cell proliferation often triggers enhanced post-mitotic cell expansion in leaves. This phenomenon is referred to as 'compensation'. Several lines of evidence from studies on compensation have shown that cell proliferation and post-mitotic cell expansion are coordinately regulated during leaf development. Therefore, compensation has attracted much attention to the mechanisms for leaf growth. However, our understanding of compensation at the subcellular level remains limited because studies of compensation have focused mainly on cellular-level phenotypes. Proper leaf growth requires quantitative control of subcellular components in association with cellular-level changes. To gain insight into the subcellular aspect of compensation, we investigated the well-known relationship between cell area and chloroplast number per cell in compensation-exhibiting lines, and asked whether chloroplast proliferation is modulated in response to the induction of compensation. We first established a convenient and reliable method for observation of chloroplasts in situ. Using this method, we analyzed Arabidopsis thaliana mutants fugu5 and angustifolia3 (an3), and a transgenic line KIP-RELATED PROTEIN2 overexpressor (KRP2 OE), which are known to exhibit typical features of compensation. We here showed that chloroplast number per cell increased in the subepidermal palisade tissue of these lines. We analyzed tetraploidized wild type, fugu5, an3 and KRP2 OE, and found that cell area itself, but not nuclear ploidy, is a key parameter that determines the activity of chloroplast proliferation. In particular, in the case of an3, we uncovered that promotion of chloroplast proliferation depends on the enhanced post-mitotic cell expansion. The expression levels of chloroplast proliferation-related genes are similar to or lower than that in the wild type during this process. This study demonstrates that chloroplast proliferation is promoted in compensation-exhibiting lines. This promotion of chloroplast proliferation takes place in response to cell-area increase in post-mitotic phase in an3. The expression of chloroplast proliferation-related genes were not promoted in compensation-exhibiting lines including an3, arguing that an as-yet-unknown mechanism is responsible for modulation of chloroplast proliferation in these lines.
Promotion of chloroplast proliferation upon enhanced post-mitotic cell expansion in leaves

PubMed Central

2013-01-01

Background Leaves are determinate organs; hence, precise control of cell proliferation and post-mitotic cell expansion is essential for their growth. A defect in cell proliferation often triggers enhanced post-mitotic cell expansion in leaves. This phenomenon is referred to as ‘compensation’. Several lines of evidence from studies on compensation have shown that cell proliferation and post-mitotic cell expansion are coordinately regulated during leaf development. Therefore, compensation has attracted much attention to the mechanisms for leaf growth. However, our understanding of compensation at the subcellular level remains limited because studies of compensation have focused mainly on cellular-level phenotypes. Proper leaf growth requires quantitative control of subcellular components in association with cellular-level changes. To gain insight into the subcellular aspect of compensation, we investigated the well-known relationship between cell area and chloroplast number per cell in compensation-exhibiting lines, and asked whether chloroplast proliferation is modulated in response to the induction of compensation. Results We first established a convenient and reliable method for observation of chloroplasts in situ. Using this method, we analyzed Arabidopsis thaliana mutants fugu5 and angustifolia3 (an3), and a transgenic line KIP-RELATED PROTEIN2 overexpressor (KRP2 OE), which are known to exhibit typical features of compensation. We here showed that chloroplast number per cell increased in the subepidermal palisade tissue of these lines. We analyzed tetraploidized wild type, fugu5, an3 and KRP2 OE, and found that cell area itself, but not nuclear ploidy, is a key parameter that determines the activity of chloroplast proliferation. In particular, in the case of an3, we uncovered that promotion of chloroplast proliferation depends on the enhanced post-mitotic cell expansion. The expression levels of chloroplast proliferation-related genes are similar to or lower than that in the wild type during this process. Conclusions This study demonstrates that chloroplast proliferation is promoted in compensation-exhibiting lines. This promotion of chloroplast proliferation takes place in response to cell-area increase in post-mitotic phase in an3. The expression of chloroplast proliferation-related genes were not promoted in compensation-exhibiting lines including an3, arguing that an as-yet-unknown mechanism is responsible for modulation of chloroplast proliferation in these lines. PMID:24074400
Inelastic Neutron Scattering Study of the Specific Features of the Phase Transitions in (NH4)2WO2F4

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

Smirnov, Lev S; Kolesnikov, Alexander I; Flerov, I. N.

2009-01-01

Oxyfluoride (NH4)2WO2F4 has been studied by the inelastic neutron scattering method over a wide temperature range 10 300 K at two initial neutron energies of 15 and 60 meV. The role of tetrahedral ammonium groups in the mechanism of sequential phase transitions at T1 = 201 K and T2 = 160 K has been discussed.
Imaging of surgical margin in pancreatic metastasis using two-photon excited fluorescence microscopy

NASA Astrophysics Data System (ADS)

Chen, Jing; Hong, Zhipeng; Chen, Hong; Chen, Youting; Xu, Yahao; Zhu, Xiaoqin; Zhuo, Shuangmu; Shi, Zheng; Chen, Jianxin

2014-09-01

Two-photon excited fluorescence (TPEF) microscopy, has become a powerful tool for imaging unstained tissue samples at subcellular level in biomedical research. The purpose of this study was to determine whether TPEF imaging of histological sections without H-E staining can be used to identify the boundary between normal pancreas and pancreatic metastasis from renal cell carcinoma (RCC). The typical features such as the significant increase of cancerous nests, the absence of pancreatic ductal, the appearance of cancer cells were observed to present the boundary between normal pancreas and pancreatic metastasis from RCC. These results correlated well with the corresponding histological outcomes. With the advent of clinically miniaturized TPEF microscopy and integrative endoscopy, TPEF microscopy has the potential application on surgical location of pancreatic metastasis from RCC in the near future.
Using Cell-ID 1.4 with R for Microscope-Based Cytometry

PubMed Central

Bush, Alan; Chernomoretz, Ariel; Yu, Richard; Gordon, Andrew

2012-01-01

This unit describes a method for quantifying various cellular features (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes referred to as bright-field or BF) is acquired to segment the image and locate each cell. Fluorescent images (one for each of the color channels to be analyzed) are then acquired by conventional wide-field epifluorescence or confocal microscopy. This method uses the image processing capabilities of Cell-ID (Gordon et al., 2007, as updated here) and data analysis by the statistical programming framework R (R-Development-Team, 2008), which we have supplemented with a package of routines for analyzing Cell-ID output. Both Cell-ID and the analysis package are open-source. PMID:23026908
Metazoan tRNA introns generate stable circular RNAs in vivo

PubMed Central

Lu, Zhipeng; Filonov, Grigory S.; Noto, John J.; Schmidt, Casey A.; Hatkevich, Talia L.; Wen, Ying; Jaffrey, Samie R.; Matera, A. Gregory

2015-01-01

We report the discovery of a class of abundant circular noncoding RNAs that are produced during metazoan tRNA splicing. These transcripts, termed tRNA intronic circular (tric)RNAs, are conserved features of animal transcriptomes. Biogenesis of tricRNAs requires anciently conserved tRNA sequence motifs and processing enzymes, and their expression is regulated in an age-dependent and tissue-specific manner. Furthermore, we exploited this biogenesis pathway to develop an in vivo expression system for generating “designer” circular RNAs in human cells. Reporter constructs expressing RNA aptamers such as Spinach and Broccoli can be used to follow the transcription and subcellular localization of tricRNAs in living cells. Owing to the superior stability of circular vs. linear RNA isoforms, this expression system has a wide range of potential applications, from basic research to pharmaceutical science. PMID:26194134
The MB2 gene family of Plasmodium species has a unique combination of S1 and GTP-binding domains

PubMed Central

Romero, Lisa C; Nguyen, Thanh V; Deville, Benoit; Ogunjumo, Oluwasanmi; James, Anthony A

2004-01-01

Background Identification and characterization of novel Plasmodium gene families is necessary for developing new anti-malarial therapeutics. The products of the Plasmodium falciparum gene, MB2, were shown previously to have a stage-specific pattern of subcellular localization and proteolytic processing. Results Genes homologous to MB2 were identified in five additional parasite species, P. knowlesi, P. gallinaceum, P. berghei, P. yoelii, and P. chabaudi. Sequence comparisons among the MB2 gene products reveal amino acid conservation of structural features, including putative S1 and GTP-binding domains, and putative signal peptides and nuclear localization signals. Conclusions The combination of domains is unique to this gene family and indicates that MB2 genes comprise a novel family and therefore may be a good target for drug development. PMID:15222903
Structural requirements of oleosin domains for subcellular targeting to the oil body.

PubMed Central

van Rooijen, G J; Moloney, M M

1995-01-01

We have investigated the protein domains responsible for the correct subcellular targeting of plant seed oleosins. We have attempted to study this targeting in vivo using "tagged" oleosins in transgenic plants. Different constructs were prepared lacking gene sequences encoding one of three structural domains of natural oleosins. Each was fused in frame to the Escherichia coli uid A gene encoding beta-glucuronidase (GUS). These constructs were introduced into Brassica napus using Agrobacterium-mediated transformation. GUS activity was measured in washed oil bodies and in the soluble protein fraction of the transgenic seeds. It was found that complete Arabidopsis oleosin-GUS fusions undergo correct subcellular targeting in transgenic Brassica seeds. Removal of the C-terminal domain of the Arabidopsis oleosin comprising the last 48 amino acids had no effect on overall subcellular targeting. In contrast, loss of the first 47 amino acids (N terminus) or amino acids 48 to 113 (which make up a lipophilic core) resulted in impaired targeting of the fusion protein to the oil bodies and greatly reduced accumulation of the fusion protein. Northern blotting revealed that this reduction is not due to differences in mRNA accumulation. Results from these measurements indicated that both the N-terminal and central oleosin domain are important for targeting to the oil body and show that there is a direct correlation between the inability to target to the oil body and protein stability. PMID:8539295
Subcellular Compartmentalization and Chemical Forms of Lead Participate in Lead Tolerance of Robinia pseudoacacia L. with Funneliformis mosseae

PubMed Central

Huang, Li; Zhang, Haoqiang; Song, Yingying; Yang, Yurong; Chen, Hui; Tang, Ming

2017-01-01

The effect of arbuscular mycorrhizal fungus on the subcellular compartmentalization and chemical forms of lead (Pb) in Pb tolerance plants was assessed in a pot experiment in greenhouse conditions. We measured root colonization, plant growth, photosynthesis, subcellular compartmentalization and chemical forms of Pb in black locust (Robinia pseudoacacia L.) seedlings inoculated with Funneliformis mosseae isolate (BGC XJ01A) under a range of Pb treatments (0, 90, 900, and 3000 mg Pb kg-1 soil). The majority of Pb was retained in the roots of R. pseudoacacia under Pb stress, with a significantly higher retention in the inoculated seedlings. F. mosseae inoculation significantly increased the proportion of Pb in the cell wall and soluble fractions and decreased the proportion of Pb in the organelle fraction of roots, stems, and leaves, with the largest proportion of Pb segregated in the cell wall fraction. F. mosseae inoculation increased the proportion of inactive Pb (especially pectate- and protein-integrated Pb and Pb phosphate) and reduced the proportion of water-soluble Pb in the roots, stems, and leaves. The subcellular compartmentalization of Pb in different chemical forms was highly correlated with improved plant biomass, height, and photosynthesis in the inoculated seedlings. This study indicates that F. mosseae could improve Pb tolerance in R. pseudoacacia seedlings growing in Pb polluted soils. PMID:28443111

Comparison of intracellular water content measurements by dark-field imaging and EELS in medium voltage TEM

NASA Astrophysics Data System (ADS)

Terryn, C.; Michel, J.; Kilian, L.; Bonhomme, P.; Balossier, G.

2000-09-01

Knowledge of the water content at the subcellular level is important to evaluate the intracellular concentration of either diffusible or non-diffusible elements in the physiological state measured by the electron microprobe methods. Water content variations in subcellular compartments are directly related to secretion phenomena and to transmembrane exchange processes, which could be attributed to pathophysiological states. In this paper we will describe in details and compare two local water measurement methods using analytical electron microscopy. The first one is based on darkfield imaging. It is applied on freeze-dried biological cryosections; it allows indirect measurement of the water content at the subcellular level from recorded maps of darkfield intensity. The second method uses electron energy loss spectroscopy. It is applied to hydrated biological cryosections. It is based on the differences that appear in the electron energy loss spectra of macromolecular assemblies and vitrified ice in the 0-30 eV range. By a multiple least squares (MLS) fit between an experimental energy loss spectrum and reference spectra of both frozen-hydrated ice and macromolecular assemblies we can deduce directly the local water concentration in biological cryosections at the subcellular level. These two methods are applied to two test specimens: human erythrocytes in plasma, and baker's yeast (Saccharomyses Cerevisiae) cryosections. We compare the water content measurements obtained by these two methods and discuss their advantages and drawbacks.
The src-family protein-tyrosine kinase p59hck is located on the secretory granules in human neutrophils and translocates towards the phagosome during cell activation.

PubMed

Möhn, H; Le Cabec, V; Fischer, S; Maridonneau-Parini, I

1995-07-15

The src-family protein-tyrosine kinase p59hck is mainly expressed in neutrophils; however, its functional role in these cells is unknown. Several other src-family members are localized on secretory vesicles and have been proposed to regulate intracellular traffic. We have established here the subcellular localization of p59hck in human neutrophils. Immunoblotting of subcellular fractions showed that approx. 60% of the p59hck per cell is localized on the secretory granules; the other 40% is distributed equally between non-granular membranes and the cytosol. Immunofluorescence of neutrophils and HL60 cells suggests that the p59hck-positive granules are azurophil granules. Granular p59hck is highly susceptible to degradation by an azurophil-granule proteinase. Different forms of p59hck occur in the three subcellular compartments: a 61 kDa form is mainly found in the granules, a 59 kDa form is predominant in the non-granular membranes, whereas cytosolic p59hck migrates as a doublet at 63 kDa. During the process of phagocytosis-linked degranulation, induced by serum-opsonized zymosan in neutrophils or HL60 cells, granular p59hck translocates towards the phagosome. The subcellular localization of p59hck suggests that the enzyme could be involved in the regulation of the degranulation process.
Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

PubMed

Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.
Clathrin to Lipid Raft-Endocytosis via Controlled Surface Chemistry and Efficient Perinuclear Targeting of Nanoparticle.

PubMed

Chakraborty, Atanu; Jana, Nikhil R

2015-09-17

Nanoparticle interacts with live cells depending on their surface chemistry, enters into cell via endocytosis, and is commonly trafficked to an endosome/lysozome that restricts subcellular targeting options. Here we show that nanoparticle surface chemistry can be tuned to alter their cell uptake mechanism and subcellular trafficking. Quantum dot based nanoprobes of 20-30 nm hydrodynamic diameters have been synthesized with tunable surface charge (between +15 mV to -25 mV) and lipophilicity to influence their cellular uptake processes and subcellular trafficking. It is observed that cationic nanoprobe electrostatically interacts with cell membrane and enters into cell via clathrin-mediated endocytosis. At lower surface charge (between +10 mV to -10 mV), the electrostatic interaction with cell membrane becomes weaker, and additional lipid raft endocytosis is initiated. If a lipophilic functional group is introduced on a weakly anionic nanoparticle surface, the uptake mechanism shifts to predominant lipid raft-mediated endocytosis. In particular, the zwitterionic-lipophilic nanoprobe has the unique advantage as it weakly interacts with anionic cell membrane, migrates toward lipid rafts for interaction through lipophilic functional group, and induces lipid raft-mediated endocytosis. While predominate or partial clathrin-mediated entry traffics most of the nanoprobes to lysozome, predominate lipid raft-mediated entry traffics them to perinuclear region, particularly to the Golgi apparatus. This finding would guide in designing appropriate nanoprobe for subcellular targeting and delivery.
Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

PubMed Central

Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent

2016-01-01

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778
Mutations in the C-terminal region affect subcellular localization of crucian carp herpesvirus (CaHV) GPCR.

PubMed

Wang, Jun; Gui, Lang; Chen, Zong-Yan; Zhang, Qi-Ya

2016-08-01

G protein-coupled receptors (GPCRs) are known as seven transmembrane domain receptors and consequently can mediate diverse biological functions via regulation of their subcellular localization. Crucian carp herpesvirus (CaHV) was recently isolated from infected fish with acute gill hemorrhage. CaHV GPCR of 349 amino acids (aa) was identified based on amino acid identity. A series of variants with truncation/deletion/substitution mutation in the C-terminal (aa 315-349) were constructed and expressed in fathead minnow (FHM) cells. The roles of three key C-terminal regions in subcellular localization of CaHV GPCR were determined. Lysine-315 (K-315) directed the aggregation of the protein preferentially at the nuclear side. Predicted N-myristoylation site (GGGWTR, aa 335-340) was responsible for punctate distribution in periplasm or throughout the cytoplasm. Predicted phosphorylation site (SSR, aa 327-329) and GGGWTR together determined the punctate distribution in cytoplasm. Detection of organelles localization by specific markers showed that the protein retaining K-315 colocalized with the Golgi apparatus. These experiments provided first evidence that different mutations of CaHV GPCR C-terminals have different affects on the subcellular localization of fish herpesvirus-encoded GPCRs. The study provided valuable information and new insights into the precise interactions between herpesvirus and fish cells, and could also provide useful targets for antiviral agents in aquaculture.
Geometric modeling of subcellular structures, organelles, and multiprotein complexes

PubMed Central

Feng, Xin; Xia, Kelin; Tong, Yiying; Wei, Guo-Wei

2013-01-01

SUMMARY Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multi-protein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes. PMID:23212797
High temperature, oxygen, and performance: Insights from reptiles and amphibians.

PubMed

Gangloff, Eric J; Telemeco, Rory S

2018-04-25

Much recent theoretical and empirical work has sought to describe the physiological mechanisms underlying thermal tolerance in animals. Leading hypotheses can be broadly divided into two categories that primarily differ in organizational scale: 1) high temperature directly reduces the function of subcellular machinery, such as enzymes and cell membranes, or 2) high temperature disrupts system-level interactions, such as mismatches in the supply and demand of oxygen, prior to having any direct negative effect on the subcellular machinery. Nonetheless, a general framework describing the contexts under which either subcellular component or organ system failure limits organisms at high temperatures remains elusive. With this commentary, we leverage decades of research on the physiology of ectothermic tetrapods (amphibians and non-avian reptiles) to address these hypotheses. Available data suggest both mechanisms are important. Thus, we expand previous work and propose the Hierarchical Mechanisms of Thermal Limitation (HMTL) hypothesis, which explains how subcellular and organ system failures interact to limit performance and set tolerance limits at high temperatures. We further integrate this framework with the thermal performance curve paradigm commonly used to predict the effects of thermal environments on performance and fitness. The HMTL framework appears to successfully explain diverse observations in reptiles and amphibians and makes numerous predictions that remain untested. We hope that this framework spurs further research in diverse taxa and facilitates mechanistic forecasts of biological responses to climate change.
The Ubiquitous Distribution of Late Embryogenesis Abundant Proteins across Cell Compartments in Arabidopsis Offers Tailored Protection against Abiotic Stress[C][W][OPEN

PubMed Central

Candat, Adrien; Paszkiewicz, Gaël; Neveu, Martine; Gautier, Romain; Logan, David C.; Avelange-Macherel, Marie-Hélène; Macherel, David

2014-01-01

Late embryogenesis abundant (LEA) proteins are hydrophilic, mostly intrinsically disordered proteins, which play major roles in desiccation tolerance. In Arabidopsis thaliana, 51 genes encoding LEA proteins clustered into nine families have been inventoried. To increase our understanding of the yet enigmatic functions of these gene families, we report the subcellular location of each protein. Experimental data highlight the limits of in silico predictions for analysis of subcellular localization. Thirty-six LEA proteins localized to the cytosol, with most being able to diffuse into the nucleus. Three proteins were exclusively localized in plastids or mitochondria, while two others were found dually targeted to these organelles. Targeting cleavage sites could be determined for five of these proteins. Three proteins were found to be endoplasmic reticulum (ER) residents, two were vacuolar, and two were secreted. A single protein was identified in pexophagosomes. While most LEA protein families have a unique subcellular localization, members of the LEA_4 family are widely distributed (cytosol, mitochondria, plastid, ER, and pexophagosome) but share the presence of the class A α-helix motif. They are thus expected to establish interactions with various cellular membranes under stress conditions. The broad subcellular distribution of LEA proteins highlights the requirement for each cellular compartment to be provided with protective mechanisms to cope with desiccation or cold stress. PMID:25005920
LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST

PubMed Central

Xie, Dan; Li, Ao; Wang, Minghui; Fan, Zhewen; Feng, Huanqing

2005-01-01

Subcellular location of a protein is one of the key functional characters as proteins must be localized correctly at the subcellular level to have normal biological function. In this paper, a novel method named LOCSVMPSI has been introduced, which is based on the support vector machine (SVM) and the position-specific scoring matrix generated from profiles of PSI-BLAST. With a jackknife test on the RH2427 data set, LOCSVMPSI achieved a high overall prediction accuracy of 90.2%, which is higher than the prediction results by SubLoc and ESLpred on this data set. In addition, prediction performance of LOCSVMPSI was evaluated with 5-fold cross validation test on the PK7579 data set and the prediction results were consistently better than the previous method based on several SVMs using composition of both amino acids and amino acid pairs. Further test on the SWISSPROT new-unique data set showed that LOCSVMPSI also performed better than some widely used prediction methods, such as PSORTII, TargetP and LOCnet. All these results indicate that LOCSVMPSI is a powerful tool for the prediction of eukaryotic protein subcellular localization. An online web server (current version is 1.3) based on this method has been developed and is freely available to both academic and commercial users, which can be accessed by at . PMID:15980436
pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information.

PubMed

Cheng, Xiang; Xiao, Xuan; Chou, Kuo-Chen

2018-05-01

For in-depth understanding the functions of proteins in a cell, the knowledge of their subcellular localization is indispensable. The current study is focused on human protein subcellular location prediction based on the sequence information alone. Although considerable efforts have been made in this regard, the problem is far from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for both basic research and drug design. Using the multi-label theory, we present a new predictor called 'pLoc-mHum' by extracting the crucial GO (Gene Ontology) information into the general PseAAC (Pseudo Amino Acid Composition). Rigorous cross-validations on a same stringent benchmark dataset have indicated that the proposed pLoc-mHum predictor is remarkably superior to iLoc-Hum, the state-of-the-art method in predicting the human protein subcellular localization. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc-mHum/, by which users can easily get their desired results without the need to go through the complicated mathematics involved. xcheng@gordonlifescience.org. Supplementary data are available at Bioinformatics online.
NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition.

PubMed

Tsai, Richard Tzong-Han; Sung, Cheng-Lung; Dai, Hong-Jie; Hung, Hsieh-Chuan; Sung, Ting-Yi; Hsu, Wen-Lian

2006-12-18

Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. To develop our ML-based Bio-NER system, we employ conditional random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features. We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows.
A multi-approach feature extractions for iris recognition

NASA Astrophysics Data System (ADS)

Sanpachai, H.; Settapong, M.

2014-04-01

Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.
Vortical features for myocardial rotation assessment in hypertrophic cardiomyopathy using cardiac tagged magnetic resonance.

PubMed

Sanz-Estébanez, Santiago; Cordero-Grande, Lucilio; Sevilla, Teresa; Revilla-Orodea, Ana; de Luis-García, Rodrigo; Martín-Fernández, Marcos; Alberola-López, Carlos

2018-07-01

Left ventricular rotational motion is a feature of normal and diseased cardiac function. However, classical torsion and twist measures rely on the definition of a rotational axis which may not exist. This paper reviews global and local rotation descriptors of myocardial motion and introduces new curl-based (vortical) features built from tensorial magnitudes, intended to provide better comprehension about fibrotic tissue characteristics mechanical properties. Fifty-six cardiomyopathy patients and twenty-two healthy volunteers have been studied using tagged magnetic resonance by means of harmonic phase analysis. Rotation descriptors are built, with no assumption about a regular geometrical model, from different approaches. The extracted vortical features have been tested by means of a sequential cardiomyopathy classification procedure; they have proven useful for the regional characterization of the left ventricular function by showing great separability not only between pathologic and healthy patients but also, and specifically, between heterogeneous phenotypes within cardiomyopathies. Copyright © 2018 Elsevier B.V. All rights reserved.
Wavelet Packet Feature Assessment for High-Density Myoelectric Pattern Recognition and Channel Selection toward Stroke Rehabilitation.

PubMed

Wang, Dongqing; Zhang, Xu; Gao, Xiaoping; Chen, Xiang; Zhou, Ping

2016-01-01

This study presents wavelet packet feature assessment of neural control information in paretic upper limb muscles of stroke survivors for myoelectric pattern recognition, taking advantage of high-resolution time-frequency representations of surface electromyogram (EMG) signals. On this basis, a novel channel selection method was developed by combining the Fisher's class separability index and the sequential feedforward selection analyses, in order to determine a small number of appropriate EMG channels from original high-density EMG electrode array. The advantages of the wavelet packet features and the channel selection analyses were further illustrated by comparing with previous conventional approaches, in terms of classification performance when identifying 20 functional arm/hand movements implemented by 12 stroke survivors. This study offers a practical approach including paretic EMG feature extraction and channel selection that enables active myoelectric control of multiple degrees of freedom with paretic muscles. All these efforts will facilitate upper limb dexterity restoration and improved stroke rehabilitation.
A Self-Adaptive Dynamic Recognition Model for Fatigue Driving Based on Multi-Source Information and Two Levels of Fusion

PubMed Central

Sun, Wei; Zhang, Xiaorui; Peeta, Srinivas; He, Xiaozheng; Li, Yongfu; Zhu, Senlai

2015-01-01

To improve the effectiveness and robustness of fatigue driving recognition, a self-adaptive dynamic recognition model is proposed that incorporates information from multiple sources and involves two sequential levels of fusion, constructed at the feature level and the decision level. Compared with existing models, the proposed model introduces a dynamic basic probability assignment (BPA) to the decision-level fusion such that the weight of each feature source can change dynamically with the real-time fatigue feature measurements. Further, the proposed model can combine the fatigue state at the previous time step in the decision-level fusion to improve the robustness of the fatigue driving recognition. An improved correction strategy of the BPA is also proposed to accommodate the decision conflict caused by external disturbances. Results from field experiments demonstrate that the effectiveness and robustness of the proposed model are better than those of models based on a single fatigue feature and/or single-source information fusion, especially when the most effective fatigue features are used in the proposed model. PMID:26393615
astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

NASA Astrophysics Data System (ADS)

Jennings, E.; Madigan, M.

2017-04-01

Given the complexity of modern cosmological parameter inference where we are faced with non-Gaussian data and noise, correlated systematics and multi-probe correlated datasets,the Approximate Bayesian Computation (ABC) method is a promising alternative to traditional Markov Chain Monte Carlo approaches in the case where the Likelihood is intractable or unknown. The ABC method is called "Likelihood free" as it avoids explicit evaluation of the Likelihood by using a forward model simulation of the data which can include systematics. We introduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler for parameter estimation. A key challenge in astrophysics is the efficient use of large multi-probe datasets to constrain high dimensional, possibly correlated parameter spaces. With this in mind astroABC allows for massive parallelization using MPI, a framework that handles spawning of processes across multiple nodes. A key new feature of astroABC is the ability to create MPI groups with different communicators, one for the sampler and several others for the forward model simulation, which speeds up sampling time considerably. For smaller jobs the Python multiprocessing option is also available. Other key features of this new sampler include: a Sequential Monte Carlo sampler; a method for iteratively adapting tolerance levels; local covariance estimate using scikit-learn's KDTree; modules for specifying optimal covariance matrix for a component-wise or multivariate normal perturbation kernel and a weighted covariance metric; restart files output frequently so an interrupted sampling run can be resumed at any iteration; output and restart files are backed up at every iteration; user defined distance metric and simulation methods; a module for specifying heterogeneous parameter priors including non-standard prior PDFs; a module for specifying a constant, linear, log or exponential tolerance level; well-documented examples and sample scripts. This code is hosted online at https://github.com/EliseJ/astroABC.
Subcellular compartmentalization of Cd and Zn in two bivalves. I. Significance of metal-sensitive fractions (MSF) and biologically detoxified metal (BDM)

USGS Publications Warehouse

Wallace, W.G.; Lee, B.-G.; Luoma, S.N.

2003-01-01

Many aspects of metal accumulation in aquatic invertebrates (i.e. toxicity, tolerance and trophic transfer) can be understood by examining the subcellular partitioning of accumulated metal. In this paper, we use a compartmentalization approach to interpret the significance of metal, species and size dependence in the subcellular partitioning of Cd and Zn in the bivalves Macoma balthica and Potamocorbula amurensis. Of special interest is the compartmentalization of metal as metal-sensitive fractions (MSF) (i.e. organelles and heat-sensitive proteins, termed 'enzymes' hereafter) and biologically detoxified metal (BDM) (i.e. metallothioneins [MT] and metal-rich granules [MRG]). Clams from San Francisco Bay, CA, were exposed for 14 d to seawater (20??? salinity) containing 3.5 ??g l-1 Cd and 20.5 ??g l-1 Zn, including 109Cd and 65Zn as radiotracers. Uptake was followed by 21 d of depuration. The subcellular partitioning of metal within clams was examined following exposure and loss. P. amurensis accumulated ???22x more Cd and ???2x more Zn than M. balthica. MT played an important role in the storage of Cd in P. amurensis, while organelles were the major site of Zn accumulation. In M. balthica, Cd and Zn partitioned similarly, although the pathway of detoxification was metal-specific (MRG for Cd; MRG and MT for Zn). Upon loss, M. balthica depurated ???40% of Cd with Zn being retained; P. amurensis retained Cd and depurated Zn (???40%). During efflux, Cd and Zn concentrations in the MSF compartment of both clams declined with metal either being lost from the animal or being transferred to the BDM compartment. Subcellular compartmentalization was also size-dependent, with the importance of BDM increasing with clam size; MSF decreased accordingly. We hypothesized that progressive retention of metal as BDM (i.e. MRG) with age may lead to size dependency of metal concentrations often observed in some populations of M. balthica.
Superresolution Imaging of Aquaporin-4 Cluster Size in Antibody-Stained Paraffin Brain Sections

PubMed Central

Smith, Alex J.; Verkman, Alan S.

2015-01-01

The water channel aquaporin-4 (AQP4) forms supramolecular clusters whose size is determined by the ratio of M1- and M23-AQP4 isoforms. In cultured astrocytes, differences in the subcellular localization and macromolecular interactions of small and large AQP4 clusters results in distinct physiological roles for M1- and M23-AQP4. Here, we developed quantitative superresolution optical imaging methodology to measure AQP4 cluster size in antibody-stained paraffin sections of mouse cerebral cortex and spinal cord, human postmortem brain, and glioma biopsy specimens. This methodology was used to demonstrate that large AQP4 clusters are formed in AQP4−/− astrocytes transfected with only M23-AQP4, but not in those expressing only M1-AQP4, both in vitro and in vivo. Native AQP4 in mouse cortex, where both isoforms are expressed, was enriched in astrocyte foot-processes adjacent to microcapillaries; clusters in perivascular regions of the cortex were larger than in parenchymal regions, demonstrating size-dependent subcellular segregation of AQP4 clusters. Two-color superresolution imaging demonstrated colocalization of Kir4.1 with AQP4 clusters in perivascular areas but not in parenchyma. Surprisingly, the subcellular distribution of AQP4 clusters was different between gray and white matter astrocytes in spinal cord, demonstrating regional specificity in cluster polarization. Changes in AQP4 subcellular distribution are associated with several neurological diseases and we demonstrate that AQP4 clustering was preserved in a postmortem human cortical brain tissue specimen, but that AQP4 was not substantially clustered in a human glioblastoma specimen despite high-level expression. Our results demonstrate the utility of superresolution optical imaging for measuring the size of AQP4 supramolecular clusters in paraffin sections of brain tissue and support AQP4 cluster size as a primary determinant of its subcellular distribution. PMID:26682810
Subcellular compartmentalization of Cd and Zn in two bivalves. II. Significance of trophically available metal (TAM)

USGS Publications Warehouse

Wallace, W.G.; Luoma, S.N.

2003-01-01

This paper examines how the subcellular partitioning of Cd and Zn in the bivalves Macoma balthica and Potamocorbula amurensis may affect the trophic transfer of metal to predators. Results show that the partitioning of metals to organelles, 'enzymes' and metallothioneins (MT) comprise a subcellular compartment containing trophically available metal (TAM; i.e. metal trophically available to predators), and that because this partitioning varies with species, animal size and metal, TAM is similarly influenced. Clams from San Francisco Bay, California, were exposed for 14 d to 3.5 ??g 1-1 Cd and 20.5 ??g 1-1 Zn, including 109Cd and 65Zn as radiotracers, and were used in feeding experiments with grass shrimp Palaemon macrodatylus, or used to investigate the subcellular partitioning of metal. Grass shrimp fed Cd-contaminated P. amurensis absorbed ???60% of ingested Cd, which was in accordance with the partitioning of Cd to the bivalve's TAM compartment (i.e. Cd associated with organelles, 'enzymes' and MT); a similar relationship was found in previous studies with grass shrimp fed Cd-contaminated oligochaetes. Thus, TAM may be used as a tool to predict the trophic transfer of at least Cd. Subcellular fractionation revealed that ???34% of both the Cd and Zn accumulated by M. balthica was associated with TAM, while partitioning to TAM in P. amurensis was metal-dependent (???60% for TAM-Cd%, ???73% for TAM-Zn%). The greater TAM-Cd% of P. amurensis than M. balthica is due to preferential binding of Cd to MT and 'enzymes', while enhanced TAM-Zn% of P. amurensis results from a greater binding of Zn to organelles. TAM for most species-metal combinations was size-dependent, decreasing with increased clam size. Based on field data, it is estimated that of the 2 bivalves, P. amurensis poses the greater threat of Cd exposure to predators because of higher tissue concentrations and greater partitioning as TAM; exposure of Zn to predators would be similar between these species.

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Sample records for sequential features subcellular

Abstract