Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory

PubMed Central

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding. PMID:24917833

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory.

PubMed

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding.

The mental representation of living and nonliving things: differential weighting and interactivity of sensorial and non-sensorial features.

PubMed

Ventura, Paulo; Morais, José; Brito-Mendes, Carlos; Kolinsky, Régine

2005-02-01

Warrington and colleagues (Warrington & McCarthy, 1983, 1987; Warrington & Shallice, 1984) claimed that sensorial and functional-associative (FA) features are differentially important in determining the meaning of living things (LT) and nonliving things (NLT). The first aim of the present study was to evaluate this hypothesis through two different access tasks: feature generation (Experiment 1) and cued recall (Experiment 2). The results of both experiments provided consistent empirical support for Warrington and colleagues' assumption. The second aim of the present study was to test a new differential interactivity hypothesis that combines Warrington and colleagueS' assumption with the notion of a higher number of intercorrelations and hence of a stronger connectivity between sensorial and non-sensorial features for LTs than for NLTs. This hypothesis was motivated by previoUs reports of an uncrossed interaction between domain (LTs vs NLTs) and attribute type (sensorial vs FA) in, for example, a feature verification task (Laws, Humber, Ramsey, & McCarthy, 1995): while FA attributes are verified faster than sensorial attributes for NLTs, no difference is observed for LTs. We replicated and generalised this finding using several feature verification tasks on both written words and pictures (Experiment 3), including in conditions aimed at minimising the intervention of priming biases and strategic or mnemonic processes (Experiment 4). The whole set of results suggests that both privileged relations between features and categories, and the differential importance of intercorrelations between features as a function of category, modulate access to semantic features.

Features of resilience

DOE PAGES

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; ...

2017-02-20

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. As a result, the proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Features of resilience

USGS Publications Warehouse

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; Palma-Oliveira, José M.; Woods, David D.; Linkov, Igor

2017-01-01

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. The proposed delineation of resilience can be important in understanding and communicating resilience concepts.

MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features.

PubMed

Xu, Juan; Li, Chuan-Xing; Li, Yong-Sheng; Lv, Jun-Ying; Ma, Ye; Shao, Ting-Ting; Xu, Liang-De; Wang, Ying-Ying; Du, Lei; Zhang, Yun-Peng; Jiang, Wei; Li, Chun-Quan; Xiao, Yun; Li, Xia

2011-02-01

Synergistic regulations among multiple microRNAs (miRNAs) are important to understand the mechanisms of complex post-transcriptional regulations in humans. Complex diseases are affected by several miRNAs rather than a single miRNA. So, it is a challenge to identify miRNA synergism and thereby further determine miRNA functions at a system-wide level and investigate disease miRNA features in the miRNA-miRNA synergistic network from a new view. Here, we constructed a miRNA-miRNA functional synergistic network (MFSN) via co-regulating functional modules that have three features: common targets of corresponding miRNA pairs, enriched in the same gene ontology category and close proximity in the protein interaction network. Predicted miRNA synergism is validated by significantly high co-expression of functional modules and significantly negative regulation to functional modules. We found that the MFSN exhibits a scale free, small world and modular architecture. Furthermore, the topological features of disease miRNAs in the MFSN are distinct from non-disease miRNAs. They have more synergism, indicating their higher complexity of functions and are the global central cores of the MFSN. In addition, miRNAs associated with the same disease are close to each other. The structure of the MFSN and the features of disease miRNAs are validated to be robust using different miRNA target data sets.

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

Data approximation using a blending type spline construction

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

Dalmo, Rune; Bratlie, Jostein

2014-11-18

Generalized expo-rational B-splines (GERBS) is a blending type spline construction where local functions at each knot are blended together by C{sup k}-smooth basis functions. One way of approximating discrete regular data using GERBS is by partitioning the data set into subsets and fit a local function to each subset. Partitioning and fitting strategies can be devised such that important or interesting data points are interpolated in order to preserve certain features. We present a method for fitting discrete data using a tensor product GERBS construction. The method is based on detection of feature points using differential geometry. Derivatives, which aremore » necessary for feature point detection and used to construct local surface patches, are approximated from the discrete data using finite differences.« less

Asymptomatic rotator cuff tears: Patient demographics and baseline shoulder function

PubMed Central

Keener, Jay D.; Steger-May, Karen; Stobbs, Georgia; Yamaguchi, Ken

2010-01-01

Background The purpose of this study is to characterize the demographic features and physical function of subjects with asymptomatic rotator cuff tears and to compare their shoulder function to controls with an intact rotator cuff. Materials and Methods 196 subjects with an asymptomatic rotator cuff tear and 54 subjects with an intact rotator cuff presenting with a painful rotator cuff tear in the contralateral shoulder were enrolled. Various demographic features, shoulder function (ASES score and SST score), range of motion and strength were compared. Results The demographic features of the study and control groups were similar. Hand dominance was associated with the presence of shoulder pain (p < .05). Subjects with an intact rotator cuff had greater but clinically insignificant ASES (p < .05) and SST scores (p < .05) than those with an asymptomatic tear. No differences in functional scores, range of motion or strength were seen between partial (n=61) and full-thickness tears (n=135). Of the full-thickness tears, 36 (27%) were classified as small, 85 (63%) as medium and 14 (10%) as large tears. No differences were seen in functional scores between full-thickness tears of various sizes. Conclusions When asymptomatic, a rotator cuff tear is associated with a clinically insignificant loss of shoulder function compared to those with an intact rotator cuff. Therefore, a clinically detectable decline in shoulder function may indicate an “at-risk” asymptomatic tear. The presence of pain is important in cuff deficient shoulders for creating a measurable loss of shoulder function. Hand dominance appears to be an important risk factor for pain. PMID:21030274

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

Chinthavali, Madhu Sudhan; Onar, Omer C; Campbell, Steven L

Integrated charger topologies that have been researched so far are with the dc-dc converters and the charging functionality usually have no isolation in the system. Isolation is an important feature that is required for user interface systems that have grid connections and therefore is a major limitation that needs to be addressed along with the integrated functionality. This study features a unique way of combining the wired and wireless charging functionalities with vehicle side boost converter integration and maintaining the isolation to provide the best solution to the plug-in electric vehicle (PEV) users. The new performance of the proposed architecturemore » is presented for wired and wireless charging options at different power levels.« less

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

PubMed

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach

NASA Astrophysics Data System (ADS)

Lopes, Fabrício M.; de Oliveira, Evaldo A.; Cesar, Roberto M.

An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many applications, such as disease treatment design and drugs creation purposes. For this reason, it is very important to uncover the functional relationship among genes and then to construct the gene regulatory network (GRN) from temporal expression data. However, this task usually involves data with a large number of variables and small number of observations. In this way, there is a strong motivation to use pattern recognition and dimensionality reduction approaches. In particular, feature selection is specially important in order to select the most important predictor genes that can explain some phenomena associated with the target genes. This work presents a first study about the sensibility of entropy methods regarding the entropy functional form, applied to the problem of topology recovery of GRNs. The generalized entropy proposed by Tsallis is used to study this sensibility. The inference process is based on a feature selection approach, which is applied to simulated temporal expression data generated by an artificial gene network (AGN) model. The inferred GRNs are validated in terms of global network measures. Some interesting conclusions can be drawn from the experimental results, as reported for the first time in the present paper.

Very high resolution Earth observation features for monitoring plant and animal community structure across multiple spatial scales in protected areas

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco; Tarantino, Cristina; Lucas, Richard M.; Nagendra, Harini; Didham, Raphael K.

2015-05-01

Monitoring the status and future trends in biodiversity can be prohibitively expensive using ground-based surveys. Consequently, significant effort is being invested in the use of satellite remote sensing to represent aspects of the proximate mechanisms (e.g., resource availability) that can be related to biodiversity surrogates (BS) such as species community descriptors. We explored the potential of very high resolution (VHR) satellite Earth observation (EO) features as proxies for habitat structural attributes that influence spatial variation in habitat quality and biodiversity change. In a semi-natural grassland mosaic of conservation concern in southern Italy, we employed a hierarchical nested sampling strategy to collect field and VHR-EO data across three spatial extent levels (landscape, patch and plot). Species incidence and abundance data were collected at the plot level for plant, insect and bird functional groups. Spectral and textural VHR-EO image features were derived from a Worldview-2 image. Three window sizes (grains) were tested for analysis and computation of textural features, guided by the perception limits of different organisms. The modelled relationships between VHR-EO features and BS responses differed across scales, suggesting that landscape, patch and plot levels are respectively most appropriate when dealing with birds, plants and insects. This research demonstrates the potential of VHR-EO for biodiversity mapping and habitat modelling, and highlights the importance of identifying the appropriate scale of analysis for specific taxonomic groups of interest. Further, textural features are important in the modelling of functional group-specific indices which represent BS in high conservation value habitat types, and provide a more direct link to species interaction networks and ecosystem functioning, than provided by traditional taxonomic diversity indices.

Estimating Shape and Micro-Motion Parameter of Rotationally Symmetric Space Objects from the Infrared Signature

PubMed Central

Wu, Yabei; Lu, Huanzhang; Zhao, Fei; Zhang, Zhiyong

2016-01-01

Shape serves as an important additional feature for space target classification, which is complementary to those made available. Since different shapes lead to different projection functions, the projection property can be regarded as one kind of shape feature. In this work, the problem of estimating the projection function from the infrared signature of the object is addressed. We show that the projection function of any rotationally symmetric object can be approximately represented as a linear combination of some base functions. Based on this fact, the signal model of the emissivity-area product sequence is constructed, which is a particular mathematical function of the linear coefficients and micro-motion parameters. Then, the least square estimator is proposed to estimate the projection function and micro-motion parameters jointly. Experiments validate the effectiveness of the proposed method. PMID:27763500

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Kinematic Features of Jaw and Lips Distinguish Symptomatic from Presymptomatic Stages of Bulbar Decline in Amyotrophic Lateral Sclerosis

ERIC Educational Resources Information Center

Bandini, Andrea; Green, Jordan R.; Wang, Jun; Campbell, Thomas F.; Zinman, Lorne; Yunusova, Yana

2018-01-01

Purpose: The goals of this study were to (a) classify speech movements of patients with amyotrophic lateral sclerosis (ALS) in presymptomatic and symptomatic phases of bulbar function decline relying solely on kinematic features of lips and jaw and (b) identify the most important measures that detect the transition between early and late bulbar…

The PRC2-binding long non-coding RNAs in human and mouse genomes are associated with predictive sequence features

NASA Astrophysics Data System (ADS)

Tu, Shiqi; Yuan, Guo-Cheng; Shao, Zhen

2017-01-01

Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance.

Protein functional features are reflected in the patterns of mRNA translation speed.

PubMed

López, Daniel; Pazos, Florencio

2015-07-09

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

A survey of stakeholder perspectives on exoskeleton technology.

PubMed

Wolff, Jamie; Parker, Claire; Borisoff, Jaimie; Mortenson, W Ben; Mattie, Johanne

2014-12-19

Exoskeleton technology has potential benefits for wheelchair users' health and mobility. However, there are practical barriers to their everyday use as a mobility device. To further understand potential exoskeleton use, and facilitate the development of new technologies, a study was undertaken to explore perspectives of wheelchair users and healthcare professionals on reasons for use of exoskeleton technology, and the importance of a variety of device characteristics. An online survey with quantitative and qualitative components was conducted with wheelchair users and healthcare professionals working directly with individuals with mobility impairments. Respondents rated whether they would use or recommend an exoskeleton for four potential reasons. Seventeen design features were rated and compared in terms of their importance. An exploratory factor analysis was conducted to categorize the 17 design features into meaningful groupings. Content analysis was used to identify themes for the open ended questions regarding reasons for use of an exoskeleton. 481 survey responses were analyzed, 354 from wheelchair users and 127 from healthcare professionals. The most highly rated reason for potential use or recommendation of an exoskeleton was health benefits. Of the design features, 4 had a median rating of very important: minimization of falls risk, comfort, putting on/taking off the device, and purchase cost. Factor analysis identified two main categories of design features: Functional Activities and Technology Characteristics. Qualitative findings indicated that health and physical benefits, use for activity and access reasons, and psychosocial benefits were important considerations in whether to use or recommend an exoskeleton. This study emphasizes the importance of developing future exoskeletons that are comfortable, affordable, minimize fall risk, and enable functional activities. Findings from this study can be utilized to inform the priorities for future development of this technology.

Clues for biomimetics from natural composite materials

PubMed Central

Lapidot, Shaul; Meirovitch, Sigal; Sharon, Sigal; Heyman, Arnon; Kaplan, David L; Shoseyov, Oded

2013-01-01

Bio-inspired material systems are derived from different living organisms such as plants, arthropods, mammals and marine organisms. These biomaterial systems from nature are always present in the form of composites, with molecular-scale interactions optimized to direct functional features. With interest in replacing synthetic materials with natural materials due to biocompatibility, sustainability and green chemistry issues, it is important to understand the molecular structure and chemistry of the raw component materials to also learn from their natural engineering, interfaces and interactions leading to durable and highly functional material architectures. This review will focus on applications of biomaterials in single material forms, as well as biomimetic composites inspired by natural organizational features. Examples of different natural composite systems will be described, followed by implementation of the principles underlying their composite organization into artificial bio-inspired systems for materials with new functional features for future medicine. PMID:22994958

Clues for biomimetics from natural composite materials.

PubMed

Lapidot, Shaul; Meirovitch, Sigal; Sharon, Sigal; Heyman, Arnon; Kaplan, David L; Shoseyov, Oded

2012-09-01

Bio-inspired material systems are derived from different living organisms such as plants, arthropods, mammals and marine organisms. These biomaterial systems from nature are always present in the form of composites, with molecular-scale interactions optimized to direct functional features. With interest in replacing synthetic materials with natural materials due to biocompatibility, sustainability and green chemistry issues, it is important to understand the molecular structure and chemistry of the raw component materials to also learn from their natural engineering, interfaces and interactions leading to durable and highly functional material architectures. This review will focus on applications of biomaterials in single material forms, as well as biomimetic composites inspired by natural organizational features. Examples of different natural composite systems will be described, followed by implementation of the principles underlying their composite organization into artificial bio-inspired systems for materials with new functional features for future medicine.

Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

Hazelbauer, Gerald L; Falke, Joseph J; Parkinson, John S

2008-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.

Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

Hazelbauer, Gerald L.; Falke, Joseph J.; Parkinson, John S.

2010-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on–off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device. PMID:18165013

Adaptive feature selection using v-shaped binary particle swarm optimization.

PubMed

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

Adaptive feature selection using v-shaped binary particle swarm optimization

PubMed Central

Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850

On the probability density function and characteristic function moments of image steganalysis in the log prediction error wavelet subband

NASA Astrophysics Data System (ADS)

Bao, Zhenkun; Li, Xiaolong; Luo, Xiangyang

2017-01-01

Extracting informative statistic features is the most essential technical issue of steganalysis. Among various steganalysis methods, probability density function (PDF) and characteristic function (CF) moments are two important types of features due to the excellent ability for distinguishing the cover images from the stego ones. The two types of features are quite similar in definition. The only difference is that the PDF moments are computed in the spatial domain, while the CF moments are computed in the Fourier-transformed domain. Then, the comparison between PDF and CF moments is an interesting question of steganalysis. Several theoretical results have been derived, and CF moments are proved better than PDF moments in some cases. However, in the log prediction error wavelet subband of wavelet decomposition, some experiments show that the result is opposite and lacks a rigorous explanation. To solve this problem, a comparison result based on the rigorous proof is presented: the first-order PDF moment is proved better than the CF moment, while the second-order CF moment is better than the PDF moment. It tries to open the theoretical discussion on steganalysis and the question of finding suitable statistical features.

Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials.

PubMed

Amsel, Ben D

2011-04-01

Empirically derived semantic feature norms categorized into different types of knowledge (e.g., visual, functional, auditory) can be summed to create number-of-feature counts per knowledge type. Initial evidence suggests several such knowledge types may be recruited during language comprehension. The present study provides a more detailed understanding of the timecourse and intensity of influence of several such knowledge types on real-time neural activity. A linear mixed-effects model was applied to single trial event-related potentials for 207 visually presented concrete words measured on total number of features (semantic richness), imageability, and number of visual motion, color, visual form, smell, taste, sound, and function features. Significant influences of multiple feature types occurred before 200ms, suggesting parallel neural computation of word form and conceptual knowledge during language comprehension. Function and visual motion features most prominently influenced neural activity, underscoring the importance of action-related knowledge in computing word meaning. The dynamic time courses and topographies of these effects are most consistent with a flexible conceptual system wherein temporally dynamic recruitment of representations in modal and supramodal cortex are a crucial element of the constellation of processes constituting word meaning computation in the brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve

NASA Astrophysics Data System (ADS)

Xu, Lili; Luo, Shuqian

2010-11-01

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve.

PubMed

Xu, Lili; Luo, Shuqian

2010-01-01

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Conserved and variable domains of RNase MRP RNA.

PubMed

Dávila López, Marcela; Rosenblad, Magnus Alm; Samuelsson, Tore

2009-01-01

Ribonuclease MRP is a eukaryotic ribonucleoprotein complex consisting of one RNA molecule and 7-10 protein subunits. One important function of MRP is to catalyze an endonucleolytic cleavage during processing of rRNA precursors. RNase MRP is evolutionary related to RNase P which is critical for tRNA processing. A large number of MRP RNA sequences that now are available have been used to identify conserved primary and secondary structure features of the molecule. MRP RNA has structural features in common with P RNA such as a conserved catalytic core, but it also has unique features and is characterized by a domain highly variable between species. Information regarding primary and secondary structure features is of interest not only in basic studies of the function of MRP RNA, but also because mutations in the RNA give rise to human genetic diseases such as cartilage-hair hypoplasia.

Is the Annual Confidential Report system effective? A study of the government appraisal system in Gujarat, India.

PubMed

Purohit, Bhaskar; Martineau, Tim

2016-06-02

Effective performance appraisal systems can not only motivate employees to improve performance but also be important for the performance of organizations. However, the appraisal systems in civil services called the Annual Confidential Report (ACR) systems can be ineffective and do not contribute to employees' learning and development. With this background, the current study aimed at understanding the ACR system and assessing its effectiveness. The research aims to contribute in filling the knowledge gap in the existing literature on the need as to why the ACR system in civil services is an important human resource management (HRM) function. The analysis is based on policy review to understand the extant appraisal-related rules and policies. Nineteen in-depth interviews with medical officers (MOs) working with the government health department of Gujarat, India, were conducted. The main objective of the research was to assess the effectiveness of the actual appraisal system called or referred to as the ACR as perceived by MOs. Thematic framework approach was used to analyze qualitative data using NVIVO 9. Themes were built around five features of an effective appraisal system, i.e., purpose, source, feedback quality, link of the ACR system with other human resource functions, and administrative effectiveness. The five features of the effective appraisal system studied in the current research (purpose, source, feedback quality, link of ACR system with other HRM functions, and administrative effectiveness) indicate that the overall appraisal system is ineffective. The overall appraisal system was perceived to be subjective and one directional in character by the study respondents. Furthermore, respondents perceived the appraisal system to be a ritual and where MOs hardly got to know about their performance, especially good performance. Hence, the feedback loop, an important feature for an effective appraisal system, was absent. The overall ACR system functions in isolation with no link to other HRM functions such as training and counselling, and a weak link with salary administration and promotion. Addressing the five features or domains of an effective appraisal system can lead to improved perceived fairness MOs have on the current appraisal system which may further influence the satisfaction and motivation positively. Improved motivation and satisfaction with the appraisal system can influence two important human resource for health-related outcomes, i.e., performance and retention.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

PubMed

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.

PRISM: Processing routines in IDL for spectroscopic measurements (installation manual and user's guide, version 1.0)

USGS Publications Warehouse

Kokaly, Raymond F.

2011-01-01

This report describes procedures for installing and using the U.S. Geological Survey Processing Routines in IDL for Spectroscopic Measurements (PRISM) software. PRISM provides a framework to conduct spectroscopic analysis of measurements made using laboratory, field, airborne, and space-based spectrometers. Using PRISM functions, the user can compare the spectra of materials of unknown composition with reference spectra of known materials. This spectroscopic analysis allows the composition of the material to be identified and characterized. Among its other functions, PRISM contains routines for the storage of spectra in database files, import/export of ENVI spectral libraries, importation of field spectra, correction of spectra to absolute reflectance, arithmetic operations on spectra, interactive continuum removal and comparison of spectral features, correction of imaging spectrometer data to ground-calibrated reflectance, and identification and mapping of materials using spectral feature-based analysis of reflectance data. This report provides step-by-step instructions for installing the PRISM software and running its functions.

ibex: An open infrastructure software platform to facilitate collaborative work in radiomics

PubMed Central

Zhang, Lifei; Fried, David V.; Fave, Xenia J.; Hunter, Luke A.; Court, Laurence E.

2015-01-01

Purpose: Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (ibex), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. Methods: The ibex software package was developed using the matlab and c/c++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, ibex is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, ibex provides an integrated development environment on top of matlab and c/c++, so users are not limited to its built-in functions. In the ibex developer studio, users can plug in, debug, and test new algorithms, extending ibex’s functionality. ibex also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the ibex workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. Results: Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the ibex software to be intuitive, powerful, and easy to use. ibex can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone ibex and ibex’s source code can be downloaded. Conclusions: The authors successfully implemented ibex, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation. PMID:25735289

IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics.

PubMed

Zhang, Lifei; Fried, David V; Fave, Xenia J; Hunter, Luke A; Yang, Jinzhong; Court, Laurence E

2015-03-01

Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (IBEX), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. The IBEX software package was developed using the MATLAB and c/c++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, IBEX is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, IBEX provides an integrated development environment on top of MATLAB and c/c++, so users are not limited to its built-in functions. In the IBEX developer studio, users can plug in, debug, and test new algorithms, extending IBEX's functionality. IBEX also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the IBEX workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the IBEX software to be intuitive, powerful, and easy to use. IBEX can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone IBEX and IBEX's source code can be downloaded. The authors successfully implemented IBEX, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation.

Dopamine, Working Memory, and Training Induced Plasticity: Implications for Developmental Research

ERIC Educational Resources Information Center

Soderqvist, Stina; Bergman Nutley, Sissela; Peyrard-Janvid, Myriam; Matsson, Hans; Humphreys, Keith; Kere, Juha; Klingberg, Torkel

2012-01-01

Cognitive deficits and particularly deficits in working memory (WM) capacity are common features in neuropsychiatric disorders. Understanding the underlying mechanisms through which WM capacity can be improved is therefore of great importance. Several lines of research indicate that dopamine plays an important role not only in WM function but also…

Adaptability: An Important Capacity for Effective Teachers

ERIC Educational Resources Information Center

Collie, Rebecca J.; Martin, Andrew J.

2016-01-01

A defining feature of teaching work is that it involves novelty, change, and uncertainty on a daily basis. Being able to respond effectively to this change is known as adaptability. In this article, we discuss the importance of adaptability for teachers and their healthy and effective functioning in the workplace. We discuss approaches for…

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

Apte, A; Veeraraghavan, H; Oh, J

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features andmore » (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.« less

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image analysis.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

The Next Generation of Interoperability Agents in Healthcare

PubMed Central

Cardoso, Luciana; Marins, Fernando; Portela, Filipe; Santos, Manuel ; Abelha, António; Machado, José

2014-01-01

Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA. PMID:24840351

Why are dunkels sticky? Preschoolers infer functionality and intentional creation for artifact properties learned from generic language.

PubMed

Cimpian, Andrei; Cadena, Cristina

2010-10-01

Artifacts pose a potential learning problem for children because the mapping between their features and their functions is often not transparent. In solving this problem, children are likely to rely on a number of information sources (e.g., others' actions, affordances). We argue that children's sensitivity to nuances in the language used to describe artifacts is an important, but so far unacknowledged, piece of this puzzle. Specifically, we hypothesize that children are sensitive to whether an unfamiliar artifact's features are highlighted using generic (e.g., "Dunkels are sticky") or non-generic (e.g., "This dunkel is sticky") language. Across two studies, older-but not younger-preschoolers who heard such features introduced via generic statements inferred that they are a functional part of the artifact's design more often than children who heard the same features introduced via non-generic statements. The ability to pick up on this linguistic cue may expand considerably the amount of conceptual information about artifacts that children derive from conversations with adults. Copyright 2010 Elsevier B.V. All rights reserved.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

SigFlux: a novel network feature to evaluate the importance of proteins in signal transduction networks.

PubMed

Liu, Wei; Li, Dong; Zhang, Jiyang; Zhu, Yunping; He, Fuchu

2006-11-27

Measuring each protein's importance in signaling networks helps to identify the crucial proteins in a cellular process, find the fragile portion of the biology system and further assist for disease therapy. However, there are relatively few methods to evaluate the importance of proteins in signaling networks. We developed a novel network feature to evaluate the importance of proteins in signal transduction networks, that we call SigFlux, based on the concept of minimal path sets (MPSs). An MPS is a minimal set of nodes that can perform the signal propagation from ligands to target genes or feedback loops. We define SigFlux as the number of MPSs in which each protein is involved. We applied this network feature to the large signal transduction network in the hippocampal CA1 neuron of mice. Significant correlations were simultaneously observed between SigFlux and both the essentiality and evolutionary rate of genes. Compared with another commonly used network feature, connectivity, SigFlux has similar or better ability as connectivity to reflect a protein's essentiality. Further classification according to protein function demonstrates that high SigFlux, low connectivity proteins are abundant in receptors and transcriptional factors, indicating that SigFlux candescribe the importance of proteins within the context of the entire network. SigFlux is a useful network feature in signal transduction networks that allows the prediction of the essentiality and conservation of proteins. With this novel network feature, proteins that participate in more pathways or feedback loops within a signaling network are proved far more likely to be essential and conserved during evolution than their counterparts.

Barriers to Functional and Qualitative Technology Education In Developing Countries: Nigeria as a Case Study.

ERIC Educational Resources Information Center

Ojo, David A.

Science and Technology have been widely recognized as the most important potent tools for socio-economic development. This paper begins with a brief critical and evaluative review of the status of science and technology education in developing countries in Africa. The conceptual framework and the major features of a functional and qualitative…

Partial dependence of breast tumor malignancy on ultrasound image features derived from boosted trees

NASA Astrophysics Data System (ADS)

Yang, Wei; Zhang, Su; Li, Wenying; Chen, Yaqing; Lu, Hongtao; Chen, Wufan; Chen, Yazhu

2010-04-01

Various computerized features extracted from breast ultrasound images are useful in assessing the malignancy of breast tumors. However, the underlying relationship between the computerized features and tumor malignancy may not be linear in nature. We use the decision tree ensemble trained by the cost-sensitive boosting algorithm to approximate the target function for malignancy assessment and to reflect this relationship qualitatively. Partial dependence plots are employed to explore and visualize the effect of features on the output of the decision tree ensemble. In the experiments, 31 image features are extracted to quantify the sonographic characteristics of breast tumors. Patient age is used as an external feature because of its high clinical importance. The area under the receiver-operating characteristic curve of the tree ensembles can reach 0.95 with sensitivity of 0.95 (61/64) at the associated specificity 0.74 (77/104). The partial dependence plots of the four most important features are demonstrated to show the influence of the features on malignancy, and they are in accord with the empirical observations. The results can provide visual and qualitative references on the computerized image features for physicians, and can be useful for enhancing the interpretability of computer-aided diagnosis systems for breast ultrasound.

Determining Changes in Neural Circuits in Tuberous Sclerosis

DTIC Science & Technology

2012-05-01

mutant mice. Importantly, the early deletion of Tsc1 in the thalamus mimicked salient features of human Tuberous Sclerosis including mosaicism, autism ...deletion of Tsc1 in the thalamus mimicks salient features of human Tuberous Sclerosis including tissue mosaicism, autism , and epilepsy. In contrast...unaffected cells. The loss of function of Tsc1 in the brain may cause mental retardation, seizures, sleep disorders, and autism . We focused on testing how a

Identifying the distinct features of geometric structures for hole trapping to generate radicals on rutile TiO₂(110) in photooxidation using density functional theory calculations with hybrid functional.

PubMed

Wang, Dong; Wang, Haifeng; Hu, P

2015-01-21

Using density functional theory calculations with HSE 06 functional, we obtained the structures of spin-polarized radicals on rutile TiO2(110), which is crucial to understand the photooxidation at the atomic level, and further calculate the thermodynamic stabilities of these radicals. By analyzing the results, we identify the structural features for hole trapping in the system, and reveal the mutual effects among the geometric structures, the energy levels of trapped hole states and their hole trapping capacities. Furthermore, the results from HSE 06 functional are compared to those from DFT + U and the stability trend of radicals against the number of slabs is tested. The effect of trapped holes on two important steps of the oxygen evolution reaction, i.e. water dissociation and the oxygen removal, is investigated and discussed.

Functional interactivity in social media: an examination of Chinese health care organizations' microblog profiles.

PubMed

Jiang, Shaohai

2017-09-08

Social media hold enormous potentials as a communication tool for health care due to its interactive nature. However, prior research mainly focused on contingency interactivity of social media, by examining messages sent from health care organizations to audiences, while little is known about functional interactivity, which refers to social media's presence of functions for facilitating communication between users and its interface. That is, how health care organizations use interactive features on social media to communicate with the public. Thus, with a general basis of the functional interactivity framework proposed by Waters et al. (Engaging stakeholders through social networking: how nonprofit organizations are using Facebook. Pub Relat Rev 2009;35:102-106), the current study investigated three aspects of functional interactivity in microblogging, and its subsequent effects. Specifically, this study analyzed 500 Chinese hospitals' profiles on Sina Weibo, the most popular microblogging platform in China. The results showed that the most common functional interactivity feature was organization disclosure, followed by information dissemination, and audience involvement. These interactive features all positively predicted the number of followers. Also, Chinese private hospitals scored significantly higher than public hospitals to use interactive features offered by social media. The findings of this study provide important implications for health care organizations to understand new communicative functions available on social media, incorporate more functions into their profiles and thus provide audiences with greater opportunity to interact with them via social media. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Spectral function of a hole in the t - J model

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

Liu, Z.; Manousakis, E.

1991-08-01

We give numerical solutions, on finite but large-size square lattices, of the equation for the single-hole Green's function obtained by the self-consistent approach of Schmitt-Rink {ital et} {ital al}. and Kane {ital et} {ital al}. The spectral function of the hole in a quantum antiferromagnet shows that most features describing the hole motion are in close agreement with the results of the exact diagonalization on the 4{sup 2} lattice in the region of {ital J}/{ital t}{le}0.2. Our results obtained on sufficiently large-size lattices suggest that certain important features of the spectral function survive in the thermodynamic limit while others changemore » due to finite-size effects. We find that the leading nonzero vertex correction is given by a two-loop diagram, which has a small contribution.« less

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Are we fully utilizing the functionalities of modern operating room ventilators?

PubMed

Liu, Shujie; Kacmarek, Robert M; Oto, Jun

2017-12-01

The modern operating room ventilators have become very sophisticated and many of their features are comparable with those of an ICU ventilator. To fully utilize the functionality of modern operating room ventilators, it is important for clinicians to understand in depth the working principle of these ventilators and their functionalities. Piston ventilators have the advantages of delivering accurate tidal volume and certain flow compensation functions. Turbine ventilators have great ability of flow compensation. Ventilation modes are mainly volume-based or pressure-based. Pressure-based ventilation modes provide better leak compensation than volume-based. The integration of advanced flow generation systems and ventilation modes of the modern operating room ventilators enables clinicians to provide both invasive and noninvasive ventilation in perioperative settings. Ventilator waveforms can be used for intraoperative neuromonitoring during cervical spine surgery. The increase in number of new features of modern operating room ventilators clearly creates the opportunity for clinicians to optimize ventilatory care. However, improving the quality of ventilator care relies on a complete understanding and correct use of these new features. VIDEO ABSTRACT: http://links.lww.com/COAN/A47.

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state.

PubMed

Yang, Yan-Li; Deng, Hong-Xia; Xing, Gui-Yang; Xia, Xiao-Luan; Li, Hai-Fang

2015-02-01

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Structures composing protein domains.

PubMed

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel; Hudeček, Jiří

2013-08-01

This review summarizes available data concerning intradomain structures (IS) such as functionally important amino acid residues, short linear motifs, conserved or disordered regions, peptide repeats, broadly occurring secondary structures or folds, etc. IS form structural features (units or elements) necessary for interactions with proteins or non-peptidic ligands, enzyme reactions and some structural properties of proteins. These features have often been related to a single structural level (e.g. primary structure) mostly requiring certain structural context of other levels (e.g. secondary structures or supersecondary folds) as follows also from some examples reported or demonstrated here. In addition, we deal with some functionally important dynamic properties of IS (e.g. flexibility and different forms of accessibility), and more special dynamic changes of IS during enzyme reactions and allosteric regulation. Selected notes concern also some experimental methods, still more necessary tools of bioinformatic processing and clinically interesting relationships. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Neuropsychiatric disorders in persons with severe traumatic brain injury: prevalence, phenomenology, and relationship with demographic, clinical, and functional features.

PubMed

Ciurli, Paola; Formisano, Rita; Bivona, Umberto; Cantagallo, Anna; Angelelli, Paola

2011-01-01

To characterize neuropsychiatric symptoms in a large group of individuals with severe traumatic brain injury (TBI) and to correlate these symptoms with demographic, clinical, and functional features. The Neuropsychiatric Inventory (NPI), a frequently used scale to assess behavioral, emotional, and motivational disorders in persons with neurological diseases, was administered to a sample of 120 persons with severe TBI. Controls were 77 healthy subjects. A wide range of neuropsychiatric symptoms was found in the population with severe TBI: apathy (42%), irritability (37%), dysphoria/depressed mood (29%), disinhibition (28%), eating disturbances (27%), and agitation (24%). A clear relationship was also found with other demographic and clinical variables. Neuropsychiatric disorders constitute an important part of the comorbidity in populations with severe TBI. Our study emphasizes the importance of integrating an overall assessment of cognitive disturbances with a specific neuropsychiatric evaluation to improve clinical understanding and treatment of persons with TBI.

[The specific features of the blood gas transport system in patients with postinfarction cardiosclerosis].

PubMed

Mikashinovich, Z I; Suroedova, R A; Olempieva, E V

2009-10-01

The specific features of blood gas transport system functioning were analyzed in patients with cardiovascular diseases. In patients with postinfarction cardiosclerosis (PICS), the quantitative mechanism for hypoxia adaptation tended to decrease, which may be considered to be a compensatory-adaptive reaction aimed at eliminating the sludge phenomenon and improving the rheological characteristics of blood. Acute myocardial reinfarction developed in patents with PICS is characterized by the lower functional activity of red blood cells, and developing hypoxia is an important link of activation of apoptotic cell death. The degree of hypoxia may be believed to correlate with the sizes of a myocardial necrosis focus.

Fractographic features of glass-ceramic and zirconia-based dental restorations fractured during clinical function.

PubMed

Oilo, Marit; Hardang, Anne D; Ulsund, Amanda H; Gjerdet, Nils R

2014-06-01

Fractures during clinical function have been reported as the major concern associated with all-ceramic dental restorations. The aim of this study was to analyze the fracture features of glass-ceramic and zirconia-based restorations fractured during clinical use. Twenty-seven crowns and onlays were supplied by dentists and dental technicians with information about type of cement and time in function, if available. Fourteen lithium disilicate glass-ceramic restorations and 13 zirconia-based restorations were retrieved and analyzed. Fractographic features were examined using optical microscopy to determine crack initiation and crack propagation of the restorations. The material comprised fractured restorations from one canine, 10 incisors, four premolars, and 11 molars. One crown was not categorized because of difficulty in orientation of the fragments. The results revealed that all core and veneer fractures initiated in the cervical margin and usually from the approximal area close to the most coronally placed curvature of the margin. Three cases of occlusal chipping were found. The margin of dental all-ceramic single-tooth restorations was the area of fracture origin. The fracture features were similar for zirconia, glass-ceramic, and alumina single-tooth restorations. Design features seem to be of great importance for fracture initiation. © 2014 Eur J Oral Sci.

SoFoCles: feature filtering for microarray classification based on gene ontology.

PubMed

Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

2010-02-01

Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

Building Data and Information Capacity in Environmental Public Health: A Best-Worst Scaling Experiment.

PubMed

Wallar, Lauren E; Sargeant, Jan M; McEwen, Scott A; Mercer, Nicola J; Papadopoulos, Andrew

Environmental public health practitioners rely on information technology (IT) to maintain and improve environmental health. However, current systems have limited capacity. A better understanding of the importance of IT features is needed to enhance data and information capacity. (1) Rank IT features according to the percentage of respondents who rated them as essential to an information management system and (2) quantify the relative importance of a subset of these features using best-worst scaling. Information technology features were initially identified from a previously published systematic review of software evaluation criteria and a list of software options from a private corporation specializing in inspection software. Duplicates and features unrelated to environmental public health were removed. The condensed list was refined by a working group of environmental public health management to a final list of 57 IT features. The essentialness of features was electronically rated by environmental public health managers. Features where 50% to 80% of respondents rated them as essential (n = 26) were subsequently evaluated using best-worst scaling. Ontario, Canada. Environmental public health professionals in local public health. Importance scores of IT features. The majority of IT features (47/57) were considered essential to an information management system by at least half of the respondents (n = 52). The highest-rated features were delivery to printer, software encryption capability, and software maintenance services. Of the 26 features evaluated in the best-worst scaling exercise, the most important features were orientation to all practice areas, off-line capability, and ability to view past inspection reports and results. The development of a single, unified environmental public health information management system that fulfills the reporting and functionality needs of system users is recommended. This system should be implemented by all public health units to support data and information capacity in local environmental public health. This study can be used to guide vendor evaluation, negotiation, and selection in local environmental public health, and provides an example of academia-practice partnerships and the use of best-worst scaling in public health research.

Differentiating Emotional Processing and Attention in Psychopathy with Functional Neuroimaging

PubMed Central

Anderson, Nathaniel E.; Steele, Vaughn R.; Maurer, J. Michael; Rao, Vikram; Koenigs, Michael R.; Decety, Jean; Kosson, David; Calhoun, Vince; Kiehl, Kent A.

2017-01-01

Psychopathic individuals are often characterized by emotional processing deficits, and recent research has examined the specific contexts and cognitive mechanisms that underlie these abnormalities. Some evidence suggests that abnormal features of attention are fundamental to psychopaths’ emotional deficits, but few studies have demonstrated the neural underpinnings responsible for such effects. Here, we use functional neuroimaging to examine attention-emotion interactions among incarcerated individuals (n=120) evaluated for psychopathic traits using the Hare Psychopathy Checklist – Revised (PCL-R). Using a task designed to manipulate attention to emotional features of visual stimuli, we demonstrate effects representing implicit emotional processing, explicit emotional processing, attention-facilitated emotional processing, and vigilance for emotional content. Results confirm the importance of considering mechanisms of attention when evaluating emotional processing differences related to psychopathic traits. The affective-interpersonal features of psychopathy (PCL-R Factor 1) were associated with relatively lower emotion-dependent augmentation of activity in visual processing areas during implicit emotional processing while antisocial-lifestyle features (PCL-R Factor 2) were associated with elevated activity in the amygdala and related salience-network regions. During explicit emotional processing psychopathic traits were associated with upregulation in the medial prefrontal cortex, insula, and superior frontal regions. Isolating the impact of explicit attention to emotional content, only Factor 1 was related to upregulation of activity in the visual processing stream, which was accompanied by increased activity in the angular gyrus. These effects highlight some important mechanisms underlying abnormal features of attention and emotional processing that accompany psychopathic traits. PMID:28092055

Differentiating emotional processing and attention in psychopathy with functional neuroimaging.

PubMed

Anderson, Nathaniel E; Steele, Vaughn R; Maurer, J Michael; Rao, Vikram; Koenigs, Michael R; Decety, Jean; Kosson, David S; Calhoun, Vince D; Kiehl, Kent A

2017-06-01

Individuals with psychopathy are often characterized by emotional processing deficits, and recent research has examined the specific contexts and cognitive mechanisms that underlie these abnormalities. Some evidence suggests that abnormal features of attention are fundamental to emotional deficits in persons with psychopathy, but few studies have demonstrated the neural underpinnings responsible for such effects. Here, we use functional neuroimaging to examine attention-emotion interactions among incarcerated individuals (n = 120) evaluated for psychopathic traits using the Hare Psychopathy Checklist-Revised (PCL-R). Using a task designed to manipulate attention to emotional features of visual stimuli, we demonstrate effects representing implicit emotional processing, explicit emotional processing, attention-facilitated emotional processing, and vigilance for emotional content. Results confirm the importance of considering mechanisms of attention when evaluating emotional processing differences related to psychopathic traits. The affective-interpersonal features of psychopathy (PCL-R Factor 1) were associated with relatively lower emotion-dependent augmentation of activity in visual processing areas during implicit emotional processing, while antisocial-lifestyle features (PCL-R Factor 2) were associated with elevated activity in the amygdala and related salience network regions. During explicit emotional processing, psychopathic traits were associated with upregulation in the medial prefrontal cortex, insula, and superior frontal regions. Isolating the impact of explicit attention to emotional content, only Factor 1 was related to upregulation of activity in the visual processing stream, which was accompanied by increased activity in the angular gyrus. These effects highlight some important mechanisms underlying abnormal features of attention and emotional processing that accompany psychopathic traits.

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness

PubMed Central

Snyder, Abraham Z.; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W.; Shen, Mark D.; Wolff, Jason J.; Botteron, Kelly N.; Dager, Stephen; Estes, Annette M.; Evans, Alan; Gerig, Guido; Hazlett, Heather C.; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Zwaigenbaum, Lonnie; Schlaggar, Bradley L.

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI. PMID:29149191

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

PubMed

Mitra, Anish; Snyder, Abraham Z; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W; Shen, Mark D; Wolff, Jason J; Botteron, Kelly N; Dager, Stephen; Estes, Annette M; Evans, Alan; Gerig, Guido; Hazlett, Heather C; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Zwaigenbaum, Lonnie; Schlaggar, Bradley L; Piven, Joseph; Pruett, John R; Raichle, Marcus

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

The Relative Importance of Family History, Gender, Mode of Onset, and Age at Onsetin Predicting Clinical Features of First-Episode Psychotic Disorders.

PubMed

Compton, Michael T; Berez, Chantal; Walker, Elaine F

Family history of psychosis, gender, mode of onset, and age at onset are considered prognostic factors important to clinicians evaluating first-episode psychosis; yet, clinicians have little guidance as to how these four factors differentially predict early-course substance abuse, symptomatology, and functioning. We conducted a "head-to-head comparison" of these four factors regarding their associations with key clinical features at initial hospitalization. We also assessed potential interactions between gender and family history with regard to age at onset of psychosis and symptom severity. Consecutively admitted first-episode patients (n=334) were evaluated in two studies that rigorously assessed a number of early-course variables. Associations among variables of interest were examined using Pearson correlations, χ 2 tests, Student's t-tests, and 2×2 factorial analyses of variance. Substance (nicotine, alcohol, and cannabis) abuse and positive symptom severity were predicted only by male gender. Negative symptom severity and global functioning impairments were predicted by earlier age at onset of psychosis. General psychopathology symptom severity was predicted by both mode of onset and age at onset. Interaction effects were not observed with regard to gender and family history in predicting age at onset or symptom severity. The four prognostic features have differential associations with substance abuse, domains of symptom severity, and global functioning. Gender and age at onset of psychosis appear to be more predictive of clinical features at the time of initial evaluation (and thus presumably longer term outcomes) than the presence of a family history of psychosis and a more gradual mode of onset.

A data driven approach for condition monitoring of wind turbine blade using vibration signals through best-first tree algorithm and functional trees algorithm: A comparative study.

PubMed

Joshuva, A; Sugumaran, V

2017-03-01

Wind energy is one of the important renewable energy resources available in nature. It is one of the major resources for production of energy because of its dependability due to the development of the technology and relatively low cost. Wind energy is converted into electrical energy using rotating blades. Due to environmental conditions and large structure, the blades are subjected to various vibration forces that may cause damage to the blades. This leads to a liability in energy production and turbine shutdown. The downtime can be reduced when the blades are diagnosed continuously using structural health condition monitoring. These are considered as a pattern recognition problem which consists of three phases namely, feature extraction, feature selection, and feature classification. In this study, statistical features were extracted from vibration signals, feature selection was carried out using a J48 decision tree algorithm and feature classification was performed using best-first tree algorithm and functional trees algorithm. The better algorithm is suggested for fault diagnosis of wind turbine blade. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function.

PubMed

Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

2017-01-01

In view of recent increase of brain computer interface (BCI) based applications, the importance of efficient classification of various mental tasks has increased prodigiously nowadays. In order to obtain effective classification, efficient feature extraction scheme is necessary, for which, in the proposed method, the interchannel relationship among electroencephalogram (EEG) data is utilized. It is expected that the correlation obtained from different combination of channels will be different for different mental tasks, which can be exploited to extract distinctive feature. The empirical mode decomposition (EMD) technique is employed on a test EEG signal obtained from a channel, which provides a number of intrinsic mode functions (IMFs), and correlation coefficient is extracted from interchannel IMF data. Simultaneously, different statistical features are also obtained from each IMF. Finally, the feature matrix is formed utilizing interchannel correlation features and intrachannel statistical features of the selected IMFs of EEG signal. Different kernels of the support vector machine (SVM) classifier are used to carry out the classification task. An EEG dataset containing ten different combinations of five different mental tasks is utilized to demonstrate the classification performance and a very high level of accuracy is achieved by the proposed scheme compared to existing methods.

Noise-resistant spectral features for retrieving foliar chemical parameters

USDA-ARS?s Scientific Manuscript database

Foliar chemical constituents are important indicators for understanding vegetation growing status and ecosystem functionality. Provided the noncontact and nondestructive traits, the hyperspectral analysis is a superior and efficient method for deriving these parameters. In practical implementation o...

An Optimization-Based Method for Feature Ranking in Nonlinear Regression Problems.

PubMed

Bravi, Luca; Piccialli, Veronica; Sciandrone, Marco

2017-04-01

In this paper, we consider the feature ranking problem, where, given a set of training instances, the task is to associate a score with the features in order to assess their relevance. Feature ranking is a very important tool for decision support systems, and may be used as an auxiliary step of feature selection to reduce the high dimensionality of real-world data. We focus on regression problems by assuming that the process underlying the generated data can be approximated by a continuous function (for instance, a feedforward neural network). We formally state the notion of relevance of a feature by introducing a minimum zero-norm inversion problem of a neural network, which is a nonsmooth, constrained optimization problem. We employ a concave approximation of the zero-norm function, and we define a smooth, global optimization problem to be solved in order to assess the relevance of the features. We present the new feature ranking method based on the solution of instances of the global optimization problem depending on the available training data. Computational experiments on both artificial and real data sets are performed, and point out that the proposed feature ranking method is a valid alternative to existing methods in terms of effectiveness. The obtained results also show that the method is costly in terms of CPU time, and this may be a limitation in the solution of large-dimensional problems.

Microbial ecology of fermentative hydrogen producing bioprocesses: useful insights for driving the ecosystem function.

PubMed

Cabrol, Lea; Marone, Antonella; Tapia-Venegas, Estela; Steyer, Jean-Philippe; Ruiz-Filippi, Gonzalo; Trably, Eric

2017-03-01

One of the most important biotechnological challenges is to develop environment friendly technologies to produce new sources of energy. Microbial production of biohydrogen through dark fermentation, by conversion of residual biomass, is an attractive solution for short-term development of bioH2 producing processes. Efficient biohydrogen production relies on complex mixed communities working in tight interaction. Species composition and functional traits are of crucial importance to maintain the ecosystem service. The analysis of microbial community revealed a wide phylogenetic diversity that contributes in different-and still mostly unclear-ways to hydrogen production. Bridging this gap of knowledge between microbial ecology features and ecosystem functionality is essential to optimize the bioprocess and develop strategies toward a maximization of the efficiency and stability of substrate conversion. The aim of this review is to provide a comprehensive overview of the most up-to-date biodata available and discuss the main microbial community features of biohydrogen engineered ecosystems, with a special emphasis on the crucial role of interactions and the relationships between species composition and ecosystem service. The elucidation of intricate relationships between community structure and ecosystem function would make possible to drive ecosystems toward an improved functionality on the basis of microbial ecology principles. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evolution and function of CAG/polyglutamine repeats in protein–protein interaction networks

PubMed Central

Schaefer, Martin H.; Wanker, Erich E.; Andrade-Navarro, Miguel A.

2012-01-01

Expanded runs of consecutive trinucleotide CAG repeats encoding polyglutamine (polyQ) stretches are observed in the genes of a large number of patients with different genetic diseases such as Huntington's and several Ataxias. Protein aggregation, which is a key feature of most of these diseases, is thought to be triggered by these expanded polyQ sequences in disease-related proteins. However, polyQ tracts are a normal feature of many human proteins, suggesting that they have an important cellular function. To clarify the potential function of polyQ repeats in biological systems, we systematically analyzed available information stored in sequence and protein interaction databases. By integrating genomic, phylogenetic, protein interaction network and functional information, we obtained evidence that polyQ tracts in proteins stabilize protein interactions. This happens most likely through structural changes whereby the polyQ sequence extends a neighboring coiled-coil region to facilitate its interaction with a coiled-coil region in another protein. Alteration of this important biological function due to polyQ expansion results in gain of abnormal interactions, leading to pathological effects like protein aggregation. Our analyses suggest that research on polyQ proteins should shift focus from expanded polyQ proteins into the characterization of the influence of the wild-type polyQ on protein interactions. PMID:22287626

Characterizing Functional Domains for TIM-Mediated Enveloped Virus Entry

PubMed Central

Moller-Tank, Sven; Albritton, Lorraine M.; Rennert, Paul D.

2014-01-01

ABSTRACT T-cell immunoglobulin and mucin domain 1 (TIM-1) and other TIM family members were recently identified as phosphatidylserine (PtdSer)-mediated virus entry-enhancing receptors (PVEERs). These proteins enhance entry of Ebola virus (EBOV) and other viruses by binding PtdSer on the viral envelope, concentrating virus on the cell surface, and promoting subsequent internalization. The PtdSer-binding activity of the immunoglobulin-like variable (IgV) domain is essential for both virus binding and internalization by TIM-1. However, TIM-3, whose IgV domain also binds PtdSer, does not effectively enhance virus entry, indicating that other domains of TIM proteins are functionally important. Here, we investigate the domains supporting enhancement of enveloped virus entry, thereby defining the features necessary for a functional PVEER. Using a variety of chimeras and deletion mutants, we found that in addition to a functional PtdSer-binding domain PVEERs require a stalk domain of sufficient length, containing sequences that promote an extended structure. Neither the cytoplasmic nor the transmembrane domain of TIM-1 is essential for enhancing virus entry, provided the protein is still plasma membrane bound. Based on these defined characteristics, we generated a mimic lacking TIM sequences and composed of annexin V, the mucin-like domain of α-dystroglycan, and a glycophosphatidylinositol anchor that functioned as a PVEER to enhance transduction of virions displaying Ebola, Chikungunya, Ross River, or Sindbis virus glycoproteins. This identification of the key features necessary for PtdSer-mediated enhancement of virus entry provides a basis for more effective recognition of unknown PVEERs. IMPORTANCE T-cell immunoglobulin and mucin domain 1 (TIM-1) and other TIM family members are recently identified phosphatidylserine (PtdSer)-mediated virus entry-enhancing receptors (PVEERs). These proteins enhance virus entry by binding the phospholipid, PtdSer, present on the viral membrane. While it is known that the PtdSer binding is essential for the PVEER function of TIM-1, TIM-3 shares this binding activity but does not enhance virus entry. No comprehensive studies have been done to characterize the other domains of TIM-1. In this study, using a variety of chimeric proteins and deletion mutants, we define the features necessary for a functional PVEER. With these features in mind, we generated a TIM-1 mimic using functionally similar domains from other proteins. This mimic, like TIM-1, effectively enhanced transduction. These studies provide insight into the key features necessary for PVEERs and will allow for more effective identification of unknown PVEERs. PMID:24696470

Comparison of multiobjective evolutionary algorithms: empirical results.

PubMed

Zitzler, E; Deb, K; Thiele, L

2000-01-01

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

Loss of Mitochondrial Function Impairs Lysosomes.

PubMed

Demers-Lamarche, Julie; Guillebaud, Gérald; Tlili, Mouna; Todkar, Kiran; Bélanger, Noémie; Grondin, Martine; Nguyen, Angela P; Michel, Jennifer; Germain, Marc

2016-05-06

Alterations in mitochondrial function, as observed in neurodegenerative diseases, lead to disrupted energy metabolism and production of damaging reactive oxygen species. Here, we demonstrate that mitochondrial dysfunction also disrupts the structure and function of lysosomes, the main degradation and recycling organelle. Specifically, inhibition of mitochondrial function, following deletion of the mitochondrial protein AIF, OPA1, or PINK1, as well as chemical inhibition of the electron transport chain, impaired lysosomal activity and caused the appearance of large lysosomal vacuoles. Importantly, our results show that lysosomal impairment is dependent on reactive oxygen species. Given that alterations in both mitochondrial function and lysosomal activity are key features of neurodegenerative diseases, this work provides important insights into the etiology of neurodegenerative diseases. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

QA4, a language for artificial intelligence.

NASA Technical Reports Server (NTRS)

Derksen, J. A. C.

1973-01-01

Introduction of a language for problem solving and specifically robot planning, program verification, and synthesis and theorem proving. This language, called question-answerer 4 (QA4), embodies many features that have been found useful for constructing problem solvers but have to be programmed explicitly by the user of a conventional language. The most important features of QA4 are described, and examples are provided for most of the material introduced. Language features include backtracking, parallel processing, pattern matching, set manipulation, and pattern-triggered function activation. The language is most convenient for use in an interactive way and has extensive trace and edit facilities.

Mining featured biomarkers associated with prostatic carcinoma based on bioinformatics.

PubMed

Piao, Guanying; Wu, Jiarui

2013-11-01

To analyze the differentially expressed genes and identify featured biomarkers from prostatic carcinoma. The software "Significance Analysis of Microarray" (SAM) was used to identify the differentially coexpressed genes (DCGs). The DCGs existed in two datasets were analyzed by GO (Gene Ontology) functional annotation. A total of 389 DCGs were obtained. By GO analysis, we found these DCGs were closely related with the acinus development, TGF-β receptor and signal transduction pathways. Furthermore, five featured biomarkers were discovered by interaction analysis. These important signal pathways and oncogenes may provide potential therapeutic targets for prostatic carcinoma.

Patient Preferences for Features of Health Care Delivery Systems: A Discrete Choice Experiment.

PubMed

Mühlbacher, Axel C; Bethge, Susanne; Reed, Shelby D; Schulman, Kevin A

2016-04-01

To estimate the relative importance of organizational-, procedural-, and interpersonal-level features of health care delivery systems from the patient perspective. We designed four discrete choice experiments (DCEs) to measure patient preferences for 21 health system attributes. Participants were recruited through the online patient portal of a large health system. We analyzed the DCE data using random effects logit models. DCEs were performed in which respondents were provided with descriptions of alternative scenarios and asked to indicate which scenario they prefer. Respondents were randomly assigned to one of the three possible health scenarios (current health, new lung cancer diagnosis, or diabetes) and asked to complete 15 choice tasks. Each choice task included an annual out-of-pocket cost attribute. A total of 3,900 respondents completed the survey. The out-of-pocket cost attribute was considered the most important across the four different DCEs. Following the cost attribute, trust and respect, multidisciplinary care, and shared decision making were judged as most important. The relative importance of out-of-pocket cost was consistently lower in the hypothetical context of a new lung cancer diagnosis compared with diabetes or the patient's current health. This study demonstrates the complexity of patient decision making processes regarding features of health care delivery systems. Our findings suggest the importance of these features may change as a function of an individual's medical conditions. © Health Research and Educational Trust.

Special requirements for electronic health record systems in ophthalmology.

PubMed

Chiang, Michael F; Boland, Michael V; Brewer, Allen; Epley, K David; Horton, Mark B; Lim, Michele C; McCannel, Colin A; Patel, Sayjal J; Silverstone, David E; Wedemeyer, Linda; Lum, Flora

2011-08-01

The field of ophthalmology has a number of unique features compared with other medical and surgical specialties regarding clinical workflow and data management. This has important implications for the design of electronic health record (EHR) systems that can be used intuitively and efficiently by ophthalmologists and that can promote improved quality of care. Ophthalmologists often lament the absence of these specialty-specific features in EHRs, particularly in systems that were developed originally for primary care physicians or other medical specialists. The purpose of this article is to summarize the special requirements of EHRs that are important for ophthalmology. The hope is that this will help ophthalmologists to identify important features when searching for EHR systems, to stimulate vendors to recognize and incorporate these functions into systems, and to assist federal agencies to develop future guidelines regarding meaningful use of EHRs. More broadly, the American Academy of Ophthalmology believes that these functions are elements of good system design that will improve access to relevant information at the point of care between the ophthalmologist and the patient, will enhance timely communications between primary care providers and ophthalmologists, will mitigate risk, and ultimately will improve the ability of physicians to deliver the highest-quality medical care. Proprietary or commercial interest disclosure may be found after the references. Copyright © 2011 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Influenza virus sequence feature variant type analysis: evidence of a role for NS1 in influenza virus host range restriction.

PubMed

Noronha, Jyothi M; Liu, Mengya; Squires, R Burke; Pickett, Brett E; Hale, Benjamin G; Air, Gillian M; Galloway, Summer E; Takimoto, Toru; Schmolke, Mirco; Hunt, Victoria; Klem, Edward; García-Sastre, Adolfo; McGee, Monnie; Scheuermann, Richard H

2012-05-01

Genetic drift of influenza virus genomic sequences occurs through the combined effects of sequence alterations introduced by a low-fidelity polymerase and the varying selective pressures experienced as the virus migrates through different host environments. While traditional phylogenetic analysis is useful in tracking the evolutionary heritage of these viruses, the specific genetic determinants that dictate important phenotypic characteristics are often difficult to discern within the complex genetic background arising through evolution. Here we describe a novel influenza virus sequence feature variant type (Flu-SFVT) approach, made available through the public Influenza Research Database resource (www.fludb.org), in which variant types (VTs) identified in defined influenza virus protein sequence features (SFs) are used for genotype-phenotype association studies. Since SFs have been defined for all influenza virus proteins based on known structural, functional, and immune epitope recognition properties, the Flu-SFVT approach allows the rapid identification of the molecular genetic determinants of important influenza virus characteristics and their connection to underlying biological functions. We demonstrate the use of the SFVT approach to obtain statistical evidence for effects of NS1 protein sequence variations in dictating influenza virus host range restriction.

Mapping landscape corridors

Treesearch

Peter Vogt; Kurt H. Riitters; Marcin Iwanowski; Christine Estreguil; Jacek Kozak; Pierre Soille

2007-01-01

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and...

Contrasting effects of feature-based statistics on the categorisation and identification of visual objects

PubMed Central

Taylor, Kirsten I.; Devereux, Barry J.; Acres, Kadia; Randall, Billi; Tyler, Lorraine K.

2013-01-01

Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. PMID:22137770

A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

PubMed Central

Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

PubMed

Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support.

PubMed

Miller, Kristen; Mosby, Danielle; Capan, Muge; Kowalski, Rebecca; Ratwani, Raj; Noaiseh, Yaman; Kraft, Rachel; Schwartz, Sanford; Weintraub, William S; Arnold, Ryan

2018-05-01

Provider acceptance and associated patient outcomes are widely discussed in the evaluation of clinical decision support systems (CDSSs), but critical design criteria for tools have generally been overlooked. The objective of this work is to inform electronic health record alert optimization and clinical practice workflow by identifying, compiling, and reporting design recommendations for CDSS to support the efficient, effective, and timely delivery of high-quality care. A narrative review was conducted from 2000 to 2016 in PubMed and The Journal of Human Factors and Ergonomics Society to identify papers that discussed/recommended design features of CDSSs that are associated with the success of these systems. Fourteen papers were included as meeting the criteria and were found to have a total of 42 unique recommendations; 11 were classified as interface features, 10 as information features, and 21 as interaction features. Features are defined and described, providing actionable guidance that can be applied to CDSS development and policy. To our knowledge, no reviews have been completed that discuss/recommend design features of CDSS at this scale, and thus we found that this was important for the body of literature. The recommendations identified in this narrative review will help to optimize design, organization, management, presentation, and utilization of information through presentation, content, and function. The designation of 3 categories (interface, information, and interaction) should be further evaluated to determine the critical importance of the categories. Future work will determine how to prioritize them with limited resources for designers and developers in order to maximize the clinical utility of CDSS. This review will expand the field of knowledge and provide a novel organization structure to identify key recommendations for CDSS.

LRRTM1 underlies synaptic convergence in visual thalamus

PubMed Central

Monavarfeshani, Aboozar; Stanton, Gail; Van Name, Jonathan; Su, Kaiwen; Mills, William A; Swilling, Kenya; Kerr, Alicia; Huebschman, Natalie A; Su, Jianmin

2018-01-01

It has long been thought that the mammalian visual system is organized into parallel pathways, with incoming visual signals being parsed in the retina based on feature (e.g. color, contrast and motion) and then transmitted to the brain in unmixed, feature-specific channels. To faithfully convey feature-specific information from retina to cortex, thalamic relay cells must receive inputs from only a small number of functionally similar retinal ganglion cells. However, recent studies challenged this by revealing substantial levels of retinal convergence onto relay cells. Here, we sought to identify mechanisms responsible for the assembly of such convergence. Using an unbiased transcriptomics approach and targeted mutant mice, we discovered a critical role for the synaptic adhesion molecule Leucine Rich Repeat Transmembrane Neuronal 1 (LRRTM1) in the emergence of retinothalamic convergence. Importantly, LRRTM1 mutant mice display impairment in visual behaviors, suggesting a functional role of retinothalamic convergence in vision. PMID:29424692

Characteristics of residential areas and transportational walking among frail and non-frail Dutch elderly: does the size of the area matter?

PubMed

Etman, Astrid; Kamphuis, Carlijn B M; Prins, Richard G; Burdorf, Alex; Pierik, Frank H; van Lenthe, Frank J

2014-03-04

A residential area supportive for walking may facilitate elderly to live longer independently. However, current evidence on area characteristics potentially important for walking among older persons is mixed. This study hypothesized that the importance of area characteristics for transportational walking depends on the size of the area characteristics measured, and older person's frailty level. The study population consisted of 408 Dutch community-dwelling persons aged 65 years and older participating in the Elderly And their Neighborhood (ELANE) study in 2011-2012. Characteristics (aesthetics, functional features, safety, and destinations) of areas surrounding participants' residences ranging from a buffer of 400 meters up to 1600 meters (based on walking path networks) were linked with self-reported transportational walking using linear regression analyses. In addition, interaction effects between frailty level and area characteristics were tested. An increase in functional features (e.g. presence of sidewalks and benches) within a 400 meter buffer, in aesthetics (e.g. absence of litter and graffiti) within 800 and 1200 meter buffers, and an increase of one destination per buffer of 400 and 800 meters were associated with more transportational walking, up to 2.89 minutes per two weeks (CI 1.07-7.32; p < 0.05). No differences were found between frail and non-frail elderly. Better functional and aesthetic features, and more destinations in the residential area of community-dwelling older persons were associated with more transportational walking. The importance of area characteristics for transportational walking differs by area size, but not by frailty level. Neighbourhood improvements may increase transportational walking among older persons, thereby contributing to living longer independently.

Cognitive impairment and pragmatics.

PubMed

Gutiérrez-Rexach, Javier; Schatz, Sara

2016-01-01

One of the most important ingredients of felicitous conversation exchanges is the adequate expression of illocutionary force and the achievement of perlocutionary effects, which can be considered essential to the functioning of pragmatic competence. The breakdown of illocutionary and perlocutionary functions is one of the most prominent external features of cognitive impairment in Alzheimer's Disease, with devastating psychological and social consequences for patients, their family and caregivers. The study of pragmatic functions is essential for a proper understanding of the linguistic and communicative aspects of Alzheimer's disease.

Shapes, scents and sounds: quantifying the full multi-sensory basis of conceptual knowledge.

PubMed

Hoffman, Paul; Lambon Ralph, Matthew A

2013-01-01

Contemporary neuroscience theories assume that concepts are formed through experience in multiple sensory-motor modalities. Quantifying the contribution of each modality to different object categories is critical to understanding the structure of the conceptual system and to explaining category-specific knowledge deficits. Verbal feature listing is typically used to elicit this information but has a number of drawbacks: sensory knowledge often cannot easily be translated into verbal features and many features are experienced in multiple modalities. Here, we employed a more direct approach in which subjects rated their knowledge of objects in each sensory-motor modality separately. Compared with these ratings, feature listing over-estimated the importance of visual form and functional knowledge and under-estimated the contributions of other sensory channels. An item's sensory rating proved to be a better predictor of lexical-semantic processing speed than the number of features it possessed, suggesting that ratings better capture the overall quantity of sensory information associated with a concept. Finally, the richer, multi-modal rating data not only replicated the sensory-functional distinction between animals and non-living things but also revealed novel distinctions between different types of artefact. Hierarchical cluster analyses indicated that mechanical devices (e.g., vehicles) were distinct from other non-living objects because they had strong sound and motion characteristics, making them more similar to animals in this respect. Taken together, the ratings align with neuroscience evidence in suggesting that a number of distinct sensory processing channels make important contributions to object knowledge. Multi-modal ratings for 160 objects are provided as supplementary materials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Complementary aspects of diffusion imaging and fMRI; I: structure and function.

PubMed

Mulkern, Robert V; Davis, Peter E; Haker, Steven J; Estepar, Raul San Jose; Panych, Lawrence P; Maier, Stephan E; Rivkin, Michael J

2006-05-01

Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.

Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.

PubMed

Kim, Seong Gon; Theera-Ampornpunt, Nawanol; Fang, Chih-Hao; Harwani, Mrudul; Grama, Ananth; Chaterji, Somali

2016-08-01

Gene expression is mediated by specialized cis-regulatory modules (CRMs), the most prominent of which are called enhancers. Early experiments indicated that enhancers located far from the gene promoters are often responsible for mediating gene transcription. Knowing their properties, regulatory activity, and genomic targets is crucial to the functional understanding of cellular events, ranging from cellular homeostasis to differentiation. Recent genome-wide investigation of epigenomic marks has indicated that enhancer elements could be enriched for certain epigenomic marks, such as, combinatorial patterns of histone modifications. Our efforts in this paper are motivated by these recent advances in epigenomic profiling methods, which have uncovered enhancer-associated chromatin features in different cell types and organisms. Specifically, in this paper, we use recent state-of-the-art Deep Learning methods and develop a deep neural network (DNN)-based architecture, called EP-DNN, to predict the presence and types of enhancers in the human genome. It uses as features, the expression levels of the histone modifications at the peaks of the functional sites as well as in its adjacent regions. We apply EP-DNN to four different cell types: H1, IMR90, HepG2, and HeLa S3. We train EP-DNN using p300 binding sites as enhancers, and TSS and random non-DHS sites as non-enhancers. We perform EP-DNN predictions to quantify the validation rate for different levels of confidence in the predictions and also perform comparisons against two state-of-the-art computational models for enhancer predictions, DEEP-ENCODE and RFECS. We find that EP-DNN has superior accuracy and takes less time to make predictions. Next, we develop methods to make EP-DNN interpretable by computing the importance of each input feature in the classification task. This analysis indicates that the important histone modifications were distinct for different cell types, with some overlaps, e.g., H3K27ac was important in cell type H1 but less so in HeLa S3, while H3K4me1 was relatively important in all four cell types. We finally use the feature importance analysis to reduce the number of input features needed to train the DNN, thus reducing training time, which is often the computational bottleneck in the use of a DNN. In this paper, we developed EP-DNN, which has high accuracy of prediction, with validation rates above 90 % for the operational region of enhancer prediction for all four cell lines that we studied, outperforming DEEP-ENCODE and RFECS. Then, we developed a method to analyze a trained DNN and determine which histone modifications are important, and within that, which features proximal or distal to the enhancer site, are important.

Degeneration and domestication of a selfish gene in yeast: molecular evolution versus site-directed mutagenesis.

PubMed

Koufopanou, Vassiliki; Burt, Austin

2005-07-01

VDE is a homing endonuclease gene in yeasts with an unusual evolutionary history including horizontal transmission, degeneration, and domestication into the mating-type switching locus HO. We investigate here the effects of these features on its molecular evolution. In addition, we correlate rates of evolution with results from site-directed mutagenesis studies. Functional elements have lower rates of evolution than degenerate ones and higher conservation at functionally important sites. However, functionally important and unimportant sites are equally likely to have been involved in the evolution of new function during the domestication of VDE into HO. The domestication event also indicates that VDE has been lost in some species and that VDE has been present in yeasts for more than 50 Myr.

A protein coevolution method uncovers critical features of the Hepatitis C Virus fusion mechanism

PubMed Central

Douam, Florian; Mancip, Jimmy; Mailly, Laurent; Montserret, Roland; Ding, Qiang; Verhoeyen, Els; Baumert, Thomas F.; Ploss, Alexander; Carbone, Alessandra

2018-01-01

Amino-acid coevolution can be referred to mutational compensatory patterns preserving the function of a protein. Viral envelope glycoproteins, which mediate entry of enveloped viruses into their host cells, are shaped by coevolution signals that confer to viruses the plasticity to evade neutralizing antibodies without altering viral entry mechanisms. The functions and structures of the two envelope glycoproteins of the Hepatitis C Virus (HCV), E1 and E2, are poorly described. Especially, how these two proteins mediate the HCV fusion process between the viral and the cell membrane remains elusive. Here, as a proof of concept, we aimed to take advantage of an original coevolution method recently developed to shed light on the HCV fusion mechanism. When first applied to the well-characterized Dengue Virus (DENV) envelope glycoproteins, coevolution analysis was able to predict important structural features and rearrangements of these viral protein complexes. When applied to HCV E1E2, computational coevolution analysis predicted that E1 and E2 refold interdependently during fusion through rearrangements of the E2 Back Layer (BL). Consistently, a soluble BL-derived polypeptide inhibited HCV infection of hepatoma cell lines, primary human hepatocytes and humanized liver mice. We showed that this polypeptide specifically inhibited HCV fusogenic rearrangements, hence supporting the critical role of this domain during HCV fusion. By combining coevolution analysis and in vitro assays, we also uncovered functionally-significant coevolving signals between E1 and E2 BL/Stem regions that govern HCV fusion, demonstrating the accuracy of our coevolution predictions. Altogether, our work shed light on important structural features of the HCV fusion mechanism and contributes to advance our functional understanding of this process. This study also provides an important proof of concept that coevolution can be employed to explore viral protein mediated-processes, and can guide the development of innovative translational strategies against challenging human-tropic viruses. PMID:29505618

Built spaces and features associated with user satisfaction in maternity waiting homes in Malawi.

PubMed

McIntosh, Nathalie; Gruits, Patricia; Oppel, Eva; Shao, Amie

2018-07-01

To assess satisfaction with maternity waiting home built spaces and features in women who are at risk for underutilizing maternity waiting homes (i.e. residential facilities that temporarily house near-term pregnant mothers close to healthcare facilities that provide obstetrical care). Specifically we wanted to answer the questions: (1) Are built spaces and features associated with maternity waiting home user satisfaction? (2) Can built spaces and features designed to improve hygiene, comfort, privacy and function improve maternity waiting home user satisfaction? And (3) Which built spaces and features are most important for maternity waiting home user satisfaction? A cross-sectional study comparing satisfaction with standard and non-standard maternity waiting home designs. Between December 2016 and February 2017 we surveyed expectant mothers at two maternity waiting homes that differed in their design of built spaces and features. We used bivariate analyses to assess if built spaces and features were associated with satisfaction. We compared ratings of built spaces and features between the two maternity waiting homes using chi-squares and t-tests to assess if design features to improve hygiene, comfort, privacy and function were associated with higher satisfaction. We used exploratory robust regression analysis to examine the relationship between built spaces and features and maternity waiting home satisfaction. Two maternity waiting homes in Malawi, one that incorporated non-standardized design features to improve hygiene, comfort, privacy, and function (Kasungu maternity waiting home) and the other that had a standard maternity waiting home design (Dowa maternity waiting home). 322 expectant mothers at risk for underutilizing maternity waiting homes (i.e. first-time mothers and those with no pregnancy risk factors) who had stayed at the Kasungu or Dowa maternity waiting homes. There were significant differences in ratings of built spaces and features between the two differently designed maternity waiting homes, with the non-standard design having higher ratings for: adequacy of toilets, and ratings of heating/cooling, air and water quality, sanitation, toilets/showers and kitchen facilities, building maintenance, sleep area, private storage space, comfort level, outdoor spaces and overall satisfaction (p = <.0001 for all). The final regression model showed that built spaces and features that are most important for maternity waiting home user satisfaction are toilets/showers, guardian spaces, safety, building maintenance, sleep area and private storage space (R 2  = 0.28). The design of maternity waiting home built spaces and features is associated with user satisfaction in women at risk for underutilizing maternity waiting homes, especially related to toilets/showers, guardian spaces, safety, building maintenance, sleep area and private storage space. Improving maternity waiting home built spaces and features may offer a promising area for improving maternity waiting home satisfaction and reducing barriers to maternity waiting home use. Copyright © 2018 Elsevier Ltd. All rights reserved.

Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

PubMed

Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

PubMed Central

Lahnakoski, Juha M.; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. PMID:22496909

Functional characterization of neotropical snakes peripheral blood leukocytes subsets: Linking flow cytometry cell features, microscopy images and serum corticosterone levels.

PubMed

de Carvalho, Marcelo Pires Nogueira; Queiroz-Hazarbassanov, Nicolle Gilda Teixeira; de Oliveira Massoco, Cristina; Sant'Anna, Sávio Stefanini; Lourenço, Mariana Mathias; Levin, Gabriel; Sogayar, Mari Cleide; Grego, Kathleen Fernandes; Catão-Dias, José Luiz

2017-09-01

Reptiles are the unique ectothermic amniotes, providing the key link between ectothermic anamniotes fish and amphibians, and endothermic birds and mammals; becoming an important group to study with the aim of providing significant knowledge into the evolutionary history of vertebrate immunity. Classification systems for reptiles' leukocytes have been described by their appearance rather than function, being still inconsistent. With the advent of modern techniques and the establishment of analytical protocols for snakes' blood by flow cytometry, we bring a qualitative and quantitative assessment of innate activities presented by snakes' peripheral blood leukocytes, thereby linking flow cytometric features with fluorescent and light microscopy images. Moreover, since corticosterone is an important immunomodulator in reptiles, hormone levels of all blood samples were measured. We provide novel and additional information which should contribute to better understanding of the development of the immune system of reptiles and vertebrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Infrared target tracking via weighted correlation filter

NASA Astrophysics Data System (ADS)

He, Yu-Jie; Li, Min; Zhang, JinLi; Yao, Jun-Ping

2015-11-01

Design of an effective target tracker is an important and challenging task for many applications due to multiple factors which can cause disturbance in infrared video sequences. In this paper, an infrared target tracking method under tracking by detection framework based on a weighted correlation filter is presented. This method consists of two parts: detection and filtering. For the detection stage, we propose a sequential detection method for the infrared target based on low-rank representation. For the filtering stage, a new multi-feature weighted function which fuses different target features is proposed, which takes the importance of the different regions into consideration. The weighted function is then incorporated into a correlation filter to compute a confidence map more accurately, in order to indicate the best target location based on the detection results obtained from the first stage. Extensive experimental results on different video sequences demonstrate that the proposed method performs favorably for detection and tracking compared with baseline methods in terms of efficiency and accuracy.

Diagnostic specificity of poor premorbid adjustment: Comparison of schizophrenia, schizoaffective disorder, and mood disorder with psychotic features

PubMed Central

Tarbox, Sarah I.; Brown, Leslie H.; Haas, Gretchen L.

2012-01-01

Individuals with schizophrenia have significant deficits in premorbid social and academic adjustment compared to individuals with non-psychotic diagnoses. However, it is unclear how severity and developmental trajectory of premorbid maladjustment compare across psychotic disorders. This study examined the association between premorbid functioning (in childhood, early adolescence, and late adolescence) and psychotic disorder diagnosis in a first-episode sample of 105 individuals: schizophrenia (n=68), schizoaffective disorder (n=22), and mood disorder with psychotic features (n=15). Social and academic maladjustment was assessed using the Cannon-Spoor Premorbid Adjustment Scale. Worse social functioning in late adolescence was associated with higher odds of schizophrenia compared to odds of either schizoaffective disorder or mood disorder with psychotic features, independently of child and early adolescent maladjustment. Greater social dysfunction in childhood was associated with higher odds of schizoaffective disorder compared to odds of schizophrenia. Premorbid decline in academic adjustment was observed for all groups, but did not predict diagnosis at any stage of development. Results suggest that social functioning is disrupted in the premorbid phase of both schizophrenia and schizoaffective disorder, but remains fairly stable in mood disorders with psychotic features. Disparities in the onset and time course of social dysfunction suggest important developmental differences between schizophrenia and schizoaffective disorder. PMID:22858353

Towards a taxonomy for integrated care: a mixed-methods study

PubMed Central

Valentijn, Pim P.; Boesveld, Inge C.; van der Klauw, Denise M.; Ruwaard, Dirk; Struijs, Jeroen N.; Molema, Johanna J.W.; Bruijnzeels, Marc A.; Vrijhoef, Hubertus JM.

2015-01-01

Introduction Building integrated services in a primary care setting is considered an essential important strategy for establishing a high-quality and affordable health care system. The theoretical foundations of such integrated service models are described by the Rainbow Model of Integrated Care, which distinguishes six integration dimensions (clinical, professional, organisational, system, functional and normative integration). The aim of the present study is to refine the Rainbow Model of Integrated Care by developing a taxonomy that specifies the underlying key features of the six dimensions. Methods First, a literature review was conducted to identify features for achieving integrated service delivery. Second, a thematic analysis method was used to develop a taxonomy of key features organised into the dimensions of the Rainbow Model of Integrated Care. Finally, the appropriateness of the key features was tested in a Delphi study among Dutch experts. Results The taxonomy consists of 59 key features distributed across the six integration dimensions of the Rainbow Model of Integrated Care. Key features associated with the clinical, professional, organisational and normative dimensions were considered appropriate by the experts. Key features linked to the functional and system dimensions were considered less appropriate. Discussion This study contributes to the ongoing debate of defining the concept and typology of integrated care. This taxonomy provides a development agenda for establishing an accepted scientific framework of integrated care from an end-user, professional, managerial and policy perspective. PMID:25759607

Towards a taxonomy for integrated care: a mixed-methods study.

PubMed

Valentijn, Pim P; Boesveld, Inge C; van der Klauw, Denise M; Ruwaard, Dirk; Struijs, Jeroen N; Molema, Johanna J W; Bruijnzeels, Marc A; Vrijhoef, Hubertus Jm

2015-01-01

Building integrated services in a primary care setting is considered an essential important strategy for establishing a high-quality and affordable health care system. The theoretical foundations of such integrated service models are described by the Rainbow Model of Integrated Care, which distinguishes six integration dimensions (clinical, professional, organisational, system, functional and normative integration). The aim of the present study is to refine the Rainbow Model of Integrated Care by developing a taxonomy that specifies the underlying key features of the six dimensions. First, a literature review was conducted to identify features for achieving integrated service delivery. Second, a thematic analysis method was used to develop a taxonomy of key features organised into the dimensions of the Rainbow Model of Integrated Care. Finally, the appropriateness of the key features was tested in a Delphi study among Dutch experts. The taxonomy consists of 59 key features distributed across the six integration dimensions of the Rainbow Model of Integrated Care. Key features associated with the clinical, professional, organisational and normative dimensions were considered appropriate by the experts. Key features linked to the functional and system dimensions were considered less appropriate. This study contributes to the ongoing debate of defining the concept and typology of integrated care. This taxonomy provides a development agenda for establishing an accepted scientific framework of integrated care from an end-user, professional, managerial and policy perspective.

Accounting for epistatic interactions improves the functional analysis of protein structures.

PubMed

Wilkins, Angela D; Venner, Eric; Marciano, David C; Erdin, Serkan; Atri, Benu; Lua, Rhonald C; Lichtarge, Olivier

2013-11-01

The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. lichtarge@bcm.edu. Supplementary data are available at Bioinformatics online.

Accounting for epistatic interactions improves the functional analysis of protein structures

PubMed Central

Wilkins, Angela D.; Venner, Eric; Marciano, David C.; Erdin, Serkan; Atri, Benu; Lua, Rhonald C.; Lichtarge, Olivier

2013-01-01

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. Contact: lichtarge@bcm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24021383

Contrasting effects of feature-based statistics on the categorisation and basic-level identification of visual objects.

PubMed

Taylor, Kirsten I; Devereux, Barry J; Acres, Kadia; Randall, Billi; Tyler, Lorraine K

2012-03-01

Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. Copyright © 2011 Elsevier B.V. All rights reserved.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

PubMed Central

Galván-Tejada, Carlos E.; Zanella-Calzada, Laura A.; Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.

2017-01-01

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions. PMID:28216571

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis.

PubMed

Galván-Tejada, Carlos E; Zanella-Calzada, Laura A; Galván-Tejada, Jorge I; Celaya-Padilla, José M; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L

2017-02-14

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.

Content and Functionality of Alcohol and Other Drug Websites: Results of an Online Survey

PubMed Central

White, Angela; Kavanagh, David; Shandley, Kerrie; Kay-Lambkin, Frances; Proudfoot, Judith; Drennan, Judy; Connor, Jason; Baker, Amanda; Young, Ross

2010-01-01

Background There is a growing trend for individuals to seek health information from online sources. Alcohol and other drug (AOD) use is a significant health problem worldwide, but access and use of AOD websites is poorly understood. Objective To investigate content and functionality preferences for AOD and other health websites. Methods An anonymous online survey examined general Internet and AOD-specific usage and search behaviors, valued features of AOD and health-related websites (general and interactive website features), indicators of website trustworthiness, valued AOD website tools or functions, and treatment modality preferences. Results Surveys were obtained from 1214 drug (n = 766) and alcohol website users (n = 448) (mean age 26.2 years, range 16-70). There were no significant differences between alcohol and drug groups on demographic variables, Internet usage, indicators of website trustworthiness, or on preferences for AOD website functionality. A robust website design/navigation, open access, and validated content provision were highly valued by both groups. While attractiveness and pictures or graphics were also valued, high-cost features (videos, animations, games) were minority preferences. Almost half of respondents in both groups were unable to readily access the information they sought. Alcohol website users placed greater importance on several AOD website tools and functions than did those accessing other drug websites: online screening tools (χ²2 = 15.8, P < .001, n = 985); prevention programs (χ²2 = 27.5, P < .001, n = 981); tracking functions (χ²2 = 11.5, P = .003, n = 983); self help treatment programs (χ²2 = 8.3, P = .02, n = 984); downloadable fact sheets for friends (χ²2 = 11.6, P = .003, n = 981); or family (χ²2 = 12.7, P = .002, n = 983). The most preferred online treatment option for both the user groups was an Internet site with email therapist support. Explorations of demographic differences were also performed. While gender did not affect survey responses, younger respondents were more likely to value interactive and social networking features, whereas downloading of credible information was most highly valued by older respondents. Conclusions Significant deficiencies in the provision of accessible information on AOD websites were identified, an important problem since information seeking was the most common reason for accessing these websites, and, therefore, may be a key avenue for engaging website users in behaviour change. The few differences between AOD website users suggested that both types of websites may have similar features, although alcohol website users may more readily be engaged in screening, prevention and self-help programs, tracking change, and may value fact sheets more highly. While the sociodemographic differences require replication and clarification, these differences support the notion that the design and features of AOD websites should target specific audiences to have maximal impact. PMID:21169168

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

Functionalized gold nanoparticle supported sensory mechanisms applied in detection of chemical and biological threat agents: a review.

PubMed

Upadhyayula, Venkata K K

2012-02-17

There is a great necessity for development of novel sensory concepts supportive of smart sensing capabilities in defense and homeland security applications for detection of chemical and biological threat agents. A smart sensor is a detection device that can exhibit important features such as speed, sensitivity, selectivity, portability, and more importantly, simplicity in identifying a target analyte. Emerging nanomaterial based sensors, particularly those developed by utilizing functionalized gold nanoparticles (GNPs) as a sensing component potentially offer many desirable features needed for threat agent detection. The sensitiveness of physical properties expressed by GNPs, e.g. color, surface plasmon resonance, electrical conductivity and binding affinity are significantly enhanced when they are subjected to functionalization with an appropriate metal, organic or biomolecular functional groups. This sensitive nature of functionalized GNPs can be potentially exploited in the design of threat agent detection devices with smart sensing capabilities. In the presence of a target analyte (i.e., a chemical or biological threat agent) a change proportional to concentration of the analyte is observed, which can be measured either by colorimetric, fluorimetric, electrochemical or spectroscopic means. This article provides a review of how functionally modified gold colloids are applied in the detection of a broad range of threat agents, including radioactive substances, explosive compounds, chemical warfare agents, biotoxins, and biothreat pathogens through any of the four sensory means mentioned previously. Copyright © 2011 Elsevier B.V. All rights reserved.

[Liver diseases in the elderly].

PubMed

Bruguera, Miguel

2014-11-01

Liver diseases in the elderly have aroused less interest than diseases of other organs, since the liver plays a limited role in aging. There are no specific liver diseases of old age, but age-related anatomical and functional modifications of the liver cause changes in the frequency and clinical behavior of some liver diseases compared with those in younger patients. This review discusses the most important features of liver function in the healthy elderly population, as well as the features of the most prevalent liver diseases in this age group, especially the diagnostic approach to the most common liver problems in the elderly: asymptomatic elevation of serum transaminases and jaundice. Copyright © 2014 Elsevier España, S.L.U. and AEEH y AEG. All rights reserved.

STELLAR CONTRIBUTION FUNCTIONS IN THE AGE OF CHEMICAL STRATIFICATION

NASA Astrophysics Data System (ADS)

Cowley, Charles; Sheminova, Valya; Castelli, Fiorella; Monier, Richard

2018-01-01

Contribution functions (CF's) were important tools to probe formation depths of features in the early numerical calculations of analytical stellar spectroscopy. In more recent work, CF's have played a minor role. Gray's (2005) text briefly discusses CF's, but CF's are not in Hubeny and Mihalas (2015). Gurtovenko and Sheminova (2015) give an extensive review of contribution functions in a recent preprint (arXiv:1505.00975). The realization that the atmospheres of certain stars are chemically stratified (Ryabchikova, Wade \\& LeBlanc, 2003, in IAU Symp. 210), and much subsequent work makes CF's of current interest. We employ new as well as older methods to compute CF's to find important layers, either for specific intensity or line depth for various points on the line profile. The most important layer is the one that causes the biggest change in the magnitude of the feature when the line absorption coefficient is set equal to zero for successive layers. This is readily done for a stratified or unstratified model. For an equivalent width, W, we calculate $(W-W_i/W) $, where $W_i$ is the equivalent width without absorption from the $i^th$ layer. We concentrate on cases where stratification is most obvious, for example, the Ca II K-line profile in the roAp stars and HR 6000 (Castelli, et al. 2017, A\\&A, 601, A119).

The regional cerebral blood flow changes in major depressive disorder with and without psychotic features.

PubMed

Gonul, Ali Saffet; Kula, Mustafa; Bilgin, Arzu Guler; Tutus, Ahmet; Oguz, Aslan

2004-09-01

Depressive patients with psychotic features demonstrate distinct biological abnormalities in the hypothalamic-pituitary-adrenal axis (HPA), dopaminergic activity, electroencephalogram sleep profiles and measures of serotonergic function when compared to nonpsychotic depressive patients. However, very few functional neuroimaging studies were specifically designed for studying the effects of psychotic features on neuroimaging findings in depressed patients. The objective of the present study was to compare brain Single Photon Emission Tomography (SPECT) images in a group of unmedicated depressive patients with and without psychotic features. Twenty-eight patients who fully met DSM-IV criteria for major depressive disorder (MDD, 12 had psychotic features) were included in the study. They were compared with 16 control subjects matched for age, gender and education. Both psychotic and nonpsychotic depressed patients showed significantly lower regional cerebral blood flow (rCBF) values in the left and right superior frontal cortex, and left anterior cingulate cortex compared to those of controls. In comparison with depressive patients without psychotic features (DwoPF), depressive patients with psychotic features (DwPF) showed significantly lower rCBF perfusion ratios in left parietal cortex, left cerebellum but had higher rCBF perfusion ratio in the left inferior frontal cortex and caudate nucleus. The present study showed that DwPF have a different rCBF pattern compared to patients without psychotic features. Abnormalities involving inferior frontal cortex, striatum and cerebellum may play an important role in the generation of psychotic symptoms in depression.

Long-term assessment of facial features and functions needing more attention in treatment of Treacher Collins syndrome.

PubMed

Plomp, Raul G; Versnel, Sarah L; van Lieshout, Manouk J S; Poublon, Rene M L; Mathijssen, Irene M J

2013-08-01

This study aimed to determine which facial features and functions need more attention during surgical treatment of Treacher Collins syndrome (TCS) in the long term. A cross-sectional cohort study was conducted to compare 23 TCS patients with 206 controls (all≥18 years) regarding satisfaction with their face. The adjusted Body Cathexis Scale was used to determine satisfaction with the appearance of the different facial features and functions. Desire for further treatment of these items was questioned. For each patient an overview was made of all facial operations performed, the affected facial features and the objective severity of the facial deformities. Patients were least satisfied with the appearance of the ears, facial profile and eyelids and with the functions hearing and nasal patency (P<0.001). Residual deformity of the reconstructed facial areas remained a problem in mainly the orbital area. The desire for further treatment and dissatisfaction was high in the operated patients, predominantly for eyelid reconstructions. Another significant wish was for improvement of hearing. In patients with TCS, functional deficits of the face are shown to be as important as the facial appearance. Particularly nasal patency and hearing are frequently impaired and require routine screening and treatment from intake onwards. Furthermore, correction of ear deformities and midface hypoplasia should be offered and performed more frequently. Residual deformity and dissatisfaction remains a problem, especially in reconstructed eyelids. II. Copyright © 2013 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

A general prediction model for the detection of ADHD and Autism using structural and functional MRI.

PubMed

Sen, Bhaskar; Borle, Neil C; Greiner, Russell; Brown, Matthew R G

2018-01-01

This work presents a novel method for learning a model that can diagnose Attention Deficit Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional connectivity features obtained from 3-dimensional structural magnetic resonance imaging (MRI) and 4-dimensional resting-state functional magnetic resonance imaging (fMRI) scans of subjects. We explore a series of three learners: (1) The LeFMS learner first extracts features from the structural MRI images using the texture-based filters produced by a sparse autoencoder. These filters are then convolved with the original MRI image using an unsupervised convolutional network. The resulting features are used as input to a linear support vector machine (SVM) classifier. (2) The LeFMF learner produces a diagnostic model by first computing spatial non-stationary independent components of the fMRI scans, which it uses to decompose each subject's fMRI scan into the time courses of these common spatial components. These features can then be used with a learner by themselves or in combination with other features to produce the model. Regardless of which approach is used, the final set of features are input to a linear support vector machine (SVM) classifier. (3) Finally, the overall LeFMSF learner uses the combined features obtained from the two feature extraction processes in (1) and (2) above as input to an SVM classifier, achieving an accuracy of 0.673 on the ADHD-200 holdout data and 0.643 on the ABIDE holdout data. Both of these results, obtained with the same LeFMSF framework, are the best known, over all hold-out accuracies on these datasets when only using imaging data-exceeding previously-published results by 0.012 for ADHD and 0.042 for Autism. Our results show that combining multi-modal features can yield good classification accuracy for diagnosis of ADHD and Autism, which is an important step towards computer-aided diagnosis of these psychiatric diseases and perhaps others as well.

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

Secure Service Proxy: A CoAP(s) Intermediary for a Securer and Smarter Web of Things

PubMed Central

Van den Abeele, Floris; Moerman, Ingrid; Demeester, Piet

2017-01-01

As the IoT continues to grow over the coming years, resource-constrained devices and networks will see an increase in traffic as everything is connected in an open Web of Things. The performance- and function-enhancing features are difficult to provide in resource-constrained environments, but will gain importance if the WoT is to be scaled up successfully. For example, scalable open standards-based authentication and authorization will be important to manage access to the limited resources of constrained devices and networks. Additionally, features such as caching and virtualization may help further reduce the load on these constrained systems. This work presents the Secure Service Proxy (SSP): a constrained-network edge proxy with the goal of improving the performance and functionality of constrained RESTful environments. Our evaluations show that the proposed design reaches its goal by reducing the load on constrained devices while implementing a wide range of features as different adapters. Specifically, the results show that the SSP leads to significant savings in processing, network traffic, network delay and packet loss rates for constrained devices. As a result, the SSP helps to guarantee the proper operation of constrained networks as these networks form an ever-expanding Web of Things. PMID:28696393

A concentrated parameter model for the human cardiovascular system including heart valve dynamics and atrioventricular interaction.

PubMed

Korakianitis, Theodosios; Shi, Yubing

2006-09-01

Numerical modeling of the human cardiovascular system has always been an active research direction since the 19th century. In the past, various simulation models of different complexities were proposed for different research purposes. In this paper, an improved numerical model to study the dynamic function of the human circulation system is proposed. In the development of the mathematical model, the heart chambers are described with a variable elastance model. The systemic and pulmonary loops are described based on the resistance-compliance-inertia concept by considering local effects of flow friction, elasticity of blood vessels and inertia of blood in different segments of the blood vessels. As an advancement from previous models, heart valve dynamics and atrioventricular interaction, including atrial contraction and motion of the annulus fibrosus, are specifically modeled. With these improvements the developed model can predict several important features that were missing in previous numerical models, including regurgitant flow on heart valve closure, the value of E/A velocity ratio in mitral flow, the motion of the annulus fibrosus (called the KG diaphragm pumping action), etc. These features have important clinical meaning and their changes are often related to cardiovascular diseases. Successful simulation of these features enhances the accuracy of simulations of cardiovascular dynamics, and helps in clinical studies of cardiac function.

Secure Service Proxy: A CoAP(s) Intermediary for a Securer and Smarter Web of Things.

PubMed

Van den Abeele, Floris; Moerman, Ingrid; Demeester, Piet; Hoebeke, Jeroen

2017-07-11

As the IoT continues to grow over the coming years, resource-constrained devices and networks will see an increase in traffic as everything is connected in an open Web of Things. The performance- and function-enhancing features are difficult to provide in resource-constrained environments, but will gain importance if the WoT is to be scaled up successfully. For example, scalable open standards-based authentication and authorization will be important to manage access to the limited resources of constrained devices and networks. Additionally, features such as caching and virtualization may help further reduce the load on these constrained systems. This work presents the Secure Service Proxy (SSP): a constrained-network edge proxy with the goal of improving the performance and functionality of constrained RESTful environments. Our evaluations show that the proposed design reaches its goal by reducing the load on constrained devices while implementing a wide range of features as different adapters. Specifically, the results show that the SSP leads to significant savings in processing, network traffic, network delay and packet loss rates for constrained devices. As a result, the SSP helps to guarantee the proper operation of constrained networks as these networks form an ever-expanding Web of Things.

In-process and post-process measurements of drill wear for control of the drilling process

NASA Astrophysics Data System (ADS)

Liu, Tien-I.; Liu, George; Gao, Zhiyu

2011-12-01

Optical inspection was used in this research for the post-process measurements of drill wear. A precision toolmakers" microscope was used. Indirect index, cutting force, is used for in-process drill wear measurements. Using in-process measurements to estimate the drill wear for control purpose can decrease the operation cost and enhance the product quality and safety. The challenge is to correlate the in-process cutting force measurements with the post-process optical inspection of drill wear. To find the most important feature, the energy principle was used in this research. It is necessary to select only the cutting force feature which shows the highest sensitivity to drill wear. The best feature selected is the peak of torque in the drilling process. Neuro-fuzzy systems were used for correlation purposes. The Adaptive-Network-Based Fuzzy Inference System (ANFIS) can construct fuzzy rules with membership functions to generate an input-output pair. A 1x6 ANFIS architecture with product of sigmoid membership functions can in-process measure the drill wear with an error as low as 0.15%. This is extremely important for control of the drilling process. Furthermore, the measurement of drill wear was performed under different drilling conditions. This shows that ANFIS has the capability of generalization.

Modeling asthma: Pitfalls, promises, and the road ahead.

PubMed

Rosenberg, Helene F; Druey, Kirk M

2018-02-16

Asthma is a chronic, heterogeneous, and recurring inflammatory disease of the lower airways, with exacerbations that feature airway inflammation and bronchial hyperresponsiveness. Asthma has been modeled extensively via disease induction in both wild-type and genetically manipulated laboratory mice (Mus musculus). Antigen sensitization and challenge strategies have reproduced numerous important features of airway inflammation characteristic of human asthma, notably the critical roles of type 2 T helper cell cytokines. Recent models of disease induction have advanced to include physiologic aeroallergens with prolonged respiratory challenge without systemic sensitization; others incorporate tobacco, respiratory viruses, or bacteria as exacerbants. Nonetheless, differences in lung size, structure, and physiologic responses limit the degree to which airway dynamics measured in mice can be compared to human subjects. Other rodent allergic airways models, including those featuring the guinea pig (Cavia porcellus) might be considered for lung function studies. Finally, domestic cats (Feline catus) and horses (Equus caballus) develop spontaneous obstructive airway disorders with clinical and pathologic features that parallel human asthma. Information on pathogenesis and treatment of these disorders is an important resource. ©2018 Society for Leukocyte Biology.

Developing a radiomics framework for classifying non-small cell lung carcinoma subtypes

NASA Astrophysics Data System (ADS)

Yu, Dongdong; Zang, Yali; Dong, Di; Zhou, Mu; Gevaert, Olivier; Fang, Mengjie; Shi, Jingyun; Tian, Jie

2017-03-01

Patient-targeted treatment of non-small cell lung carcinoma (NSCLC) has been well documented according to the histologic subtypes over the past decade. In parallel, recent development of quantitative image biomarkers has recently been highlighted as important diagnostic tools to facilitate histological subtype classification. In this study, we present a radiomics analysis that classifies the adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). We extract 52-dimensional, CT-based features (7 statistical features and 45 image texture features) to represent each nodule. We evaluate our approach on a clinical dataset including 324 ADCs and 110 SqCCs patients with CT image scans. Classification of these features is performed with four different machine-learning classifiers including Support Vector Machines with Radial Basis Function kernel (RBF-SVM), Random forest (RF), K-nearest neighbor (KNN), and RUSBoost algorithms. To improve the classifiers' performance, optimal feature subset is selected from the original feature set by using an iterative forward inclusion and backward eliminating algorithm. Extensive experimental results demonstrate that radiomics features achieve encouraging classification results on both complete feature set (AUC=0.89) and optimal feature subset (AUC=0.91).

The role of MicroRNA molecules and MicroRNA-regulating machinery in the pathogenesis and progression of epithelial ovarian cancer.

PubMed

Wang, Xiyin; Ivan, Mircea; Hawkins, Shannon M

2017-11-01

MicroRNA molecules are small, single-stranded RNA molecules that function to regulate networks of genes. They play important roles in normal female reproductive tract biology, as well as in the pathogenesis and progression of epithelial ovarian cancer. DROSHA, DICER, and Argonaute proteins are components of the microRNA-regulatory machinery and mediate microRNA production and function. This review discusses aberrant expression of microRNA molecules and microRNA-regulating machinery associated with clinical features of epithelial ovarian cancer. Understanding the regulation of microRNA molecule production and function may facilitate the development of novel diagnostic and therapeutic strategies to improve the prognosis of women with epithelial ovarian cancer. Additionally, understanding microRNA molecules and microRNA-regulatory machinery associations with clinical features may influence prevention and early detection efforts. Copyright © 2017 Elsevier Inc. All rights reserved.

Evolution, functions, and mysteries of plant ARGONAUTE proteins.

PubMed

Zhang, Han; Xia, Rui; Meyers, Blake C; Walbot, Virginia

2015-10-01

ARGONAUTE (AGO) proteins bind small RNAs (sRNAs) to form RNA-induced silencing complexes for transcriptional and post-transcriptional gene silencing. Genomes of primitive plants encode only a few AGO proteins. The Arabidopsis thaliana genome encodes ten AGO proteins, designated AGO1 to AGO10. Most early studies focused on these ten proteins and their interacting sRNAs. AGOs in other flowering plant species have duplicated and diverged from this set, presumably corresponding to new, diverged or specific functions. Among these, the grass-specific AGO18 family has been discovered and implicated as playing important roles during plant reproduction and viral defense. This review covers our current knowledge about functions and features of AGO proteins in both eudicots and monocots and compares their similarities and differences. On the basis of these features, we propose a new nomenclature for some plant AGOs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

PubMed Central

2013-01-01

Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks. PMID:24006890

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

G Protein-Coupled Receptor Rhodopsin: A Prospectus

PubMed Central

Filipek, Sławomir; Stenkamp, Ronald E.; Teller, David C.; Palczewski, Krzysztof

2006-01-01

Rhodopsin is a retinal photoreceptor protein of bipartite structure consisting of the transmembrane protein opsin and a light-sensitive chromophore 11-cis-retinal, linked to opsin via a protonated Schiff base. Studies on rhodopsin have unveiled many structural and functional features that are common to a large and pharmacologically important group of proteins from the G protein-coupled receptor (GPCR) superfamily, of which rhodopsin is the best-studied member. In this work, we focus on structural features of rhodopsin as revealed by many biochemical and structural investigations. In particular, the high-resolution structure of bovine rhodopsin provides a template for understanding how GPCRs work. We describe the sensitivity and complexity of rhodopsin that lead to its important role in vision. PMID:12471166

Walking and Walkability: Is Wayfinding a Missing Link? Implications for Public Health Practice.

PubMed

Vandenberg, Ann E; Hunter, Rebecca H; Anderson, Lynda A; Bryant, Lucinda L; Hooker, Steven P; Satariano, William A

2016-02-01

Research on walking and walkability has yet to focus on wayfinding, the interactive, problem-solving process by which people use environmental information to locate themselves and navigate through various settings. We reviewed the literature on outdoor pedestrian-oriented wayfinding to examine its relationship to walking and walkability, 2 areas of importance to physical activity promotion. Our findings document that wayfinding is cognitively demanding and can compete with other functions, including walking itself. Moreover, features of the environment can either facilitate or impede wayfinding, just as environmental features can influence walking. Although there is still much to be learned about wayfinding and walking behaviors, our review helps frame the issues and lays out the importance of this area of research and practice.

Eukaryotic genes of archaebacterial origin are more important than the more numerous eubacterial genes, irrespective of function.

PubMed

Cotton, James A; McInerney, James O

2010-10-05

The traditional tree of life shows eukaryotes as a distinct lineage of living things, but many studies have suggested that the first eukaryotic cells were chimeric, descended from both Eubacteria (through the mitochondrion) and Archaebacteria. Eukaryote nuclei thus contain genes of both eubacterial and archaebacterial origins, and these genes have different functions within eukaryotic cells. Here we report that archaebacterium-derived genes are significantly more likely to be essential to yeast viability, are more highly expressed, and are significantly more highly connected and more central in the yeast protein interaction network. These findings hold irrespective of whether the genes have an informational or operational function, so that many features of eukaryotic genes with prokaryotic homologs can be explained by their origin, rather than their function. Taken together, our results show that genes of archaebacterial origin are in some senses more important to yeast metabolism than genes of eubacterial origin. This importance reflects these genes' origin as the ancestral nuclear component of the eukaryotic genome.

Lessons Out-of-School: Boy Scouts, Girl Scouts and 4-H Clubs as Educational Environments.

ERIC Educational Resources Information Center

Kleinfeld, Judith; Shinkwin, Anne

By providing opportunities for closer youth-adult contact, exercising responsibility, performing community service, and learning practical skills, well-functioning youth groups create important educational occasions which are often lacking in school. To point out the overlooked features of traditional youth groups, researchers interviewed and…

Transformation of the Schoolhouse. Annual Report for 1969.

ERIC Educational Resources Information Center

Coughlin, Gaila, Ed.

This report reviews some of the more important educational innovations that have transformed the arrangement of space and design of the schoolhouse environment. Design, structural, and functional features are described for open plan schools (schools without interior walls). Consideration is given to the use of performance specifications in the…

The American University as a Civic Institution.

ERIC Educational Resources Information Center

Stanley, Manfred; And Others

1989-01-01

This Civic Arts Review issue contains an essay by Stanley Manfred titled "The American University as a Civic Institution" which identifies some of the features which have made the contemporary American university a civic institution with important civic functions, and identifies some of the societal contradictions which impede recognition and…

Web OPAC Interfaces: An Overview.

ERIC Educational Resources Information Center

Babu, B. Ramesh; O'Brien, Ann

2000-01-01

Discussion of Web-based online public access catalogs (OPACs) focuses on a review of six Web OPAC interfaces in use in academic libraries in the United Kingdom. Presents a checklist and guidelines of important features and functions that are currently available, including search strategies, access points, display, links, and layout. (Author/LRW)

Children's Daily Routines during Kindergarten Transition

ERIC Educational Resources Information Center

Wildenger, Leah K.; McIntyre, Laura Lee; Fiese, Barbara H.; Eckert, Tanya L.

2008-01-01

Routines are an important feature of family life and functioning in families with young children. Common daily routines such as dinnertime, bedtime, and waking activities are powerful organizers of family behavior and may be instrumental to children and families during times of transition, such as elementary school entry. Daily routines were…

Contextualized Instruction: Teaching Relevant Behaviors in Relevant Contexts.

ERIC Educational Resources Information Center

Reboy, Lisa M.; Semb, George B.

In contextualized instruction, the critical features of a context are considered important for the acquisition and transfer of a skill. Examples of contextualized instruction programs are Functional Context Education (FCE) and Anchored Instruction (AI). FCE involves the teaching of reading and mathematics skills in contexts that are relevant to…

A CsMYB6-CsTRY module regulates fruit trichome initiation in cucumber

USDA-ARS?s Scientific Manuscript database

The epidermal features on the fruits, such as the number and size of trichomes or spines are important fruit quality traits for cucumber production. Little is known about the molecular mechanisms underlying fruit spine formation in cucumber. Here, we reported cloning and functional characterization ...

Properties of language networks and language systems. Comment on "Approaching human language with complex networks" by Cong and Liu

NASA Astrophysics Data System (ADS)

Yu, Shuiyuan; Xu, Chunshan

2014-12-01

Language is generally considered a defining feature of human beings, a key medium for interpersonal communication, a fundamental tool for human thinking and an important vehicle for culture transmission. For the anthropoids to evolve into human being, the emergence of linguistic system is a vital step. Then, how can language serve functions so complicated and so important? To answer this question, it is necessary to probe into a central topic in linguistics: the structure of language, which has been inevitably involved in various fields of linguistic research-the functions of languages, the evolution of languages, the typology of languages, etc.

Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

PubMed

Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

2015-12-01

The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

Acoustic features of objects matched by an echolocating bottlenose dolphin.

PubMed

Delong, Caroline M; Au, Whitlow W L; Lemonds, David W; Harley, Heidi E; Roitblat, Herbert L

2006-03-01

The focus of this study was to investigate how dolphins use acoustic features in returning echolocation signals to discriminate among objects. An echolocating dolphin performed a match-to-sample task with objects that varied in size, shape, material, and texture. After the task was completed, the features of the object echoes were measured (e.g., target strength, peak frequency). The dolphin's error patterns were examined in conjunction with the between-object variation in acoustic features to identify the acoustic features that the dolphin used to discriminate among the objects. The present study explored two hypotheses regarding the way dolphins use acoustic information in echoes: (1) use of a single feature, or (2) use of a linear combination of multiple features. The results suggested that dolphins do not use a single feature across all object sets or a linear combination of six echo features. Five features appeared to be important to the dolphin on four or more sets: the echo spectrum shape, the pattern of changes in target strength and number of highlights as a function of object orientation, and peak and center frequency. These data suggest that dolphins use multiple features and integrate information across echoes from a range of object orientations.

Content management systems and E-commerce: a comparative case study

NASA Astrophysics Data System (ADS)

Al Rasheed, Amal A.; El-Masri, Samir D.

2011-12-01

The need for CMS's to create and edit e-commerce websites has increased with the growing importance of e-commerce. In this paper, the various features essential for e-commerce CMS's are explored. The aim of the paper was to find the best CMS solution for e-commerce which includes the best of both CMS and store management. Accordingly, we conducted a study on three popular open source CMS's for e-commerce: VirtueMart from Joomla!, Ubercart from Drupal, and Magento. We took into account features like hosting and installation, performance, support/community, content management, add on modules and functional features. We concluded with improvements that could be made in order to alleviate problems.

Evaluating, Comparing, and Interpreting Protein Domain Hierarchies

PubMed Central

2014-01-01

Abstract Arranging protein domain sequences hierarchically into evolutionarily divergent subgroups is important for investigating evolutionary history, for speeding up web-based similarity searches, for identifying sequence determinants of protein function, and for genome annotation. However, whether or not a particular hierarchy is optimal is often unclear, and independently constructed hierarchies for the same domain can often differ significantly. This article describes methods for statistically evaluating specific aspects of a hierarchy, for probing the criteria underlying its construction and for direct comparisons between hierarchies. Information theoretical notions are used to quantify the contributions of specific hierarchical features to the underlying statistical model. Such features include subhierarchies, sequence subgroups, individual sequences, and subgroup-associated signature patterns. Underlying properties are graphically displayed in plots of each specific feature's contributions, in heat maps of pattern residue conservation, in “contrast alignments,” and through cross-mapping of subgroups between hierarchies. Together, these approaches provide a deeper understanding of protein domain functional divergence, reveal uncertainties caused by inconsistent patterns of sequence conservation, and help resolve conflicts between competing hierarchies. PMID:24559108

CpG islands: algorithms and applications in methylation studies.

PubMed

Zhao, Zhongming; Han, Leng

2009-05-15

Methylation occurs frequently at 5'-cytosine of the CpG dinucleotides in vertebrate genomes; however, this epigenetic feature is rarely observed in CpG islands (CGIs) or CpG clusters in the promoter regions of genes. Aberrant methylation of the promoter-associated CGIs might influence gene expression and cause carcinogenesis. Because of the functional importance, multiple algorithms have been available for identifying CGIs in a genome or a sequence. They can be categorized into the traditional algorithms (e.g., Gardiner-Garden and Frommer (1987), Takai and Jones (2002), and CpGPRoD (2002)) or statistical property based algorithms (CpGcluster (2006) and CG cluster (2007)). We reviewed the features of these algorithms and evaluated their performance on identifying functional CGIs using genome-wide methylation data. Moreover, identification of CGIs is an initial step in many recent studies for predicting methylation status as well as in the design of methylation detection platforms. We reviewed the benchmarks and features used in these studies.

An approach based on wavelet analysis for feature extraction in the a-wave of the electroretinogram.

PubMed

Barraco, R; Persano Adorno, D; Brai, M

2011-12-01

Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time-frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathological case, shift toward lower values and change their times of occurrence. The present findings are a first step toward a deeper understanding of the features of the a-wave and possible applications to diagnostic procedures in order to recognise incipient photoreceptoral pathologies. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Adaptive multiscale processing for contrast enhancement

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.

1993-07-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Targeting and assembly of components of the TOC protein import complex at the chloroplast outer envelope membrane

PubMed Central

Richardson, Lynn G. L.; Paila, Yamuna D.; Siman, Steven R.; Chen, Yi; Smith, Matthew D.; Schnell, Danny J.

2014-01-01

The translocon at the outer envelope membrane of chloroplasts (TOC) initiates the import of thousands of nuclear encoded preproteins required for chloroplast biogenesis and function. The multimeric TOC complex contains two GTP-regulated receptors, Toc34 and Toc159, which recognize the transit peptides of preproteins and initiate protein import through a β–barrel membrane channel, Toc75. Different isoforms of Toc34 and Toc159 assemble with Toc75 to form structurally and functionally diverse translocons, and the composition and levels of TOC translocons is required for the import of specific subsets of coordinately expressed proteins during plant growth and development. Consequently, the proper assembly of the TOC complexes is key to ensuring organelle homeostasis. This review will focus on our current knowledge of the targeting and assembly of TOC components to form functional translocons at the outer membrane. Our analyses reveal that the targeting of TOC components involves elements common to the targeting of other outer membrane proteins, but also include unique features that appear to have evolved to specifically facilitate assembly of the import apparatus. PMID:24966864

Targeting and assembly of components of the TOC protein import complex at the chloroplast outer envelope membrane.

PubMed

Richardson, Lynn G L; Paila, Yamuna D; Siman, Steven R; Chen, Yi; Smith, Matthew D; Schnell, Danny J

2014-01-01

The translocon at the outer envelope membrane of chloroplasts (TOC) initiates the import of thousands of nuclear encoded preproteins required for chloroplast biogenesis and function. The multimeric TOC complex contains two GTP-regulated receptors, Toc34 and Toc159, which recognize the transit peptides of preproteins and initiate protein import through a β-barrel membrane channel, Toc75. Different isoforms of Toc34 and Toc159 assemble with Toc75 to form structurally and functionally diverse translocons, and the composition and levels of TOC translocons is required for the import of specific subsets of coordinately expressed proteins during plant growth and development. Consequently, the proper assembly of the TOC complexes is key to ensuring organelle homeostasis. This review will focus on our current knowledge of the targeting and assembly of TOC components to form functional translocons at the outer membrane. Our analyses reveal that the targeting of TOC components involves elements common to the targeting of other outer membrane proteins, but also include unique features that appear to have evolved to specifically facilitate assembly of the import apparatus.

The Fisher-Markov selector: fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data.

PubMed

Cheng, Qiang; Zhou, Hongbo; Cheng, Jie

2011-06-01

Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and contain significant noise, missing components, or outliers. Existing methods either cannot handle high-dimensional data efficiently or scalably, or can only obtain local optimum instead of global optimum. Toward the selection of the globally optimal subset of features efficiently, we introduce a new selector--which we call the Fisher-Markov selector--to identify those features that are the most useful in describing essential differences among the possible groups. In particular, in this paper we present a way to represent essential discriminating characteristics together with the sparsity as an optimization objective. With properly identified measures for the sparseness and discriminativeness in possibly high-dimensional settings, we take a systematic approach for optimizing the measures to choose the best feature subset. We use Markov random field optimization techniques to solve the formulated objective functions for simultaneous feature selection. Our results are noncombinatorial, and they can achieve the exact global optimum of the objective function for some special kernels. The method is fast; in particular, it can be linear in the number of features and quadratic in the number of observations. We apply our procedure to a variety of real-world data, including mid--dimensional optical handwritten digit data set and high-dimensional microarray gene expression data sets. The effectiveness of our method is confirmed by experimental results. In pattern recognition and from a model selection viewpoint, our procedure says that it is possible to select the most discriminating subset of variables by solving a very simple unconstrained objective function which in fact can be obtained with an explicit expression.

The intriguing nature of dorsal root ganglion neurons: linking structure with polarity and function.

PubMed

Nascimento, Ana Isabel; Mar, Fernando Milhazes; Sousa, Mónica Mendes

2018-05-02

Dorsal root ganglion (DRG) neurons are the first neurons of the sensory pathway. They are activated by a variety of sensory stimuli that are then transmitted to the central nervous system. An important feature of DRG neurons is their unique morphology where a single process -the stem axon- bifurcates into a peripheral and a central axonal branch, with different functions and cellular properties. Distinctive structural aspects of the two DRG neuron branches may have important implications for their function in health and disease. However, the link between DRG axonal branch structure, polarity and function has been largely neglected in the field, and relevant information is rather scattered across the literature. In particular, ultrastructural differences between the two axonal branches are likely to account for the higher transport and regenerative ability of the peripheral DRG neuron axon when compared to the central one. Nevertheless, the cell intrinsic factors contributing to this central-peripheral asymmetry are still unknown. Here we critically review the factors that may underlie the functional asymmetry between the peripheral and central DRG axonal branches. Also, we discuss the hypothesis that DRG neurons may assemble a structure resembling the axon initial segment that may be responsible, at least in part, for their polarity and electrophysiological features. Ultimately, we suggest that the clarification of the axonal ultrastructure of DRG neurons using state-of-the-art techniques will be crucial to understand the physiology of this peculiar cell type. Copyright © 2018. Published by Elsevier Ltd.

Rhodium-catalyzed C-H alkynylation of arenes at room temperature.

PubMed

Feng, Chao; Loh, Teck-Peng

2014-03-03

The rhodium(III)-catalyzed ortho C-H alkynylation of non-electronically activated arenes is disclosed. This process features a straightforward and highly effective protocol for the synthesis of functionalized alkynes and represents the first example of merging a hypervalent iodine reagent with rhodium(III) catalysis. Notably, this reaction proceeds at room temperature, tolerates a variety of functional groups, and more importantly, exhibits high selectivity for monoalkynylation. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effects of Spatial and Feature Attention on Disparity-Rendered Structure-From-Motion Stimuli in the Human Visual Cortex

PubMed Central

Ip, Ifan Betina; Bridge, Holly; Parker, Andrew J.

2014-01-01

An important advance in the study of visual attention has been the identification of a non-spatial component of attention that enhances the response to similar features or objects across the visual field. Here we test whether this non-spatial component can co-select individual features that are perceptually bound into a coherent object. We combined human psychophysics and functional magnetic resonance imaging (fMRI) to demonstrate the ability to co-select individual features from perceptually coherent objects. Our study used binocular disparity and visual motion to define disparity structure-from-motion (dSFM) stimuli. Although the spatial attention system induced strong modulations of the fMRI response in visual regions, the non-spatial system’s ability to co-select features of the dSFM stimulus was less pronounced and variable across subjects. Our results demonstrate that feature and global feature attention effects are variable across participants, suggesting that the feature attention system may be limited in its ability to automatically select features within the attended object. Careful comparison of the task design suggests that even minor differences in the perceptual task may be critical in revealing the presence of global feature attention. PMID:24936974

Human brain distinctiveness based on EEG spectral coherence connectivity.

PubMed

Rocca, D La; Campisi, P; Vegso, B; Cserti, P; Kozmann, G; Babiloni, F; Fallani, F De Vico

2014-09-01

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of the current analyses rely on the extraction of features characterizing the activity of single brain regions, like power spectrum estimation, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherence-based connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N = 108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performance shows that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.5% is obtained in EC (96.26% in EO) when fusing power spectrum information from parieto-occipital (centro-parietal in EO) regions. Taken together, these results suggest that the functional connectivity patterns represent effective features for improving EEG-based biometric systems.

Admixtures in Cement-Matrix Composites for Mechanical Reinforcement, Sustainability, and Smart Features

PubMed Central

Bastos, Guillermo; Patiño-Barbeito, Faustino; Patiño-Cambeiro, Faustino; Armesto, Julia

2016-01-01

For more than a century, several inclusions have been mixed with Portland cement—nowadays the most-consumed construction material worldwide—to improve both the strength and durability required for construction. The present paper describes the different families of inclusions that can be combined with cement matrix and reviews the achievements reported to date regarding mechanical performance, as well as two other innovative functionalities of growing importance: reducing the high carbon footprint of Portland cement, and obtaining new smart features. Nanomaterials stand out in the production of such advanced features, allowing the construction of smart or multi-functional structures by means of thermal- and strain-sensing, and photocatalytic properties. The first self-cleaning concretes (photocatalytic) have reached the markets. In this sense, it is expected that smart concretes will be commercialized to address specialized needs in construction and architecture. Conversely, other inclusions that enhance strength or reduce the environmental impact remain in the research stage, in spite of the promising results reported in these issues. Despite the fact that such functionalities are especially profitable in the case of massive cement consumption, the shift from the deeply established Portland cement to green cements still has to overcome economic, institutional, and technical barriers. PMID:28774091

Contribution of Insula in Parkinson’s Disease: A Quantitative Meta-Analysis Study

PubMed Central

Criaud, Marion; Christopher, Leigh; Boulinguez, Philippe; Ballanger, Benedicte; Lang, Anthony E.; Cho, Sang S.; Houle, Sylvain; Strafella, Antonio P.

2016-01-01

The insula region is known to be an integrating hub interacting with multiple brain networks involved in cognitive, affective, sensory, and autonomic processes. There is growing evidence suggesting that this region may have an important role in Parkinson’s disease (PD). Thus, to investigate the functional organization of the insular cortex and its potential role in parkinsonian features, we used a coordinate-based quantitative meta-analysis approach, the activation likelihood estimation. A total of 132 insular foci were selected from 96 published experiments comprising the five functional categories: cognition, affective/behavioral symptoms, bodily awareness/autonomic function, sensorimotor function, and nonspecific resting functional changes associated with the disease. We found a significant convergence of activation maxima related to PD in different insular regions including anterior and posterior regions bilaterally. This study provides evidence of an important functional distribution of different domains within the insular cortex in PD, particularly in relation to nonmotor aspects, with an influence of medication effect. PMID:26800238

Contribution of insula in Parkinson's disease: A quantitative meta-analysis study.

PubMed

Criaud, Marion; Christopher, Leigh; Boulinguez, Philippe; Ballanger, Benedicte; Lang, Anthony E; Cho, Sang S; Houle, Sylvain; Strafella, Antonio P

2016-04-01

The insula region is known to be an integrating hub interacting with multiple brain networks involved in cognitive, affective, sensory, and autonomic processes. There is growing evidence suggesting that this region may have an important role in Parkinson's disease (PD). Thus, to investigate the functional organization of the insular cortex and its potential role in parkinsonian features, we used a coordinate-based quantitative meta-analysis approach, the activation likelihood estimation. A total of 132 insular foci were selected from 96 published experiments comprising the five functional categories: cognition, affective/behavioral symptoms, bodily awareness/autonomic function, sensorimotor function, and nonspecific resting functional changes associated with the disease. We found a significant convergence of activation maxima related to PD in different insular regions including anterior and posterior regions bilaterally. This study provides evidence of an important functional distribution of different domains within the insular cortex in PD, particularly in relation to nonmotor aspects, with an influence of medication effect. © 2016 Wiley Periodicals, Inc.

Diagnostic specificity of poor premorbid adjustment: comparison of schizophrenia, schizoaffective disorder, and mood disorder with psychotic features.

PubMed

Tarbox, Sarah I; Brown, Leslie H; Haas, Gretchen L

2012-10-01

Individuals with schizophrenia have significant deficits in premorbid social and academic adjustment compared to individuals with non-psychotic diagnoses. However, it is unclear how severity and developmental trajectory of premorbid maladjustment compare across psychotic disorders. This study examined the association between premorbid functioning (in childhood, early adolescence, and late adolescence) and psychotic disorder diagnosis in a first-episode sample of 105 individuals: schizophrenia (n=68), schizoaffective disorder (n=22), and mood disorder with psychotic features (n=15). Social and academic maladjustment was assessed using the Cannon-Spoor Premorbid Adjustment Scale. Worse social functioning in late adolescence was associated with higher odds of schizophrenia compared to odds of either schizoaffective disorder or mood disorder with psychotic features, independently of child and early adolescent maladjustment. Greater social dysfunction in childhood was associated with higher odds of schizoaffective disorder compared to odds of schizophrenia. Premorbid decline in academic adjustment was observed for all groups, but did not predict diagnosis at any stage of development. Results suggest that social functioning is disrupted in the premorbid phase of both schizophrenia and schizoaffective disorder, but remains fairly stable in mood disorders with psychotic features. Disparities in the onset and time course of social dysfunction suggest important developmental differences between schizophrenia and schizoaffective disorder. Copyright © 2012 Elsevier B.V. All rights reserved.

Speech, Voice, and Communication.

PubMed

Johnson, Julia A

2017-01-01

Communication changes are an important feature of Parkinson's and include both motor and nonmotor features. This chapter will cover briefly the motor features affecting speech production and voice function before focusing on the nonmotor aspects. A description of the difficulties experienced by people with Parkinson's when trying to communicate effectively is presented along with some of the assessment tools and therapists' treatment options. The idea of clinical heterogeneity of PD and subtyping patients with different communication problems is explored and suggestions are made on how this may influence clinicians' treatment methods and choices so as to provide personalized therapy programmes. The importance of encouraging and supporting people to maintain social networks, employment, and leisure activities is stated as the key to achieving sustainability. Finally looking into the future, the emergence of new technologies is seen as providing further possibilities to support therapists in the goal of helping people with Parkinson's to maintain good communication skills throughout the course of the disease. © 2017 Elsevier Inc. All rights reserved.

Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro-connectome, particularly in the context of data fusion.

Glycosyltransferase-mediated Sweet Modification in Oral Streptococci.

PubMed

Zhu, F; Zhang, H; Wu, H

2015-05-01

Bacterial glycosyltransferases play important roles in bacterial fitness and virulence. Oral streptococci have evolved diverse strategies to survive and thrive in the carbohydrate-rich oral cavity. In this review, we discuss 2 important biological processes mediated by 2 distinct groups of glycosyltransferases in oral streptococci that are important for bacterial colonization and virulence. The first process is the glycosylation of highly conserved serine-rich repeat adhesins by a series of glycosyltransferases. Using Streptococcus parasanguinis as a model, we highlight new features of several glycosyltransferases that sequentially modify the serine-rich glycoprotein Fap1. Distinct features of a novel glycosyltransferase fold from a domain of unknown function 1792 are contrasted with common properties of canonical glycosyltransferases. The second biological process we cover is involved in building sticky glucan matrix to establish cariogenic biofilms by an important opportunistic pathogen Streptococcus mutans through the action of a family of 3 glucosyltransferases. We focus on discussing the structural feature of this family as a glycoside hydrolase family of enzymes. While the 2 processes are distinct, they all produce carbohydrate-coated biomolecules, which enable bacteria to stick better in the complex oral microbiome. Understanding the making of the sweet modification presents a unique opportunity to develop novel antiadhesion and antibiofilm strategies to fight infections by oral streptococci and beyond. © International & American Associations for Dental Research 2015.

Glycosyltransferase-mediated Sweet Modification in Oral Streptococci

PubMed Central

Zhu, F.; Zhang, H.

2015-01-01

Bacterial glycosyltransferases play important roles in bacterial fitness and virulence. Oral streptococci have evolved diverse strategies to survive and thrive in the carbohydrate-rich oral cavity. In this review, we discuss 2 important biological processes mediated by 2 distinct groups of glycosyltransferases in oral streptococci that are important for bacterial colonization and virulence. The first process is the glycosylation of highly conserved serine-rich repeat adhesins by a series of glycosyltransferases. Using Streptococcus parasanguinis as a model, we highlight new features of several glycosyltransferases that sequentially modify the serine-rich glycoprotein Fap1. Distinct features of a novel glycosyltransferase fold from a domain of unknown function 1792 are contrasted with common properties of canonical glycosyltransferases. The second biological process we cover is involved in building sticky glucan matrix to establish cariogenic biofilms by an important opportunistic pathogen Streptococcus mutans through the action of a family of 3 glucosyltransferases. We focus on discussing the structural feature of this family as a glycoside hydrolase family of enzymes. While the 2 processes are distinct, they all produce carbohydrate-coated biomolecules, which enable bacteria to stick better in the complex oral microbiome. Understanding the making of the sweet modification presents a unique opportunity to develop novel antiadhesion and antibiofilm strategies to fight infections by oral streptococci and beyond. PMID:25755271

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

PubMed

Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

2017-02-01

Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

Undefined freeform surfaces having deterministic structure: issues of their characterization for functionality and manufacture

NASA Astrophysics Data System (ADS)

Whitehouse, David J.

2016-09-01

There is an increasing use of surfaces which have structure, an increase in the use of freeform surfaces, and most importantly an increase in the number of surfaces having both characteristics. These can be called multi-function surfaces, where more than one function is helped by the geometrical features: the structure can help one, the freeform another. Alternatively, they can be complementary to optimize a single function, but in all cases both geometries are involved. This paper examines some of the problems posed by having such disparate geometries on one surface; in particular, the methods of characterization needed to help understand the functionality and also to some extent their manufacture. This involves investigating ways of expressing how local and global geometric features of undefined freeform surfaces might influence function and how surface structure on top of or in series with the freeform affects the nature of the characterization. Some methods have been found of identifying possible strategies for tackling the characterization problem, based in part on the principles of least action and on the way that nature has solved the marriage of flexible freeform geometry and structure on surfaces.

Aquaporin structure-function relationships: water flow through plant living cells.

PubMed

Zhao, Chang-Xing; Shao, Hong-Bo; Chu, Li-Ye

2008-04-01

Plant aquaporins play an important role in water uptake and movement-an aquaporin that opens and closes a gate that regulates water movement in and out of cells. Some plant aquaporins also play an important role in response to water stress. Since their discovery, advancing knowledge of their structures and properties led to an understanding of the basic features of the water transport mechanism and increased illumination to water relations. Meanwhile, molecular and functional characterization of aquaporins has revealed the significance of their regulation in response to the adverse environments such as salinity and drought. This paper reviews the structure, species diversity, physiology function, regulation of plant aquaporins, and the relations between environmental factors and plant aquaporins. Complete understanding of aquaporin function and regulation is to integrate those mechanisms in time and space and to well regulate the permeation of water across biological membranes under changing environmental and developmental conditions.

A computational prediction of structure and function of novel homologue of Arabidopsis thaliana Vps51/Vps67 subunit in Corchorus olitorius.

PubMed

Zaman, Aubhishek; Fancy, Nurun Nahar

2012-12-01

Vps mediated vesicular transport is important for transferring macromolecules trapped inside a vesicle. Although highly abundant, Vps shows tremendous sequence variation among diverse array of species. However, this difference in sequence, which seems to also translate into substantial functional variation, is hardly characterized in Corchorus spp. Here, our computational study investigates structural and functional features of one of the Vps subunit namely Vps51/Vps67 in C. olitorius. Broad scale structural characterization revealed novel information about the overall Vps structure and binding sites. Moreover, functional analyses indicate interaction partners which were unexplored to date. Since membrane trafficking is essentially associated with nutrient uptake and chemical de-toxification, characterization of the Vps subunit can well provide us with better insight into important agronomic traits such as stress response, immune response and phytoremediation capacity.

Issues related to the detection of boundaries

Treesearch

M.-J. Fortin; Olson; R.J.; S. Ferson; L. Iverson; C. Hunsaker; G. Edwards; D. Levine; K. Butera; V. Klemas; V. Klemas

2000-01-01

Ecotones are inherent features of landscapes, transitional zones, and play more than one functional role in ecosystem dynamics. The delineation of ecotones and environmental boundaries is therefore an important step in land-use management planning. The delineation of ecotones depends on the phenomenon of interest and the statistical methods used as well as the...

Promoting Complex Systems Learning through the Use of Conceptual Representations in Hypermedia

ERIC Educational Resources Information Center

Liu, Lei; Hmelo-Silver, Cindy E.

2009-01-01

Studying complex systems is increasingly important in many science domains. Many features of complex systems make it difficult for students to develop deep understanding. Our previous research indicated that a function-centered conceptual representation is part of the disciplinary toolbox of biologists, suggesting that it is an appropriate…

The Forms and Functions of Impulsive Actions: Implications for Behavioral Assessment and Therapy

ERIC Educational Resources Information Center

Farmer, Richard F.; Golden, Jeannie A.

2009-01-01

Impulsivity is a central defining feature of several psychiatric disorders and a frequent correlate of many forms of psychopathology and maladjustment. Despite recognition of the importance of impulsivity to an understanding of a wide variety of clinically-relevant behaviors, this multifaceted construct remains ill-defined and not well understood.…

Open Source Solutions for Libraries: ABCD vs Koha

ERIC Educational Resources Information Center

Macan, Bojan; Fernandez, Gladys Vanesa; Stojanovski, Jadranka

2013-01-01

Purpose: The purpose of this study is to present an overview of the two open source (OS) integrated library systems (ILS)--Koha and ABCD (ISIS family), to compare their "next-generation library catalog" functionalities, and to give comparison of other important features available through ILS modules. Design/methodology/approach: Two open source…

Psychotherapeutic Function of the Kazakh Traditional Music

ERIC Educational Resources Information Center

Shakerimova, Zere S.; Nussupova, Aizada S.; Burambaeva, Maryam N.; Yermanov, Zhanat R.; Emreyeva, Akmaral E.; Janseitova, Sveta S.

2016-01-01

This article considers the psychotherapeutic parameters of traditional Kazakh music, best practices that were achieved in practical psychology. From the one hand, it allows us to see the music features in a new light, and from the other hand--to identify the ethnic psychology of the Kazakh nation. An important step in the study of the…

A "Bit" of Quantum Mechanics

ERIC Educational Resources Information Center

Oss, Stefano; Rosi, Tommaso

2015-01-01

We have developed an app for iOS-based smart-phones/tablets that allows a 3-D, complex phase-based colorful visualization of hydrogen atom wave functions. Several important features of the quantum behavior of atomic orbitals can easily be made evident, thus making this app a useful companion in introductory modern physics classes. There are many…

Web Design Matters

ERIC Educational Resources Information Center

Mathews, Brian

2009-01-01

The web site is a library's most important feature. Patrons use the web site for numerous functions, such as renewing materials, placing holds, requesting information, and accessing databases. The homepage is the place they turn to look up the hours, branch locations, policies, and events. Whether users are at work, at home, in a building, or on…

Family-Based Cognitive-Behavioral Treatments for Suicidal Adolescents and their Integration with Individual Treatment

ERIC Educational Resources Information Center

Wells, Karen C.; Heilbron, Nicole

2012-01-01

A considerable research base underscores the importance of family functioning in the risk for and treatment of adolescent suicidal thoughts and behaviors. This paper reviews the extant empirical literature documenting associations between features of the family context and adolescent suicidal thoughts and behaviors. A case example is provided to…

An Examination of the Association of African American Mothers' Perceptions of Their Neighborhoods with Their Parenting and Adolescent Adjustment.

ERIC Educational Resources Information Center

Taylor, Ronald D.

2000-01-01

Investigated links between African American mothers' perceptions of their urban neighborhoods and adjustment of their adolescents. Interview data indicated that important features of neighborhoods (crime, physical deterioration, and resource availability) measured through mothers' reports related to adolescent functioning and mothers' parenting…

Old-growth forests in the Southwest and Rocky Mountain Regions - Proceedings of a workshop

Treesearch

Merrill R. Kaufman; W. H. Moir; Richard L. Bassett

1992-01-01

This paper reviews the science and management of old-growth forests and summarizes discussions among 30 participants at a workshop in Portal, Arizona, March 9-13, 1992. Concepts of old-growth forests - the perceptions, values, definitions, characteristic features, ecological functions, and landscape importance - vary widely. Because concepts are complex,...

Heterogeneous patterns of brain atrophy in Alzheimer's disease.

PubMed

Poulakis, Konstantinos; Pereira, Joana B; Mecocci, Patrizia; Vellas, Bruno; Tsolaki, Magda; Kłoszewska, Iwona; Soininen, Hilkka; Lovestone, Simon; Simmons, Andrew; Wahlund, Lars-Olof; Westman, Eric

2018-05-01

There is increasing evidence showing that brain atrophy varies between patients with Alzheimer's disease (AD), suggesting that different anatomical patterns might exist within the same disorder. We investigated AD heterogeneity based on cortical and subcortical atrophy patterns in 299 AD subjects from 2 multicenter cohorts. Clusters of patients and important discriminative features were determined using random forest pairwise similarity, multidimensional scaling, and distance-based hierarchical clustering. We discovered 2 typical (72.2%) and 3 atypical (28.8%) subtypes with significantly different demographic, clinical, and cognitive characteristics, and different rates of cognitive decline. In contrast to previous studies, our unsupervised random forest approach based on cortical and subcortical volume measures and their linear and nonlinear interactions revealed more typical AD subtypes with important anatomically discriminative features, while the prevalence of atypical cases was lower. The hippocampal-sparing and typical AD subtypes exhibited worse clinical progression in visuospatial, memory, and executive cognitive functions. Our findings suggest there is substantial heterogeneity in AD that has an impact on how patients function and progress over time. Copyright © 2018 Elsevier Inc. All rights reserved.

Cross-cultural differences in preference for recovery of mobility among spinal cord injury rehabilitation professionals.

PubMed

Ditunno, P L; Patrick, M; Stineman, M; Morganti, B; Townson, A F; Ditunno, J F

2006-09-01

Direct observation of a constrained consensus-building process in three culturally independent five-person panels of rehabilitation professionals from the US, Italy and Canada. To illustrate cultural differences in belief among rehabilitation professionals about the relative importance of alternative functional goals during spinal cord injury (SCI) rehabilitation. Spinal Cord Injury Units in Philadelphia-USA, Rome-Italy and Vancouver-Canada. Each of the three panels came to independent consensus about recovery priorities in SCI utilizing the features resource trade-off game. The procedure involves trading imagined levels of independence (resources) across different functional items (features) assuming different stages of recovery. Sphincter management was of primary importance to all three groups. The Italian and Canadian rehabilitation professionals, however, showed preference for walking over wheelchair mobility at lower stages of assumed recovery, whereas the US professionals set wheelchair independence at a higher priority than walking. These preliminary results suggest cross-cultural recovery priority differences among SCI rehabilitation professionals. These dissimilarities in preference may reflect disparities in values, cultural expectations and health care policies.

Cultured bovine granulosa cells rapidly lose important features of their identity and functionality but partially recover under long-term culture conditions.

PubMed

Yenuganti, Vengala Rao; Vanselow, Jens

2017-05-01

Cell culture models are essential for the detailed study of molecular processes. We analyze the dynamics of changes in a culture model of bovine granulosa cells. The cells were cultured for up to 8 days and analyzed for steroid production and gene expression. According to the expression of the marker genes CDH1, CDH2 and VIM, the cells maintained their mesenchymal character throughout the time of culture. In contrast, the levels of functionally important transcripts and of estradiol and progesterone production were rapidly down-regulated but showed a substantial up-regulation from day 4. FOXL2, a marker for granulosa cell identity, was also rapidly down-regulated after plating but completely recovered towards the end of culture. In contrast, expression of the Sertoli cell marker SOX9 and the lesion/inflammation marker PTGS2 increased during the first 2 days after plating but gradually decreased later on. We conclude that only long-term culture conditions (>4 days) allow the cells to recover from plating stress and to re-acquire characteristic granulosa cell features.

The importance of becoming double-stranded: Innate immunity and the kinetic model of HIV-1 central plus strand synthesis

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

Poeschla, Eric, E-mail: poeschla.eric@mayo.edu

Central initiation of plus strand synthesis is a conserved feature of lentiviruses and certain other retroelements. This complication of the standard reverse transcription mechanism produces a transient “central DNA flap” in the viral cDNA, which has been proposed to mediate its subsequent nuclear import. This model has assumed that the important feature is the flapped DNA structure itself rather than the process that produces it. Recently, an alternative kinetic model was proposed. It posits that central plus strand synthesis functions to accelerate conversion to the double-stranded state, thereby helping HIV-1 to evade single-strand DNA-targeting antiviral restrictions such as APOBEC3 proteins,more » and perhaps to avoid innate immune sensor mechanisms. The model is consistent with evidence that lentiviruses must often synthesize their cDNAs when dNTP concentrations are limiting and with data linking reverse transcription and uncoating. There may be additional kinetic advantages for the artificial genomes of lentiviral gene therapy vectors. - Highlights: • Two main functional models for HIV central plus strand synthesis have been proposed. • In one, a transient central DNA flap in the viral cDNA mediates HIV-1 nuclear import. • In the other, multiple kinetic consequences are emphasized. • One is defense against APOBEC3G, which deaminates single-stranded DNA. • Future questions pertain to antiviral restriction, uncoating and nuclear import.« less

Biological features of hepatitis B virus isolates from patients based on full-length genomic analysis.

PubMed

Wen, Yu-Mei; Wang, Yong-Xiang

2009-01-01

The mechanisms for HBV persistence and the pathogenesis of chronic HB have been shown mainly due to defects in host immune responses. However, HBV isolates with different biological features may also contribute to different clinical outcomes and epidemiological implications in viral hepatitis B (HB). This review presents interesting biological features of HBV isolates based on the structural and functional analysis of full-length HBV isolates from various patients. Among isolates from children after failure of HB vaccination, 129L mutant at the 'a' determinant was found with normal binding efficiency to anti-HBs, but with reduced immunogenicity, which could initiate persistent HBV infections. Isolates from fulminant hepatitis (FH) B patients were not all highly replicative, but differences in capacities of anti-HBs induction could be involved in the pathogenesis of FH. The high replicative competency of isolates from hepatocellular carcinoma (HCC) patients could result in enhanced immune-mediated cytopathic effects against HBV viral proteins, and increased transactivating activity by the X protein. The mechanism of a double-spliced variant in enhancing replication of the wild-type virus is presented. The importance of integrating structural and functional analysis to reveal biological features of HBV isolates in viral pathogenesis is discussed.

A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram.

PubMed

Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei

2016-05-09

Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD) systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG) is a proven biosignal that accurately and simultaneously reflects human's biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD) using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.

Imaging of Myocardial Fatty Acid Oxidation

PubMed Central

Mather, Kieren J; DeGrado, Tim

2016-01-01

Myocardial fuel selection is a key feature of the health and function of the heart, with clear links between myocardial function and fuel selection and important impacts of fuel selection on ischemia tolerance. Radiopharmaceuticals provide uniquely valuable tools for in vivo, non-invasive assessment of these aspects of cardiac function and metabolism. Here we review the landscape of imaging probes developed to provide noninvasive assessment of myocardial fatty acid oxidation (MFAO). Also, we review the state of current knowledge that myocardial fatty acid imaging has helped establish of static and dynamic fuel selection that characterizes cardiac and cardiometabolic disease and the interplay between fuel selection and various aspects of cardiac function. PMID:26923433

A model of the extent and distribution of woody linear features in rural Great Britain.

PubMed

Scholefield, Paul; Morton, Dan; Rowland, Clare; Henrys, Peter; Howard, David; Norton, Lisa

2016-12-01

Hedges and lines of trees (woody linear features) are important boundaries that connect and enclose habitats, buffer the effects of land management, and enhance biodiversity in increasingly impoverished landscapes. Despite their acknowledged importance in the wider countryside, they are usually not considered in models of landscape function due to their linear nature and the difficulties of acquiring relevant data about their character, extent, and location. We present a model which uses national datasets to describe the distribution of woody linear features along boundaries in Great Britain. The method can be applied for other boundary types and in other locations around the world across a range of spatial scales where different types of linear feature can be separated using characteristics such as height or width. Satellite-derived Land Cover Map 2007 (LCM2007) provided the spatial framework for locating linear features and was used to screen out areas unsuitable for their occurrence, that is, offshore, urban, and forest areas. Similarly, Ordnance Survey Land-Form PANORAMA®, a digital terrain model, was used to screen out where they do not occur. The presence of woody linear features on boundaries was modelled using attributes from a canopy height dataset obtained by subtracting a digital terrain map (DTM) from a digital surface model (DSM). The performance of the model was evaluated against existing woody linear feature data in Countryside Survey across a range of scales. The results indicate that, despite some underestimation, this simple approach may provide valuable information on the extents and locations of woody linear features in the countryside at both local and national scales.

Integrating depth functions and hyper-scale terrain analysis for 3D soil organic carbon modeling in agricultural fields at regional scale

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.

2012-04-01

Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of different depth functions, ii. The use of different machine learning approaches for modeling the parameters of the fitted depth functions using the ConMap features and iii. The influence of different spatial scales on the SOC profile distribution variability. Keywords: 3D modeling, Digital soil mapping, Depth functions, Terrain analysis. Reference Behrens, T., K. Schmidt, K., Zhu, A.X. Scholten, T. 2010. The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science, v. 61, p.133-143.

Parametric dictionary learning for modeling EAP and ODF in diffusion MRI.

PubMed

Merlet, Sylvain; Caruyer, Emmanuel; Deriche, Rachid

2012-01-01

In this work, we propose an original and efficient approach to exploit the ability of Compressed Sensing (CS) to recover diffusion MRI (dMRI) signals from a limited number of samples while efficiently recovering important diffusion features such as the ensemble average propagator (EAP) and the orientation distribution function (ODF). Some attempts to sparsely represent the diffusion signal have already been performed. However and contrarly to what has been presented in CS dMRI, in this work we propose and advocate the use of a well adapted learned dictionary and show that it leads to a sparser signal estimation as well as to an efficient reconstruction of very important diffusion features. We first propose to learn and design a sparse and parametric dictionary from a set of training diffusion data. Then, we propose a framework to analytically estimate in closed form two important diffusion features: the EAP and the ODF. Various experiments on synthetic, phantom and human brain data have been carried out and promising results with reduced number of atoms have been obtained on diffusion signal reconstruction, thus illustrating the added value of our method over state-of-the-art SHORE and SPF based approaches.

Feature integration and spatial attention: common processes for endogenous and exogenous orienting.

PubMed

Henderickx, David; Maetens, Kathleen; Soetens, Eric

2010-05-01

Briand (J Exp Psychol Hum Percept Perform 24:1243-1256, 1998) and Briand and Klein (J Exp Psychol Hum Percept Perform 13:228-241, 1987) demonstrated that spatial cueing effects are larger for detecting conjunction of features than for detecting simple features when spatial attention is oriented exogenously, and not when attention is oriented endogenously. Their results were interpreted as if only exogenous attention affects the posterior spatial attention system that performs the feature binding function attributed to spatial attention by Treisman's feature integration theory (FIT; 1980). In a series of 6 experiments, we attempted to replicate Briand's findings. Manipulations of distractor string size and symmetry of stimulus presentation left and right from fixation were implemented in Posner's cueing paradigm. The data indicate that both exogenous and endogenous cueing address the same attentional mechanism needed for feature binding. The results also limit the generalisability of Briand's proposal concerning the role of exogenous attention in feature integration. Furthermore, the importance to control the effect of unintended attentional capture in a cueing task is demonstrated.

What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study

PubMed Central

Chien, Yu-Tai; Chen, Yu-Jen; Hsiung, Hsiao-Fang; Chen, Hsiao-Jung; Hsieh, Meng-Hua; Wu, Wen-Jie

2017-01-01

Background Physical activity is important for middle-agers to maintain health both in middle age and in old age. Although thousands of exercise-promotion mobile phone apps are available for download, current literature offers little understanding regarding which design features can enhance middle-aged adults’ quality perception toward exercise-promotion apps and which factor may influence such perception. Objectives The aims of this study were to understand (1) which design features of exercise-promotion apps can enhance quality perception of middle-agers, (2) whether their needs are matched by current functions offered in app stores, and (3) whether physical activity (PA) and mobile phone self-efficacy (MPSE) influence quality perception. Methods A total of 105 middle-agers participated and filled out three scales: the International Physical Activity Questionnaire (IPAQ), the MPSE scale, and the need for design features questionnaire. The design features were developed based on the Coventry, Aberdeen, and London—Refined (CALO-RE) taxonomy. Following the Kano quality model, the need for design features questionnaire asked participants to classify design features into five categories: attractive, one-dimensional, must-be, indifferent, and reverse. The quality categorization was conducted based on a voting approach and the categorization results were compared with the findings of a prevalence study to realize whether needs match current availability. In total, 52 multinomial logistic regression models were analyzed to evaluate the effects of PA level and MPSE on quality perception of design features. Results The Kano analysis on the total sample revealed that visual demonstration of exercise instructions is the only attractive design feature, whereas the other 51 design features were perceived with indifference. Although examining quality perception by PA level, 21 features are recommended to low level, 6 features to medium level, but none to high-level PA. In contrast, high-level MPSE is recommended with 14 design features, medium level with 6 features, whereas low-level participants are recommended with 1 feature. The analysis suggests that the implementation of demanded features could be low, as the average prevalence of demanded design features is 20% (4.3/21). Surprisingly, social comparison and social support, most implemented features in current apps, were categorized into the indifferent category. The magnitude of effect is larger for MPSE because it effects quality perception of more design features than PA. Delving into the 52 regression models revealed that high MPSE more likely induces attractive or one- dimensional categorization, suggesting the importance of technological self-efficacy on eHealth care promotion. Conclusions This study is the first to propose middle-agers’ needs in relation to mobile phone exercise-promotion. In addition to the tailor-made recommendations, suggestions are offered to app designers to enhance the performance of persuasive features. An interesting finding on change of quality perception attributed to MPSE is proposed as future research. PMID:28546140

Association of Left Atrial Function and Left Atrial Enhancement in Patients with Atrial Fibrillation: A Cardiac Magnetic Resonance Study

PubMed Central

Habibi, Mohammadali; Lima, Joao A.C.; Khurram, Irfan M.; Zimmerman, Stefan L.; Zipunnikov, Vadim; Fukumoto, Kotaro; Spragg, David; Ashikaga, Hiroshi; Rickard, John; Marine, Joseph E.; Calkins, Hugh; Nazarian, Saman

2015-01-01

Background Atrial fibrillation (AF) is associated with left atrial (LA) structural and functional changes. Cardiac magnetic resonance (CMR) late gadolinium enhancement (LGE) and feature-tracking are capable of noninvasive quantification of LA fibrosis and myocardial motion, respectively. We sought to examine the association of phasic LA function with LA enhancement in patients with AF. Methods and Results LA structure and function was measured in 90 AF patients (age 61 ± 10 years, 76% male) referred for ablation and 14 healthy volunteers. Peak global longitudinal LA strain (PLAS), LA systolic strain rate (SR-s), and early (SR-ed) and late diastolic (SR-ld) strain rates were measured using cine-CMR images acquired during sinus rhythm. The degree of LGE was quantified. Compared to patients with paroxysmal AF (60% of cohort), those with persistent AF had larger maximum LA volume index (LAVImax, 56 ± 17ml/m2 versus 49 ± 13ml/m2 p=0.036), and increased LGE (27.1± 11.7% versus 36.8 ± 14.8% p<0.001). Aside from LA active emptying fraction, all LA parameters (passive emptying fraction, PLAS, SR-s, SR-ed and SR-ld) were lower in patients with persistent AF (p< 0.05 for all). Healthy volunteers had less LGE and higher LA functional parameters compared to AF patients (p<0.05 for all). In multivariable analysis, increased LGE was associated with lower LA passive emptying fraction, PLAS, SR-s, SR-ed, and SR-ld (p<0.05 for all). Conclusions Increased LA enhancement is associated with decreased LA reservoir, conduit, and booster pump functions. Phasic measurement of LA function using feature-tracking CMR may add important information regarding the physiological importance of LA fibrosis. PMID:25652181

Incorporating metals into de novo proteins.

PubMed

Peacock, Anna F A

2013-12-01

The de novo design of artificial metalloproteins from first-principles is a powerful strategy with which to establish the minimum structure required for function, as well as to identify the important design features for tuning the chemistry of the coordinated metal ion. Herein we describe recent contributions to this field, covering metallo-porphyrin, mononuclear and multinuclear metal ion sites engineered into de novo proteins. Using miniature artificial scaffolds these examples demonstrate that complex natural protein folds are not required to mimic naturally occurring metal ion sites in proteins. More importantly progress is being made to engineer de novo metalloproteins capable of performing functions not in the repertoire of biology. Copyright © 2013 Elsevier Ltd. All rights reserved.

Metal Transport across Biomembranes: Emerging Models for a Distinct Chemistry*

PubMed Central

Argüello, José M.; Raimunda, Daniel; González-Guerrero, Manuel

2012-01-01

Transition metals are essential components of important biomolecules, and their homeostasis is central to many life processes. Transmembrane transporters are key elements controlling the distribution of metals in various compartments. However, due to their chemical properties, transition elements require transporters with different structural-functional characteristics from those of alkali and alkali earth ions. Emerging structural information and functional studies have revealed distinctive features of metal transport. Among these are the relevance of multifaceted events involving metal transfer among participating proteins, the importance of coordination geometry at transmembrane transport sites, and the presence of the largely irreversible steps associated with vectorial transport. Here, we discuss how these characteristics shape novel transition metal ion transport models. PMID:22389499

Metal transport across biomembranes: emerging models for a distinct chemistry.

PubMed

Argüello, José M; Raimunda, Daniel; González-Guerrero, Manuel

2012-04-20

Transition metals are essential components of important biomolecules, and their homeostasis is central to many life processes. Transmembrane transporters are key elements controlling the distribution of metals in various compartments. However, due to their chemical properties, transition elements require transporters with different structural-functional characteristics from those of alkali and alkali earth ions. Emerging structural information and functional studies have revealed distinctive features of metal transport. Among these are the relevance of multifaceted events involving metal transfer among participating proteins, the importance of coordination geometry at transmembrane transport sites, and the presence of the largely irreversible steps associated with vectorial transport. Here, we discuss how these characteristics shape novel transition metal ion transport models.

Assessment of chronic post-surgical pain after knee replacement: development of a core outcome set.

PubMed

Wylde, V; MacKichan, F; Bruce, J; Gooberman-Hill, R

2015-05-01

Approximately 20% of patients experience chronic post-surgical pain (CPSP) after total knee replacement (TKR). There is scope to improve assessment of CPSP after TKR, and this study aimed to develop a core outcome set. Eighty patients and 43 clinicians were recruited into a three-round modified Delphi study. In Round 1, participants were presented with 56 pain features identified from a systematic review, structured interviews with patients and focus groups with clinicians. Participants assigned importance ratings, using a 1-9 scale, to individual pain features; those features rated as most important were retained in subsequent rounds. Consensus that a pain feature should be included in the core outcome set was defined as the feature having a rating of 7-9 by ≥70% of both panels (patients and clinicians) and 1-3 by ≤15% of both panels or rated as 7-9 by ≥90% of one panel. Round 1 was completed by 71 patients and 39 clinicians, and Round 3 by 62 patients and 33 clinicians. The final consensus was that 33 pain features were important. These were grouped into an 8-item core outcome set comprising: pain intensity, pain interference with daily living, pain and physical functioning, temporal aspects of pain, pain description, emotional aspects of pain, use of pain medication, and improvement and satisfaction with pain relief. This core outcome set serves to guide assessment of CPSP after TKR. Consistency in assessment can promote standardized reporting and facilitate comparability between studies that address a common but understudied type of CPSP. © 2014 The Authors. European Journal of Pain published by John Wiley & Sons Ltd on behalf of European Pain Federation - EFIC®.

"Anti-Michael addition" of Grignard reagents to sulfonylacetylenes: synthesis of alkynes.

PubMed

Esteban, Francisco; Boughani, Lazhar; García Ruano, José L; Fraile, Alberto; Alemán, José

2017-05-10

In this work, the addition of Grignard reagents to arylsulfonylacetylenes, which undergoes an "anti-Michael addition", resulting in their alkynylation under very mild conditions is described. The simplicity of the experimental procedure and the functional group tolerance are the main features of this methodology. This is an important advantage over the use of organolithium at -78 °C that we previously reported. Moreover, the synthesis of diynes and other examples showing functional group tolerance in this anti-Michael reaction is also presented.

Assessing efficiency of spatial sampling using combined coverage analysis in geographical and feature spaces

NASA Astrophysics Data System (ADS)

Hengl, Tomislav

2015-04-01

Efficiency of spatial sampling largely determines success of model building. This is especially important for geostatistical mapping where an initial sampling plan should provide a good representation or coverage of both geographical (defined by the study area mask map) and feature space (defined by the multi-dimensional covariates). Otherwise the model will need to extrapolate and, hence, the overall uncertainty of the predictions will be high. In many cases, geostatisticians use point data sets which are produced using unknown or inconsistent sampling algorithms. Many point data sets in environmental sciences suffer from spatial clustering and systematic omission of feature space. But how to quantify these 'representation' problems and how to incorporate this knowledge into model building? The author has developed a generic function called 'spsample.prob' (Global Soil Information Facilities package for R) and which simultaneously determines (effective) inclusion probabilities as an average between the kernel density estimation (geographical spreading of points; analysed using the spatstat package in R) and MaxEnt analysis (feature space spreading of points; analysed using the MaxEnt software used primarily for species distribution modelling). The output 'iprob' map indicates whether the sampling plan has systematically missed some important locations and/or features, and can also be used as an input for geostatistical modelling e.g. as a weight map for geostatistical model fitting. The spsample.prob function can also be used in combination with the accessibility analysis (cost of field survey are usually function of distance from the road network, slope and land cover) to allow for simultaneous maximization of average inclusion probabilities and minimization of total survey costs. The author postulates that, by estimating effective inclusion probabilities using combined geographical and feature space analysis, and by comparing survey costs to representation efficiency, an optimal initial sampling plan can be produced which satisfies both criteria: (a) good representation (i.e. within a tolerance threshold), and (b) minimized survey costs. This sampling analysis framework could become especially interesting for generating sampling plans in new areas e.g. for which no previous spatial prediction model exists. The presentation includes data processing demos with standard soil sampling data sets Ebergotzen (Germany) and Edgeroi (Australia), also available via the GSIF package.

Use of and Beliefs About Mobile Phone Apps for Diabetes Self-Management: Surveys of People in a Hospital Diabetes Clinic and Diabetes Health Professionals in New Zealand.

PubMed

Boyle, Leah; Grainger, Rebecca; Hall, Rosemary M; Krebs, Jeremy D

2017-06-30

People with diabetes mellitus (DM) are using mobile phone apps to support self-management. The numerous apps available to assist with diabetes management have a variety of functions. Some functions, like insulin dose calculators, have significant potential for harm. The study aimed to establish (1) whether people with DM in Wellington, New Zealand, use apps for DM self-management and evaluate desirable features of apps and (2) whether health professionals (HPs) in New Zealand treating people with DM recommend apps to patients, the features HPs regard as important, and their confidence with recommending apps. A survey of patients seen at a hospital diabetes clinic over 12 months (N=539) assessed current app use and desirable features. A second survey of HPs attending a diabetes conference (n=286) assessed their confidence with app recommendations and perceived usefulness. Of the 189 responders (35.0% response rate) to the patient survey, 19.6% (37/189) had used a diabetes app. App users were younger and in comparison to other forms of diabetes mellitus, users prominently had type 1 DM. The most favored feature of the app users was a glucose diary (87%, 32/37), and an insulin calculator was the most desirable function for a future app (46%, 17/37). In non-app users, the most desirable feature for a future app was a glucose diary (64.4%, 98/152). Of the 115 responders (40.2% response rate) to the HPs survey, 60.1% (68/113) had recommended a diabetes app. Diaries for blood glucose levels and carbohydrate counting were considered the most useful app features and the features HPs felt most confident to recommend. HPs were least confident in recommending insulin calculation apps. The use of apps to record blood glucose was the most favored function in apps used by people with diabetes, with interest in insulin dose calculating function. HPs do not feel confident in recommending insulin dose calculators. There is an urgent need for an app assessment process to give confidence in the quality and safety of diabetes management apps to people with diabetes (potential app users) and HPs (potential app prescribers). ©Leah Boyle, Rebecca Grainger, Rosemary M Hall, Jeremy D Krebs. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 30.06.2017.

Rhenium-phthalocyanine molecular nanojunction with high magnetic anisotropy and high spin filtering efficiency

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

Li, J.; Institute of Nanomaterial and Nanostructure, Changsha University of Science and Technology, Changsha 410114; Hu, J.

2015-07-20

Using the density functional and non-equilibrium Green's function approaches, we studied the magnetic anisotropy and spin-filtering properties of various transition metal-Phthalocyanine molecular junctions across two Au electrodes. Our important finding is that the Au-RePc-Au junction has both large spin filtering efficiency (>80%) and large magnetic anisotropy energy, which makes it suitable for device applications. To provide insights for the further experimental work, we discussed the correlation between the transport property, magnetic anisotropy, and wave function features of the RePc molecule, and we also illustrated the possibility of controlling its magnetic state.

Serenity: A subsystem quantum chemistry program.

PubMed

Unsleber, Jan P; Dresselhaus, Thomas; Klahr, Kevin; Schnieders, David; Böckers, Michael; Barton, Dennis; Neugebauer, Johannes

2018-05-15

We present the new quantum chemistry program Serenity. It implements a wide variety of functionalities with a focus on subsystem methodology. The modular code structure in combination with publicly available external tools and particular design concepts ensures extensibility and robustness with a focus on the needs of a subsystem program. Several important features of the program are exemplified with sample calculations with subsystem density-functional theory, potential reconstruction techniques, a projection-based embedding approach and combinations thereof with geometry optimization, semi-numerical frequency calculations and linear-response time-dependent density-functional theory. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Functional constraints on tooth morphology in carnivorous mammals

PubMed Central

2012-01-01

Background The range of potential morphologies resulting from evolution is limited by complex interacting processes, ranging from development to function. Quantifying these interactions is important for understanding adaptation and convergent evolution. Using three-dimensional reconstructions of carnivoran and dasyuromorph tooth rows, we compared statistical models of the relationship between tooth row shape and the opposing tooth row, a static feature, as well as measures of mandibular motion during chewing (occlusion), which are kinetic features. This is a new approach to quantifying functional integration because we use measures of movement and displacement, such as the amount the mandible translates laterally during occlusion, as opposed to conventional morphological measures, such as mandible length and geometric landmarks. By sampling two distantly related groups of ecologically similar mammals, we study carnivorous mammals in general rather than a specific group of mammals. Results Statistical model comparisons demonstrate that the best performing models always include some measure of mandibular motion, indicating that functional and statistical models of tooth shape as purely a function of the opposing tooth row are too simple and that increased model complexity provides a better understanding of tooth form. The predictors of the best performing models always included the opposing tooth row shape and a relative linear measure of mandibular motion. Conclusions Our results provide quantitative support of long-standing hypotheses of tooth row shape as being influenced by mandibular motion in addition to the opposing tooth row. Additionally, this study illustrates the utility and necessity of including kinetic features in analyses of morphological integration. PMID:22899809

Protons, osmolytes, and fitness of internal milieu for protein function.

PubMed

Somero, G N

1986-08-01

The composition of the intracellular milieu shows striking similarities among widely different species. Only certain values of intracellular pH, values that generally reflect alphastat regulation, and only narrow ranges of inorganic ion concentrations are found in the cytoplasm of the cells of most animals, plants, and microorganisms. In water-stressed organisms only a few types of low-molecular-weight organic molecules (osmolytes) are accumulated. These highly conserved characteristics of the intracellular fluids reflect the need to maintain critical features of macromolecules within narrow ranges optimal for life. For proteins these features include maintaining adequate rates of catalysis, a high level of regulatory responsiveness, and a precise balance between stability and lability of structure (tertiary conformation, subunit assembly, and multiprotein complexes). The optimal values for these functional and structural features of proteins often lie near the midrange of possible values for these properties, and only under specific conditions of intracellular pH, ionic strength, and osmolyte composition are these optimal midrange values conserved. In dormant cells the departure of solution conditions from values that are optimal for protein function and structure may be instrumental in reducing or shutting down metabolic functions. Seen from a broad evolutionary perspective, the evolution of the intracellular milieu is an important complement to macromolecular evolution. In certain instances appropriate modifications of the internal milieu may reduce the need for adaptive amino acid replacements in proteins.

The flagellum of Trypanosoma brucei: new tricks from an old dog

PubMed Central

Ralston, Katherine S.; Hill, Kent L.

2010-01-01

African trypanosomes, i.e. Trypanosoma brucei and related sub-species, are devastating human and animal pathogens that cause significant human mortality and limit sustained economic development in sub-Saharan Africa. Trypanosoma brucei is a highly motile protozoan parasite and coordinated motility is central to both disease pathogenesis in the mammalian host and parasite development in the tsetse fly vector. Since motility is critical for parasite development and pathogenesis, understanding unique aspects of the T. brucei flagellum may uncover novel targets for therapeutic intervention in African sleeping sickness. Moreover, studies of conserved features of the T. brucei flagellum are directly relevant to understanding fundamental aspects of flagellum and cilium function in other eukaryotes, making T. brucei an important model system. The T. brucei flagellum contains a canonical 9 + 2 axoneme, together with additional features that are unique to kinetoplastids and a few closely-related organisms. Until recently, much of our knowledge of the structure and function of the trypanosome flagellum was based on analogy and inference from other organisms. There has been an explosion in functional studies in T. brucei in recent years, revealing conserved as well as novel and unexpected structural and functional features of the flagellum. Most notably, the flagellum has been found to be an essential organelle, with critical roles in parasite motility, morphogenesis, cell division and immune evasion. This review highlights recent discoveries on the T. brucei flagellum. PMID:18472102

Are non-muscle actin isoforms functionally equivalent?

PubMed

Simiczyjew, Aleksandra; Pietraszek-Gremplewicz, Katarzyna; Mazur, Antonina Joanna; Nowak, Dorota

2017-11-01

Actin is highly conserved and it is the most widespread protein in eukaryotic cells. One of the most important features of actin, which allows it to have many different functions, is its ability to polymerize and interact with many other proteins. Actins are the major constituent of the actin cytoskeleton, which is an important system that is involved in various aspects of cell function, including cell motility, structure, integrity, regulation of signal transduction and transcription. Six mammal actin isoforms are highly conserved and share common functions. Two of them, β and γ non-muscle actin isoforms, which differ only by four amino acids located at the N-terminus of the polypeptide chain, are required for survival and proper cell functioning. We also summarized data about actbl2, which is suggested to be a newly discovered isoactin. Here, we review the current knowledge about tissue-specific expression of the non-muscle actin isoforms and possible functional differences between them. We also discuss molecular tools, which in recent years have allowed for a better understanding of the role of these proteins in cell functioning.

Vibrations of bioionic liquids by ab initio molecular dynamics and vibrational spectroscopy.

PubMed

Tanzi, Luana; Benassi, Paola; Nardone, Michele; Ramondo, Fabio

2014-12-26

Density functional theory and vibrational spectroscopy are used to investigate a class of bioionic liquids consisting of a choline cation and carboxylate anions. Through quantum mechanical studies of motionless ion pairs and molecular dynamics of small portions of the liquid, we have characterized important structural features of the ionic liquid. Hydrogen bonding produces stable ion pairs in the liquid and induces vibrational features of the carboxylate groups comparable with experimental results. Infrared and Raman spectra of liquids have been measured, and main bands have been assigned on the basis of theoretical spectra.

Age-related functional brain changes in young children.

PubMed

Long, Xiangyu; Benischek, Alina; Dewey, Deborah; Lebel, Catherine

2017-07-15

Brain function and structure change significantly during the toddler and preschool years. However, most studies focus on older or younger children, so the specific nature of these changes is unclear. In the present study, we analyzed 77 functional magnetic resonance imaging datasets from 44 children aged 2-6 years. We extracted measures of both local (amplitude of low frequency fluctuation and regional homogeneity) and global (eigenvector centrality mapping) activity and connectivity, and examined their relationships with age using robust linear correlation analysis and strict control for head motion. Brain areas within the default mode network and the frontoparietal network, such as the middle frontal gyrus, the inferior parietal lobule and the posterior cingulate cortex, showed increases in local and global functional features with age. Several brain areas such as the superior parietal lobule and superior temporal gyrus presented opposite development trajectories of local and global functional features, suggesting a shifting connectivity framework in early childhood. This development of functional connectivity in early childhood likely underlies major advances in cognitive abilities, including language and development of theory of mind. These findings provide important insight into the development patterns of brain function during the preschool years, and lay the foundation for future studies of altered brain development in young children with brain disorders or injury. Copyright © 2017 Elsevier Inc. All rights reserved.

Sex-Specific Patterns of Aberrant Brain Function in First-Episode Treatment-Naive Patients with Schizophrenia.

PubMed

Lei, Wei; Li, Mingli; Deng, Wei; Zhou, Yi; Ma, Xiaohong; Wang, Qiang; Guo, Wanjun; Li, Yinfei; Jiang, Lijun; Han, Yuanyuan; Huang, Chaohua; Hu, Xun; Li, Tao

2015-07-16

Male and female patients with schizophrenia show significant differences in a number of important clinical features, yet the neural substrates of these differences are still poorly understood. Here we explored the sex differences in the brain functional aberrations in 124 treatment-naïve patients with first-episode schizophrenia (61 males), compared with 102 age-matched healthy controls (50 males). Maps of degree centrality (DC) and amplitude of low-frequency fluctuations (ALFF) were constructed using resting-state functional magnetic resonance imaging data and compared between groups. We found that: (1) Selective DC reduction was observed in the right putamen (Put_R) in male patients and the left middle frontal gyrus (MFG) in female patients; (2) Functional connectivity analysis (using Put_R and MFG as seeds) found that male and female patients have disturbed functional integration in two separate networks, i.e., the sensorimotor network and the default mode network; (3) Significant ALFF alterations were also observed in these two networks in both genders; (4) Sex specific brain functional alterations were associated with various symptoms in patients. These results suggested that sex-specific patterns of functional aberration existed in schizophrenia, and these patterns were associated with the clinical features both in male and female patients.

Quality of life assessment software for computer-inexperienced older adults: multimedia utility elicitation for activities of daily living.

PubMed Central

Goldstein, M. K.; Miller, D. E.; Davies, S.; Garber, A. M.

2002-01-01

Functional status as measured by dependencies in the Activities of Daily Living (ADLs) is an important indicator of overall health for older adults. Methodologies for outcomes-based medical-decision-making for public policy, such as decision modeling and cost-effectiveness analysis, require utilities for outcome health states. Utilities have been reported for many disease states, but have not been indexed by functional status, which is a strong predictor of outcome in geriatrics. We describe here a utility elicitation program developed specifically for use with computer-inexperienced older adults: Functional Limitation And Independence Rating (FLAIR1). FLAIR1 design features address common physical problems of the aged and computer attitudes of inexperienced users that could impede computer acceptance. We interviewed 400 adults ages 65 years and older with FLAIR1. In exit interviews with 154 respondents, 118 (76%) found FLAIR1 easy to use. Design features in FLAIR1 can be applied to other software for older adults PMID:12463834

Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

[Analysis of Conformational Features of Watson-Crick Duplex Fragments by Molecular Mechanics and Quantum Mechanics Methods].

PubMed

Poltev, V I; Anisimov, V M; Sanchez, C; Deriabina, A; Gonzalez, E; Garcia, D; Rivas, F; Polteva, N A

2016-01-01

It is generally accepted that the important characteristic features of the Watson-Crick duplex originate from the molecular structure of its subunits. However, it still remains to elucidate what properties of each subunit are responsible for the significant characteristic features of the DNA structure. The computations of desoxydinucleoside monophosphates complexes with Na-ions using density functional theory revealed a pivotal role of DNA conformational properties of single-chain minimal fragments in the development of unique features of the Watson-Crick duplex. We found that directionality of the sugar-phosphate backbone and the preferable ranges of its torsion angles, combined with the difference between purines and pyrimidines. in ring bases, define the dependence of three-dimensional structure of the Watson-Crick duplex on nucleotide base sequence. In this work, we extended these density functional theory computations to the minimal' fragments of DNA duplex, complementary desoxydinucleoside monophosphates complexes with Na-ions. Using several computational methods and various functionals, we performed a search for energy minima of BI-conformation for complementary desoxydinucleoside monophosphates complexes with different nucleoside sequences. Two sequences are optimized using ab initio method at the MP2/6-31++G** level of theory. The analysis of torsion angles, sugar ring puckering and mutual base positions of optimized structures demonstrates that the conformational characteristic features of complementary desoxydinucleoside monophosphates complexes with Na-ions remain within BI ranges and become closer to the corresponding characteristic features of the Watson-Crick duplex crystals. Qualitatively, the main characteristic features of each studied complementary desoxydinucleoside monophosphates complex remain invariant when different computational methods are used, although the quantitative values of some conformational parameters could vary lying within the limits typical for the corresponding family. We observe that popular functionals in density functional theory calculations lead to the overestimated distances between base pairs, while MP2 computations and the newer complex functionals produce the structures that have too close atom-atom contacts. A detailed study of some complementary desoxydinucleoside monophosphate complexes with Na-ions highlights the existence of several energy minima corresponding to BI-conformations, in other words, the complexity of the relief pattern of the potential energy surface of complementary desoxydinucleoside monophosphate complexes. This accounts for variability of conformational parameters of duplex fragments with the same base sequence. Popular molecular mechanics force fields AMBER and CHARMM reproduce most of the conformational characteristics of desoxydinucleoside monophosphates and their complementary complexes with Na-ions but fail to reproduce some details of the dependence of the Watson-Crick duplex conformation on the nucleotide sequence.

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

PubMed Central

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

2018-01-01

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

Developmental Changes in Information Central to Artifact Representation: Evidence from "Functional Fluency" Tasks

ERIC Educational Resources Information Center

Defeyter, Margaret Anne; Avons, S. E.; German, Tamsin C.

2007-01-01

Research suggests that while information about design is a central feature of older children's artifact representations it may be less important in the artifact representations of younger children. Three experiments explore the pattern of responses that 5- and 7-year-old children generate when asked to produce multiple uses for familiar…

Intact Visual Discrimination of Complex and Feature-Ambiguous Stimuli in the Absence of Perirhinal Cortex

ERIC Educational Resources Information Center

Squire, Larry R.; Levy, Daniel A.; Shrager, Yael

2005-01-01

The perirhinal cortex is known to be important for memory, but there has recently been interest in the possibility that it might also be involved in visual perceptual functions. In four experiments, we assessed visual discrimination ability and visual discrimination learning in severely amnesic patients with large medial temporal lobe lesions that…

Wetland features and landscape context predict the risk of wetland habitat loss

Treesearch

Kevin J. Gutzwiller; Curtis H. Flather

2011-01-01

Wetlands generally provide significant ecosystem services and function as important harbors of biodiversity. To ensure that these habitats are conserved, an efficient means of identifying wetlands at risk of conversion is needed, especially in the southern United States where the rate of wetland loss has been highest in recent decades. We used multivariate adaptive...

The Potential da Vinci in All of Us

ERIC Educational Resources Information Center

Petto, Sarah; Petto, Andrew

2009-01-01

The study of the human form is fundamental to both science and art curricula. For vertebrates, perhaps no feature is more important than the skeleton to determine observable form and function. As Leonard da Vinci's famous Proportions of the Human Figure (Virtruvian Man) illustrates, the size, shape, and proportions of the human body are defined by…

Hydrologic connectivity between geographically isolated wetlands and surface water systems: A review of select modeling methods

Treesearch

Heather E. Golden; Charles R. Lane; Devendra M. Amatya; Karl W. Bandilla; Hadas Raanan Kiperwas Kiperwas; Christopher D. Knightes; Herbert Ssegane

2014-01-01

Geographically isolated wetlands (GIW), depressional landscape features entirely surrounded by upland areas, provide a wide range of ecological functions and ecosystem services for human well-being. Current and future ecosystem management and decision-making rely on a solid scientific understanding of how hydrologic processes affect these important GIW services and...

An exploration of subgroups of mild cognitive impairment based on cognitive, neuropsychiatric and functional features: analysis of data from the National Alzheimer's Coordinating Center.

PubMed

Hanfelt, John J; Wuu, Joanne; Sollinger, Ann B; Greenaway, Melanie C; Lah, James J; Levey, Allan I; Goldstein, Felicia C

2011-11-01

To empirically expand the existing subtypes of mild cognitive impairment (MCI) by incorporating information on neuropsychiatric and functional features, and to assess whether cerebrovascular disease (CVD) risk factors are associated with any of these subgroups. Latent class analysis using 1,655 patients with MCI. Participants in the Uniform Data Set (UDS) from 29 National Institutes of Health-supported Alzheimer's Disease Centers. Patients with a consensus diagnosis of MCI from each center and with a Mini-Mental State Examination score of 22 or greater. UDS cognitive battery, Neuropsychiatric Inventory Questionnaire, and Functional Assessment Questionnaire administered at initial visit. Seven empirically based subgroups of MCI were identified: 1) minimally impaired (relative frequency, 12%); 2) amnestic only (16%); 3) amnestic with functional and neuropsychiatric features (16%); 4) amnestic multidomain (12%); 5) amnestic multidomain with functional and neuropsychiatric features (12%); 6) functional and neuropsychiatric features (15%); and 7) executive function and language impairments (18%). Two of these subgroups with functional and neuropsychiatric features were at least 3.8 times more likely than the minimally impaired subgroup to have a Rosen-Hachinski score of 4 or greater, an indicator of probable CVD. Findings suggest that there are several distinct phenotypes of MCI characterized by prominent cognitive features, prominent functional features, and neuropsychiatric features or a combination of all three. Subgroups with functional and neuropsychiatric features are significantly more likely to have CVD, which suggests that there may be distinct differences in disease etiology from the other phenotypes.

Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

NASA Astrophysics Data System (ADS)

Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

2018-02-01

This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

Deep learning of support vector machines with class probability output networks.

PubMed

Kim, Sangwook; Yu, Zhibin; Kil, Rhee Man; Lee, Minho

2015-04-01

Deep learning methods endeavor to learn features automatically at multiple levels and allow systems to learn complex functions mapping from the input space to the output space for the given data. The ability to learn powerful features automatically is increasingly important as the volume of data and range of applications of machine learning methods continues to grow. This paper proposes a new deep architecture that uses support vector machines (SVMs) with class probability output networks (CPONs) to provide better generalization power for pattern classification problems. As a result, deep features are extracted without additional feature engineering steps, using multiple layers of the SVM classifiers with CPONs. The proposed structure closely approaches the ideal Bayes classifier as the number of layers increases. Using a simulation of classification problems, the effectiveness of the proposed method is demonstrated. Copyright © 2014 Elsevier Ltd. All rights reserved.

An information measure for class discrimination. [in remote sensing of crop observation

NASA Technical Reports Server (NTRS)

Shen, S. S.; Badhwar, G. D.

1986-01-01

This article describes a separability measure for class discrimination. This measure is based on the Fisher information measure for estimating the mixing proportion of two classes. The Fisher information measure not only provides a means to assess quantitatively the information content in the features for separating classes, but also gives the lower bound for the variance of any unbiased estimate of the mixing proportion based on observations of the features. Unlike most commonly used separability measures, this measure is not dependent on the form of the probability distribution of the features and does not imply a specific estimation procedure. This is important because the probability distribution function that describes the data for a given class does not have simple analytic forms, such as a Gaussian. Results of applying this measure to compare the information content provided by three Landsat-derived feature vectors for the purpose of separating small grains from other crops are presented.

Decoding memory features from hippocampal spiking activities using sparse classification models.

PubMed

Dong Song; Hampson, Robert E; Robinson, Brian S; Marmarelis, Vasilis Z; Deadwyler, Sam A; Berger, Theodore W

2016-08-01

To understand how memory information is encoded in the hippocampus, we build classification models to decode memory features from hippocampal CA3 and CA1 spatio-temporal patterns of spikes recorded from epilepsy patients performing a memory-dependent delayed match-to-sample task. The classification model consists of a set of B-spline basis functions for extracting memory features from the spike patterns, and a sparse logistic regression classifier for generating binary categorical output of memory features. Results show that classification models can extract significant amount of memory information with respects to types of memory tasks and categories of sample images used in the task, despite the high level of variability in prediction accuracy due to the small sample size. These results support the hypothesis that memories are encoded in the hippocampal activities and have important implication to the development of hippocampal memory prostheses.

Characterizing populations and searching for diagnostics via elastic registration of MRI images

NASA Astrophysics Data System (ADS)

Pettey, David; Gee, James C.

2001-07-01

Given image data from two distinct populations and a family of functions, we find the scalar discriminant function which best discriminates between the populations. The goals are two-fold: first, to construct a discriminant function which can accurately and reliably classify subjects via the image data. Second, the best discriminant allows us to see which features in the images distinguish between the populations; these features can guide us to finding characteristic differences between the two groups even if these differences are not sufficient to perform classification. We apply our method to mid-sagittal MRI sections of the corpus callosum from 34 males and 52 females. While we are not certain of the ability of the derived discriminant function to perform sex classification, we find that regions in the anterior of the corpus callosum do appear to be more important for the discriminant function than other regions. This indicates there may be significant differences in the relative size of the splenium in males and females, as has been reported elsewhere. More notably, we applied previous methods which support this view on our larger data set, but found that these methods no longer show statistically significant differences between the male and female splenium.

Improved sparse decomposition based on a smoothed L0 norm using a Laplacian kernel to select features from fMRI data.

PubMed

Zhang, Chuncheng; Song, Sutao; Wen, Xiaotong; Yao, Li; Long, Zhiying

2015-04-30

Feature selection plays an important role in improving the classification accuracy of multivariate classification techniques in the context of fMRI-based decoding due to the "few samples and large features" nature of functional magnetic resonance imaging (fMRI) data. Recently, several sparse representation methods have been applied to the voxel selection of fMRI data. Despite the low computational efficiency of the sparse representation methods, they still displayed promise for applications that select features from fMRI data. In this study, we proposed the Laplacian smoothed L0 norm (LSL0) approach for feature selection of fMRI data. Based on the fast sparse decomposition using smoothed L0 norm (SL0) (Mohimani, 2007), the LSL0 method used the Laplacian function to approximate the L0 norm of sources. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of LSL0 for the sparse source estimation and feature selection. Simulated results indicated that LSL0 produced more accurate source estimation than SL0 at high noise levels. The classification accuracy using voxels that were selected by LSL0 was higher than that by SL0 in both simulated and real fMRI experiment. Moreover, both LSL0 and SL0 showed higher classification accuracy and required less time than ICA and t-test for the fMRI decoding. LSL0 outperformed SL0 in sparse source estimation at high noise level and in feature selection. Moreover, LSL0 and SL0 showed better performance than ICA and t-test for feature selection. Copyright © 2015 Elsevier B.V. All rights reserved.

The relative importance of aerosol scattering and absorption in remote sensing

NASA Technical Reports Server (NTRS)

Fraser, R. S.; Kaufman, Y. J.

1985-01-01

Previous attempts to explain the effect of aerosols on satellite measurements of surface properties for the visible and near-infrared spectrum have emphasized the amount of aerosols without consideration of their absorption properties. In order to estimate the importance of absorption, the radiances of the sunlight scattered from models of the earth-atmosphere system are computed as functions of the aerosol optical thickness and absorption. The absorption effect is small where the surface reflectance is weak, but is important for strong reflectance. These effects on classification of surface features, measuring vegetation index, and measuring surface reflectance are presented.

Learning Time-Varying Coverage Functions

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

Learning Time-Varying Coverage Functions.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-12-08

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data.

Emergence of Rich-Club Topology and Coordinated Dynamics in Development of Hippocampal Functional Networks In Vitro

PubMed Central

Charlesworth, Paul; Kitzbichler, Manfred G.; Paulsen, Ole

2015-01-01

Recent studies demonstrated that the anatomical network of the human brain shows a “rich-club” organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called “hub neurons”). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a “rich-get-richer” growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. PMID:25855164

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

The hip adductor muscle group in caviomorph rodents: anatomy and homology.

PubMed

García-Esponda, César M; Candela, Adriana M

2015-06-01

Anatomical comparative studies including myological data of caviomorph rodents are relatively scarce, leading to a lack of use of muscular features in cladistic and morphofunctional analyses. In rodents, the hip adductor muscles constitute an important group of the hindlimb musculature, having an important function during the beginning of the stance phase. These muscles are subdivided in several distinct ways in the different clades of rodents, making the identification of their homologies hard to establish. In this contribution we provide a detailed description of the anatomical variation of the hip adductor muscle group of different genera of caviomorph rodents and identify the homologies of these muscles in the context of Rodentia. On this basis, we identify the characteristic pattern of the hip adductor muscles in Caviomorpha. Our results indicate that caviomorphs present a singular pattern of the hip adductor musculature that distinguishes them from other groups of rodents. They are characterized by having a single m. adductor brevis that includes solely its genicular part. This muscle, together with the m. gracilis, composes a muscular sheet that is medial to all other muscles of the hip adductor group. Both muscles probably have a synergistic action during locomotion, where the m. adductor brevis reinforces the multiple functions of the m. gracilis in caviomorphs. Mapping of analyzed myological characters in the context of Rodentia indicates that several features are recovered as potential synapomorphies of caviomorphs. Thus, analysis of the myological data described here adds to the current knowledge of caviomorph rodents from anatomical and functional points of view, indicating that this group has features that clearly differentiate them from other rodents. Copyright © 2015 Elsevier GmbH. All rights reserved.

Alcohol and Drug Use and the Developing Brain

PubMed Central

Gray, Kevin M.

2016-01-01

Adolescence is an important neurodevelopmental period marked by rapidly escalating rates of alcohol and drug use. Over the past decade, research has attempted to disentangle pre- and post-substance use effects on brain development by using sophisticated longitudinal designs. This review focuses on recent, prospective studies and addresses the following important questions: (1) what neuropsychological and neural features predate adolescent substance use, making youth more vulnerable to engage in heavy alcohol or drug use, and (2) how does heavy alcohol and drug use affect normal neural development and cognitive functioning? Findings suggest that pre-existing neural features that relate to increased substance use during adolescence include poorer neuropsychological functioning on tests of inhibition and working memory, smaller gray and white matter volume, changes in white matter integrity, and altered brain activation during inhibition, working memory, reward, and resting state. After substance use is initiated, alcohol and marijuana use are associated with poorer cognitive functioning on tests of verbal memory, visuospatial functioning, psychomotor speed, working memory, attention, cognitive control, and overall IQ. Heavy alcohol use during adolescence is related to accelerated decreases in gray matter and attenuated increases in white matter volume, as well as increased brain activation during tasks of inhibition and working memory, relative to controls. Larger longitudinal studies with more diverse samples are needed to better understand the interactive effects of alcohol, marijuana, and other substances, as well as the role of sex, co-occurring psychopathology, genetics, sleep, and age of initiation on substance use. PMID:26984684

Molecular-Scale Features that Govern the Effects of O-Glycosylation on a Carbohydrate-Binding Module

DOE PAGES

Guan, Xiaoyang; Chaffey, Patrick K.; Zeng, Chen; ...

2015-09-21

The protein glycosylation is a ubiquitous post-translational modification in all kingdoms of life. Despite its importance in molecular and cellular biology, the molecular-level ramifications of O-glycosylation on biomolecular structure and function remain elusive. Here, we took a small model glycoprotein and changed the glycan structure and size, amino acid residues near the glycosylation site, and glycosidic linkage while monitoring any corresponding changes to physical stability and cellulose binding affinity. The results of this study reveal the collective importance of all the studied features in controlling the most pronounced effects of O-glycosylation in this system. This study suggests the possibility ofmore » designing proteins with multiple improved properties by simultaneously varying the structures of O-glycans and amino acids local to the glycosylation site.« less

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Effective method for detecting regions of given colors and the features of the region surfaces

NASA Astrophysics Data System (ADS)

Gong, Yihong; Zhang, HongJiang

1994-03-01

Color can be used as a very important cue for image recognition. In industrial and commercial areas, color is widely used as a trademark or identifying feature in objects, such as packaged goods, advertising signs, etc. In image database systems, one may retrieve an image of interest by specifying prominent colors and their locations in the image (image retrieval by contents). These facts enable us to detect or identify a target object using colors. However, this task depends mainly on how effectively we can identify a color and detect regions of the given color under possibly non-uniform illumination conditions such as shade, highlight, and strong contrast. In this paper, we present an effective method to detect regions matching given colors, along with the features of the region surfaces. We adopt the HVC color coordinates in the method because of its ability of completely separating the luminant and chromatic components of colors. Three basis functions functionally serving as the low-pass, high-pass, and band-pass filters, respectively, are introduced.

Visualizing bacterial tRNA identity determinants and antideterminants using function logos and inverse function logos

PubMed Central

Freyhult, Eva; Moulton, Vincent; Ardell, David H.

2006-01-01

Sequence logos are stacked bar graphs that generalize the notion of consensus sequence. They employ entropy statistics very effectively to display variation in a structural alignment of sequences of a common function, while emphasizing its over-represented features. Yet sequence logos cannot display features that distinguish functional subclasses within a structurally related superfamily nor do they display under-represented features. We introduce two extensions to address these needs: function logos and inverse logos. Function logos display subfunctions that are over-represented among sequences carrying a specific feature. Inverse logos generalize both sequence logos and function logos by displaying under-represented, rather than over-represented, features or functions in structural alignments. To make inverse logos, a compositional inverse is applied to the feature or function frequency distributions before logo construction, where a compositional inverse is a mathematical transform that makes common features or functions rare and vice versa. We applied these methods to a database of structurally aligned bacterial tDNAs to create highly condensed, birds-eye views of potentially all so-called identity determinants and antideterminants that confer specific amino acid charging or initiator function on tRNAs in bacteria. We recovered both known and a few potentially novel identity elements. Function logos and inverse logos are useful tools for exploratory bioinformatic analysis of structure–function relationships in sequence families and superfamilies. PMID:16473848

Expression of Epithelial Mesenchymal Transition and Cancer Stem Cell Markers in Circulating Tumor Cells.

PubMed

Werner, Stefan; Stenzl, Arnulf; Pantel, Klaus; Todenhöfer, Tilman

2017-01-01

The characterization of circulating tumor cells (CTC) has the potential not only to provide important insights into molecular alterations of advanced tumor disease but also to facilitate risk prediction. Epithelial mesenchymal transition (EMT) has been discovered as important process for the development of metastases and the dissemination of tumor cells into the blood stream. In different tumor types, CTC with a mesenchymal phenotype have been reported that have presumably underwent EMT. Moreover, CTC with stem-cell like characteristics have been postulated as important drivers of tumor progression. Different platforms have been introduced to allow CTC enrichment independent of expression of epithelial antigens, as these may be downregulated in EMT- or stem-cell-like CTC. Both for CTCs with EMT- or stem-cell features different markers have been proposed. However, there is still a lack of evidence on the association of these markers with functional features and characteristics for stem cells and cells undergoing EMT.

A qualitative study of perceptions of meaningful change in spinal muscular atrophy.

PubMed

McGraw, Sarah; Qian, Ying; Henne, Jeff; Jarecki, Jill; Hobby, Kenneth; Yeh, Wei-Shi

2017-04-04

This qualitative study examined how individuals with Spinal Muscular Atrophy (SMA), their caregivers, and clinicians defined meaningful change, primarily in the Type II and non-ambulant type III patient populations, associated with treatment of this condition. In addition, we explored participants' views about two measures of motor function routinely used in clinical trials for these SMA subtypes, namely the expanded version of the Hammersmith Functional Motor Scale (HFMSE) and the Upper Limb Module (ULM). The 123 participants (21 with SMA, 64 parents, and 11 clinicians), recruited through SMA advocacy organizations, participated in one of 16 focus groups or 37 interviews. The sessions were audio-recorded, and verbatim transcripts were analyzed using a grounded theory approach. For the participants, meaningful change was relative to functional ability, and small changes in motor function could have an important impact on quality of life. Because patients and families feared progressive loss of functional ability, the participants saw maintenance of abilities as a meaningful outcome. They believed that measures of motor function covered important items, but worried that the HFMSE and ULM might not be sensitive enough to capture small changes. In addition, they felt that outcome measures should assess other important features of life with SMA, including the ability to perform daily activities, respiratory function, swallowing, fatigue, and endurance. Given the heterogeneity of SMA, it is important to expand the assessment of treatment effects to a broader range of outcomes using measures sensitive enough to detect small changes.

Recent Achievement in Gene Cloning and Functional Genomics in Soybean

PubMed Central

Zhai, Hong; Lü, Shixiang; Wu, Hongyan; Zhang, Yupeng

2013-01-01

Soybean is a model plant for photoperiodism as well as for symbiotic nitrogen fixation. However, a rather low efficiency in soybean transformation hampers functional analysis of genes isolated from soybean. In comparison, rapid development and progress in flowering time and photoperiodic response have been achieved in Arabidopsis and rice. As the soybean genomic information has been released since 2008, gene cloning and functional genomic studies have been revived as indicated by successfully characterizing genes involved in maturity and nematode resistance. Here, we review some major achievements in the cloning of some important genes and some specific features at genetic or genomic levels revealed by the analysis of functional genomics of soybean. PMID:24311973

The fundamental role of subcellular topography in peripheral nerve repair therapies.

PubMed

Spivey, Eric C; Khaing, Zin Z; Shear, Jason B; Schmidt, Christine E

2012-06-01

Clinical evidence suggests that nano- and microtopography incorporated into scaffolds does not merely improve peripheral nerve regeneration, but is in fact a prerequisite for meaningful restoration of nerve function. Although the biological mechanisms involved are not fully understood, grafts incorporating physical guides that mimic microscopic nerve tissue features (e.g., basal laminae) appear to provide a significant advantage over grafts that rely on purely chemical or macroscopic similarities to nerve tissue. Investigators consistently demonstrate the fundamental importance of nano- and micro-scale physical features for appropriate cell response in a wide range of biological scenarios. Additionally, recent in vivo research demonstrates that nerve regeneration scaffolds with cell-scale physical features are more effective than those that rely only on chemical or macro-scale features. Physical guidance at the cell-scale is especially important for long (>20 mm) nerve defects, for which the only reliable treatment is the autologous nerve graft. The lack of other available options exposes a clear need for the application of nano- and microfabrication techniques that will allow the next generation of engineered nerve guides to more closely mimic native tissue at those scales. This review examines current research to determine what elements of cell-scale topography in experimental scaffolds are most effective at stimulating functional recovery, and then presents an overview of fabrication techniques that could potentially improve future treatment paradigms. Relative advantages and disadvantages of these techniques are discussed, with respect to both clinical adaptation and likely effectiveness. Our intent is to more clearly delineate the remaining obstacles in the development of a next generation nerve guide, particularly for long defects, and offer new perspectives on steering current technologies towards clinically viable solutions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Visual perceptual training reconfigures post-task resting-state functional connectivity with a feature-representation region.

PubMed

Sarabi, Mitra Taghizadeh; Aoki, Ryuta; Tsumura, Kaho; Keerativittayayut, Ruedeerat; Jimura, Koji; Nakahara, Kiyoshi

2018-01-01

The neural mechanisms underlying visual perceptual learning (VPL) have typically been studied by examining changes in task-related brain activation after training. However, the relationship between post-task "offline" processes and VPL remains unclear. The present study examined this question by obtaining resting-state functional magnetic resonance imaging (fMRI) scans of human brains before and after a task-fMRI session involving visual perceptual training. During the task-fMRI session, participants performed a motion coherence discrimination task in which they judged the direction of moving dots with a coherence level that varied between trials (20, 40, and 80%). We found that stimulus-induced activation increased with motion coherence in the middle temporal cortex (MT+), a feature-specific region representing visual motion. On the other hand, stimulus-induced activation decreased with motion coherence in the dorsal anterior cingulate cortex (dACC) and bilateral insula, regions involved in decision making under perceptual ambiguity. Moreover, by comparing pre-task and post-task rest periods, we revealed that resting-state functional connectivity (rs-FC) with the MT+ was significantly increased after training in widespread cortical regions including the bilateral sensorimotor and temporal cortices. In contrast, rs-FC with the MT+ was significantly decreased in subcortical regions including the thalamus and putamen. Importantly, the training-induced change in rs-FC was observed only with the MT+, but not with the dACC or insula. Thus, our findings suggest that perceptual training induces plastic changes in offline functional connectivity specifically in brain regions representing the trained visual feature, emphasising the distinct roles of feature-representation regions and decision-related regions in VPL.

Positional Accuracy in Optical Trap-Assisted Nanolithography

NASA Astrophysics Data System (ADS)

Arnold, Craig B.; McLeod, Euan

2009-03-01

The ability to directly print patterns on size scales below 100 nm is important for many applications where the production or repair of high resolution and density features are important. Laser-based direct-write methods have the benefit of quickly and easily being able to modify and create structures on existing devices, but feature sizes are conventionally limited by diffraction. In this presentation, we show how to overcome this limit with a new method of probe-based near-field nanopatterning in which we employ a CW laser to optically trap and manipulate dispersed microspheres against a substrate using a 2-d Bessel beam optical trap. A secondary, pulsed nanosecond laser at 355 nm is directed through the bead and used to modify the surface below the microsphere, taking advantage of the near-field enhancement in order to produce materials modification with feature sizes under 100 nm. Here, we analyze the 3-d positioning accuracy of the microsphere through analytic modeling as a function of experimental parameters. The model is verified in all directions for our experimental conditions and is used to predict the conditions required for improved positional accuracy.

Correlation of the lung microbiota with metabolic profiles in bronchoalveolar lavage fluid in HIV infection.

PubMed

Cribbs, Sushma K; Uppal, Karan; Li, Shuzhao; Jones, Dean P; Huang, Laurence; Tipton, Laura; Fitch, Adam; Greenblatt, Ruth M; Kingsley, Lawrence; Guidot, David M; Ghedin, Elodie; Morris, Alison

2016-01-20

While 16S ribosomal RNA (rRNA) sequencing has been used to characterize the lung's bacterial microbiota in human immunodeficiency virus (HIV)-infected individuals, taxonomic studies provide limited information on bacterial function and impact on the host. Metabolic profiles can provide functional information on host-microbe interactions in the lungs. We investigated the relationship between the respiratory microbiota and metabolic profiles in the bronchoalveolar lavage fluid of HIV-infected and HIV-uninfected outpatients. Targeted sequencing of the 16S rRNA gene was used to analyze the bacterial community structure and liquid chromatography-high-resolution mass spectrometry was used to detect features in bronchoalveolar lavage fluid. Global integration of all metabolic features with microbial species was done using sparse partial least squares regression. Thirty-nine HIV-infected subjects and 20 HIV-uninfected controls without acute respiratory symptoms were enrolled. Twelve mass-to-charge ratio (m/z) features from C18 analysis were significantly different between HIV-infected individuals and controls (false discovery rate (FDR) = 0.2); another 79 features were identified by network analysis. Further metabolite analysis demonstrated that four features were significantly overrepresented in the bronchoalveolar lavage (BAL) fluid of HIV-infected individuals compared to HIV-uninfected, including cystine, two complex carbohydrates, and 3,5-dibromo-L-tyrosine. There were 231 m/z features significantly associated with peripheral blood CD4 cell counts identified using sparse partial least squares regression (sPLS) at a variable importance on projection (VIP) threshold of 2. Twenty-five percent of these 91 m/z features were associated with various microbial species. Bacteria from families Caulobacteraceae, Staphylococcaceae, Nocardioidaceae, and genus Streptococcus were associated with the greatest number of features. Glycerophospholipid and lineolate pathways correlated with these bacteria. In bronchoalveolar lavage fluid, specific metabolic profiles correlated with bacterial organisms known to play a role in the pathogenesis of pneumonia in HIV-infected individuals. These findings suggest that microbial communities and their interactions with the host may have functional metabolic impact in the lung.

What to Build for Middle-Agers to Come? Attractive and Necessary Functions of Exercise-Promotion Mobile Phone Apps: A Cross-Sectional Study.

PubMed

Liao, Gen-Yih; Chien, Yu-Tai; Chen, Yu-Jen; Hsiung, Hsiao-Fang; Chen, Hsiao-Jung; Hsieh, Meng-Hua; Wu, Wen-Jie

2017-05-25

Physical activity is important for middle-agers to maintain health both in middle age and in old age. Although thousands of exercise-promotion mobile phone apps are available for download, current literature offers little understanding regarding which design features can enhance middle-aged adults' quality perception toward exercise-promotion apps and which factor may influence such perception. The aims of this study were to understand (1) which design features of exercise-promotion apps can enhance quality perception of middle-agers, (2) whether their needs are matched by current functions offered in app stores, and (3) whether physical activity (PA) and mobile phone self-efficacy (MPSE) influence quality perception. A total of 105 middle-agers participated and filled out three scales: the International Physical Activity Questionnaire (IPAQ), the MPSE scale, and the need for design features questionnaire. The design features were developed based on the Coventry, Aberdeen, and London-Refined (CALO-RE) taxonomy. Following the Kano quality model, the need for design features questionnaire asked participants to classify design features into five categories: attractive, one-dimensional, must-be, indifferent, and reverse. The quality categorization was conducted based on a voting approach and the categorization results were compared with the findings of a prevalence study to realize whether needs match current availability. In total, 52 multinomial logistic regression models were analyzed to evaluate the effects of PA level and MPSE on quality perception of design features. The Kano analysis on the total sample revealed that visual demonstration of exercise instructions is the only attractive design feature, whereas the other 51 design features were perceived with indifference. Although examining quality perception by PA level, 21 features are recommended to low level, 6 features to medium level, but none to high-level PA. In contrast, high-level MPSE is recommended with 14 design features, medium level with 6 features, whereas low-level participants are recommended with 1 feature. The analysis suggests that the implementation of demanded features could be low, as the average prevalence of demanded design features is 20% (4.3/21). Surprisingly, social comparison and social support, most implemented features in current apps, were categorized into the indifferent category. The magnitude of effect is larger for MPSE because it effects quality perception of more design features than PA. Delving into the 52 regression models revealed that high MPSE more likely induces attractive or one- dimensional categorization, suggesting the importance of technological self-efficacy on eHealth care promotion. This study is the first to propose middle-agers' needs in relation to mobile phone exercise-promotion. In addition to the tailor-made recommendations, suggestions are offered to app designers to enhance the performance of persuasive features. An interesting finding on change of quality perception attributed to MPSE is proposed as future research. ©Gen-Yih Liao, Yu-Tai Chien, Yu-Jen Chen, Hsiao-Fang Hsiung, Hsiao-Jung Chen, Meng-Hua Hsieh, Wen-Jie Wu. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 25.05.2017.

Spectroscopic Diagnosis of Arsenic Contamination in Agricultural Soils

PubMed Central

Shi, Tiezhu; Liu, Huizeng; Chen, Yiyun; Fei, Teng; Wang, Junjie; Wu, Guofeng

2017-01-01

This study investigated the abilities of pre-processing, feature selection and machine-learning methods for the spectroscopic diagnosis of soil arsenic contamination. The spectral data were pre-processed by using Savitzky-Golay smoothing, first and second derivatives, multiplicative scatter correction, standard normal variate, and mean centering. Principle component analysis (PCA) and the RELIEF algorithm were used to extract spectral features. Machine-learning methods, including random forests (RF), artificial neural network (ANN), radial basis function- and linear function- based support vector machine (RBF- and LF-SVM) were employed for establishing diagnosis models. The model accuracies were evaluated and compared by using overall accuracies (OAs). The statistical significance of the difference between models was evaluated by using McNemar’s test (Z value). The results showed that the OAs varied with the different combinations of pre-processing, feature selection, and classification methods. Feature selection methods could improve the modeling efficiencies and diagnosis accuracies, and RELIEF often outperformed PCA. The optimal models established by RF (OA = 86%), ANN (OA = 89%), RBF- (OA = 89%) and LF-SVM (OA = 87%) had no statistical difference in diagnosis accuracies (Z < 1.96, p < 0.05). These results indicated that it was feasible to diagnose soil arsenic contamination using reflectance spectroscopy. The appropriate combination of multivariate methods was important to improve diagnosis accuracies. PMID:28471412

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.

Statistical analysis of dendritic spine distributions in rat hippocampal cultures

PubMed Central

2013-01-01

Background Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites. Results Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type. Conclusions Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons. PMID:24088199

Effects of facial emotion recognition remediation on visual scanning of novel face stimuli.

PubMed

Marsh, Pamela J; Luckett, Gemma; Russell, Tamara; Coltheart, Max; Green, Melissa J

2012-11-01

Previous research shows that emotion recognition in schizophrenia can be improved with targeted remediation that draws attention to important facial features (eyes, nose, mouth). Moreover, the effects of training have been shown to last for up to one month after training. The aim of this study was to investigate whether improved emotion recognition of novel faces is associated with concomitant changes in visual scanning of these same novel facial expressions. Thirty-nine participants with schizophrenia received emotion recognition training using Ekman's Micro-Expression Training Tool (METT), with emotion recognition and visual scanpath (VSP) recordings to face stimuli collected simultaneously. Baseline ratings of interpersonal and cognitive functioning were also collected from all participants. Post-METT training, participants showed changes in foveal attention to the features of facial expressions of emotion not used in METT training, which were generally consistent with the information about important features from the METT. In particular, there were changes in how participants looked at the features of facial expressions of emotion surprise, disgust, fear, happiness, and neutral, demonstrating that improved emotion recognition is paralleled by changes in the way participants with schizophrenia viewed novel facial expressions of emotion. However, there were overall decreases in foveal attention to sad and neutral faces that indicate more intensive instruction might be needed for these faces during training. Most importantly, the evidence shows that participant gender may affect training outcomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Varied Rates of Implementation of Patient-Centered Medical Home Features and Residents' Perceptions of Their Importance Based on Practice Experience.

PubMed

Eiff, M Patrice; Green, Larry A; Jones, Geoff; Devlaeminck, Alex Verdieck; Waller, Elaine; Dexter, Eve; Marino, Miguel; Carney, Patricia A

2017-03-01

Little is known about how the patient-centered medical home (PCMH) is being implemented in residency practices. We describe both the trends in implementation of PCMH features and the influence that working with PCMH features has on resident attitudes toward their importance in 14 family medicine residencies associated with the P4 Project. We assessed 24 residency continuity clinics annually between 2007-2011 on presence or absence of PCMH features. Annual resident surveys (n=690) assessed perceptions of importance of PCMH features using a 4-point scale (not at all important to very important). We used generalized estimating equations logistic regression to assess trends and ordinal-response proportional odds regression models to determine if resident ratings of importance were associated with working with those features during training. Implementation of electronic health record (EHR) features increased significantly from 2007-2011, such as email communication with patients (33% to 67%), preventive services registries (23% to 64%), chronic disease registries (63% to 82%), and population-based quality assurance (46% to 79%). Team-based care was the only process of care feature to change significantly (54% to 93%). Residents with any exposure to EHR-based features had higher odds of rating the features more important compared to those with no exposure. We observed consistently lower odds of the resident rating process of care features as more important with any exposure compared to no exposure. Residencies engaged in educational transformation were more successful in implementing EHR-based PCMH features, and exposure during training appears to positively influence resident ratings of importance, while exposure to process of care features are slower to implement with less influence on importance ratings.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

NASA Astrophysics Data System (ADS)

Jegadeeshwaran, R.; Sugumaran, V.

2015-02-01

Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.

Animal Toxins Providing Insights into TRPV1 Activation Mechanism

PubMed Central

Geron, Matan; Hazan, Adina

2017-01-01

Beyond providing evolutionary advantages, venoms offer unique research tools, as they were developed to target functionally important proteins and pathways. As a key pain receptor in the nociceptive pathway, transient receptor potential vanilloid 1 (TRPV1) of the TRP superfamily has been shown to be a target for several toxins, as a way of producing pain to deter predators. Importantly, TRPV1 is involved in thermoregulation, inflammation, and acute nociception. As such, toxins provide tools to understand TRPV1 activation and modulation, a critical step in advancing pain research and the development of novel analgesics. Indeed, the phytotoxin capsaicin, which is the spicy chemical in chili peppers, was invaluable in the original cloning and characterization of TRPV1. The unique properties of each subsequently characterized toxin have continued to advance our understanding of functional, structural, and biophysical characteristics of TRPV1. By building on previous reviews, this work aims to provide a comprehensive summary of the advancements made in TRPV1 research in recent years by employing animal toxins, in particular DkTx, RhTx, BmP01, Echis coloratus toxins, APHCs and HCRG21. We examine each toxin’s functional aspects, behavioral effects, and structural features, all of which have contributed to our current knowledge of TRPV1. We additionally discuss the key features of TRPV1’s outer pore domain, which proves to be the target of the currently discussed toxins. PMID:29035314

Ecological forestry in an uneven-aged, late-successional forest: Simulated effects of contrasting treatments on structure and yield

Treesearch

Jacob J. Hanson; Craig G. Lorimer; Corey R. Halpin; Brian J. Palik

2012-01-01

Ecological forestry practices are designed to retain species and structural features important for maintaining ecosystem function but which may be deficient in conventionally managed stands. We used the spatially-explicit, individual tree model CANOPY to assess tradeoffs in enhanced ecological attributes vs. reductions in timber yield for a wide variety of treatments...

A Snapshot of the Role of the Textbook in English Secondary Mathematics Classrooms

ERIC Educational Resources Information Center

O'Keeffe, Lisa; White, Bruce

2017-01-01

The role and function of the mathematics textbook has been widely discussed since its inclusion in the Trends in International Mathematics and Science study (TIMSS) in the late nineties. It is a common feature in many classrooms worldwide and has been identified as an important vehicle for the promotion of curricula. However, there has also been…

Genre Analysis of Personal Statements: Analysis of Moves in Application Essays to Medical and Dental Schools

ERIC Educational Resources Information Center

Ding, Huiling

2007-01-01

Despite the important role the personal statement plays in the graduate school application processes, little research has been done on its functional features and little instruction has been given about it in academic writing courses. The author conducted a multi-level discourse analysis on a corpus of 30 medical/dental school application letters,…

The Food Code in the Yakut Culture: Semantics and Functions

ERIC Educational Resources Information Center

Gabysheva, Luiza Lvovna

2016-01-01

The relevance of researching the issue of a specific cultural meaning for a word in a folklore text is based on its being insufficiently studied and due to the importance for solving the problem of the folklore language semantic features. Yakut nominations for dairy products, which are the key words in the language of the Sakha people's folklore,…

Higher Education Policy: An International Comparative Perspective. Issues in Higher Education Series.

ERIC Educational Resources Information Center

Goedegebuure, Leo, Ed.; And Others

This book is the result of a research project on the most important principles, structural features, and functionalities of higher education policies in 11 developed nations around the world. Reports on each nation, are based in large part on analysis of responses to a common questionnaire by national experts in each nation. An opening chapter,…

A Case Study of the Features of Oral Narratives Produced by a Small Group of Children with Sensory Processing Disorder

ERIC Educational Resources Information Center

Kingston, Helen Chen

2009-01-01

Research indicates that oral narrative is the discourse form that functions as a bridge between conversational oral language and language skills that contribute to the acquisition of literacy in children (Westby, 1991). Learning to tell stories, therefore, is important to children's literacy development. Mastering extended discourse tasks such as…

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations.

PubMed

Deng, Lu; Du, Jincheng

2018-01-14

Borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Q n distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3 B and 4 B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. The results also shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Deng, Lu; Du, Jincheng

2018-01-01

Borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Qn distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3B and 4B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. The results also shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

Identification of DNA-Binding Proteins Using Structural, Electrostatic and Evolutionary Features

PubMed Central

Nimrod, Guy; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2009-01-01

Summary DNA binding proteins (DBPs) often take part in various crucial processes of the cell's life cycle. Therefore, the identification and characterization of these proteins are of great importance. We present here a random forests classifier for identifying DBPs among proteins with known three-dimensional structures. First, clusters of evolutionarily conserved regions (patches) on the protein's surface are detected using the PatchFinder algorithm; previous studies showed that these regions are typically the proteins' functionally important regions. Next, we train a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein including its dipole moment. Using 10-fold cross validation on a dataset of 138 DNA-binding proteins and 110 proteins which do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of previously published methods. Furthermore, when we tested 5 different methods on 11 new DBPs which did not appear in the original dataset, only our method annotated all correctly. The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA. PMID:19233205

Identification of DNA-binding proteins using structural, electrostatic and evolutionary features.

PubMed

Nimrod, Guy; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2009-04-10

DNA-binding proteins (DBPs) participate in various crucial processes in the life-cycle of the cells, and the identification and characterization of these proteins is of great importance. We present here a random forests classifier for identifying DBPs among proteins with known 3D structures. First, clusters of evolutionarily conserved regions (patches) on the surface of proteins were detected using the PatchFinder algorithm; earlier studies showed that these regions are typically the functionally important regions of proteins. Next, we trained a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein, including its dipole moment. Using 10-fold cross-validation on a dataset of 138 DBPs and 110 proteins that do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of published methods. Furthermore, when we tested five different methods on 11 new DBPs that did not appear in the original dataset, only our method annotated all correctly. The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA.

Extracting DNA words based on the sequence features: non-uniform distribution and integrity.

PubMed

Li, Zhi; Cao, Hongyan; Cui, Yuehua; Zhang, Yanbo

2016-01-25

DNA sequence can be viewed as an unknown language with words as its functional units. Given that most sequence alignment algorithms such as the motif discovery algorithms depend on the quality of background information about sequences, it is necessary to develop an ab initio algorithm for extracting the "words" based only on the DNA sequences. We considered that non-uniform distribution and integrity were two important features of a word, based on which we developed an ab initio algorithm to extract "DNA words" that have potential functional meaning. A Kolmogorov-Smirnov test was used for consistency test of uniform distribution of DNA sequences, and the integrity was judged by the sequence and position alignment. Two random base sequences were adopted as negative control, and an English book was used as positive control to verify our algorithm. We applied our algorithm to the genomes of Saccharomyces cerevisiae and 10 strains of Escherichia coli to show the utility of the methods. The results provide strong evidences that the algorithm is a promising tool for ab initio building a DNA dictionary. Our method provides a fast way for large scale screening of important DNA elements and offers potential insights into the understanding of a genome.

A Rare Combination of Functional Disomy Xp, Deletion Xq13.2-q28 Spanning the XIST Gene, and Duplication 3q25.33-q29 in a Female with der(X)t(X;3)(q13.2;q25.33).

PubMed

Peterson, Jess F; Basel, Donald G; Bick, David P; Chirempes, Brett; Lorier, Rachel B; Zemlicka, Nykula; Grignon, John W; Weik, LuAnn; Kappes, Ulrike

2018-03-01

We report a 19-year-old female patient with a history of short stature, primary ovarian insufficiency, sensorineural hearing loss, sacral teratoma, neurogenic bladder, and intellectual disability with underlying mosaicism for der(X)t(X;3)(q13.2;q25.33), a ring X chromosome, and monosomy X. Derivative X chromosomes from unbalanced X-autosomal translocations are preferentially silenced by the XIST gene (Xq13.2) located within the X-inactivation center. The unbalanced X-autosomal translocation in our case resulted in loss of the XIST gene thus precluding the inactivation of the derivative X chromosome. As a result, clinical features of functional disomy Xp, Turner's syndrome, and duplication 3q syndrome were observed. Importantly, indications of the derivative X chromosome were revealed by microarray analysis following an initial diagnosis of Turner's syndrome made by conventional cytogenetic studies approximately 18 months earlier. This case demonstrates the importance of utilizing microarray analysis as a first-line test in patients with clinical features beyond the scope of a well-defined genetic syndrome.

Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia.

PubMed

Zhang, Jianfeng; Huang, Zirui; Chen, Yali; Zhang, Jun; Ghinda, Diana; Nikolova, Yuliya; Wu, Jinsong; Xu, Jianghui; Bai, Wenjie; Mao, Ying; Yang, Zhong; Duncan, Niall; Qin, Pengmin; Wang, Hao; Chen, Bing; Weng, Xuchu; Northoff, Georg

2018-05-01

Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial "decoupling." This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC). © 2018 Wiley Periodicals, Inc.

Network motif frequency vectors reveal evolving metabolic network organisation.

PubMed

Pearcy, Nicole; Crofts, Jonathan J; Chuzhanova, Nadia

2015-01-01

At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this underlying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic networks.

The functional basis of face evaluation

PubMed Central

Oosterhof, Nikolaas N.; Todorov, Alexander

2008-01-01

People automatically evaluate faces on multiple trait dimensions, and these evaluations predict important social outcomes, ranging from electoral success to sentencing decisions. Based on behavioral studies and computer modeling, we develop a 2D model of face evaluation. First, using a principal components analysis of trait judgments of emotionally neutral faces, we identify two orthogonal dimensions, valence and dominance, that are sufficient to describe face evaluation and show that these dimensions can be approximated by judgments of trustworthiness and dominance. Second, using a data-driven statistical model for face representation, we build and validate models for representing face trustworthiness and face dominance. Third, using these models, we show that, whereas valence evaluation is more sensitive to features resembling expressions signaling whether the person should be avoided or approached, dominance evaluation is more sensitive to features signaling physical strength/weakness. Fourth, we show that important social judgments, such as threat, can be reproduced as a function of the two orthogonal dimensions of valence and dominance. The findings suggest that face evaluation involves an overgeneralization of adaptive mechanisms for inferring harmful intentions and the ability to cause harm and can account for rapid, yet not necessarily accurate, judgments from faces. PMID:18685089

Super-enhancers: Asset management in immune cell genomes.

PubMed

Witte, Steven; O'Shea, John J; Vahedi, Golnaz

2015-09-01

Super-enhancers (SEs) are regions of the genome consisting of clusters of regulatory elements bound with very high amounts of transcription factors, and this architecture appears to be the hallmark of genes and noncoding RNAs linked with cell identity. Recent studies have identified SEs in CD4(+) T cells and have further linked these regions to single nucleotide polymorphisms (SNPs) associated with immune-mediated disorders, pointing to an important role for these structures in the T cell differentiation and function. Here we review the features that define SEs, and discuss their function within the broader understanding of the mechanisms that define immune cell identity and function. We propose that SEs present crucial regulatory hubs, coordinating intrinsic and extrinsic differentiation signals, and argue that delineating these regions will provide important insight into the factors and mechanisms that define immune cell identity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Jump phenomena. [large amplitude responses of nonlinear systems

NASA Technical Reports Server (NTRS)

Reiss, E. L.

1980-01-01

The paper considers jump phenomena composed of large amplitude responses of nonlinear systems caused by small amplitude disturbances. Physical problems where large jumps in the solution amplitude are important features of the response are described, including snap buckling of elastic shells, chemical reactions leading to combustion and explosion, and long-term climatic changes of the earth's atmosphere. A new method of rational functions was then developed which consists of representing the solutions of the jump problems as rational functions of the small disturbance parameter; this method can solve jump problems explicitly.

Implementation of logic functions and computations by chemical kinetics

NASA Astrophysics Data System (ADS)

Hjelmfelt, A.; Ross, J.

We review our work on the computational functions of the kinetics of chemical networks. We examine spatially homogeneous networks which are based on prototypical reactions occurring in living cells and show the construction of logic gates and sequential and parallel networks. This work motivates the study of an important biochemical pathway, glycolysis, and we demonstrate that the switch that controls the flux in the direction of glycolysis or gluconeogenesis may be described as a fuzzy AND operator. We also study a spatially inhomogeneous network which shares features of theoretical and biological neural networks.

Desktop Nanofabrication with Massively Multiplexed Beam Pen Lithography

PubMed Central

Liao, Xing; Brown, Keith A.; Schmucker, Abrin L.; Liu, Guoliang; He, Shu; Shim, Wooyoung; Mirkin, Chad A.

2013-01-01

The development of a lithographic method that can rapidly define nanoscale features across centimeter-scale surfaces has been a long standing goal of the nanotechnology community. If such a ‘desktop nanofab’ could be implemented in a low-cost format, it would bring the possibility of point-of-use nanofabrication for rapidly prototyping diverse functional structures. Here we report the development of a new tool that is capable of writing arbitrary patterns composed of diffraction-unlimited features over square centimeter areas that are in registry with existing patterns and nanostructures. Importantly, this instrument is based on components that are inexpensive compared to the combination of state-of-the-art nanofabrication tools that approach its capabilities. This tool can be used to prototype functional electronic devices in a mask-free fashion in addition to providing a unique platform for performing high throughput nano- to macroscale photochemistry with relevance to biology and medicine. PMID:23868336

Hereditary spastic paraplegia.

PubMed

Blackstone, Craig

2018-01-01

The hereditary spastic paraplegias (HSPs) are a heterogeneous group of neurologic disorders with the common feature of prominent lower-extremity spasticity, resulting from a length-dependent axonopathy of corticospinal upper motor neurons. The HSPs exist not only in "pure" forms but also in "complex" forms that are associated with additional neurologic and extraneurologic features. The HSPs are among the most genetically diverse neurologic disorders, with well over 70 distinct genetic loci, for which about 60 mutated genes have already been identified. Numerous studies elucidating the molecular pathogenesis underlying HSPs have highlighted the importance of basic cellular functions - especially membrane trafficking, mitochondrial function, organelle shaping and biogenesis, axon transport, and lipid/cholesterol metabolism - in axon development and maintenance. An encouragingly small number of converging cellular pathogenic themes have been identified for the most common HSPs, and some of these pathways present compelling targets for future therapies. Copyright © 2018 Elsevier B.V. All rights reserved.

Predicted Deepwater Bathymetry from Satellite Altimetry: Non-Fourier Transform Alternatives

NASA Astrophysics Data System (ADS)

Salazar, M.; Elmore, P. A.

2017-12-01

Robert Parker (1972) demonstrated the effectiveness of Fourier Transforms (FT) to compute gravitational potential anomalies caused by uneven, non-uniform layers of material. This important calculation relates the gravitational potential anomaly to sea-floor topography. As outlined by Sandwell and Smith (1997), a six-step procedure, utilizing the FT, then demonstrated how satellite altimetry measurements of marine geoid height are inverted into seafloor topography. However, FTs are not local in space and produce Gibb's phenomenon around discontinuities. Seafloor features exhibit spatial locality and features such as seamounts and ridges often have sharp inclines. Initial tests compared the windowed-FT to wavelets in reconstruction of the step and saw-tooth functions and resulted in lower RMS error with fewer coefficients. This investigation, thus, examined the feasibility of utilizing sparser base functions such as the Mexican Hat Wavelet, which is local in space, to first calculate the gravitational potential, and then relate it to sea-floor topography.

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

PubMed Central

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

PubMed

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

Desktop nanofabrication with massively multiplexed beam pen lithography.

PubMed

Liao, Xing; Brown, Keith A; Schmucker, Abrin L; Liu, Guoliang; He, Shu; Shim, Wooyoung; Mirkin, Chad A

2013-01-01

The development of a lithographic method that can rapidly define nanoscale features across centimetre-scale surfaces has been a long-standing goal for the nanotechnology community. If such a 'desktop nanofab' could be implemented in a low-cost format, it would bring the possibility of point-of-use nanofabrication for rapidly prototyping diverse functional structures. Here we report the development of a new tool that is capable of writing arbitrary patterns composed of diffraction-unlimited features over square centimetre areas that are in registry with existing patterns and nanostructures. Importantly, this instrument is based on components that are inexpensive compared with the combination of state-of-the-art nanofabrication tools that approach its capabilities. This tool can be used to prototype functional electronic devices in a mask-free fashion in addition to providing a unique platform for performing high-throughput nano- to macroscale photochemistry with relevance to biology and medicine.

Dysfunctional tubular endoplasmic reticulum constitutes a pathological feature of Alzheimer's disease.

PubMed

Sharoar, M G; Shi, Q; Ge, Y; He, W; Hu, X; Perry, G; Zhu, X; Yan, R

2016-09-01

Pathological features in Alzheimer's brains include mitochondrial dysfunction and dystrophic neurites (DNs) in areas surrounding amyloid plaques. Using a mouse model that overexpresses reticulon 3 (RTN3) and spontaneously develops age-dependent hippocampal DNs, here we report that DNs contain both RTN3 and REEPs, topologically similar proteins that can shape tubular endoplasmic reticulum (ER). Importantly, ultrastructural examinations of such DNs revealed gradual accumulation of tubular ER in axonal termini, and such abnormal tubular ER inclusion is found in areas surrounding amyloid plaques in biopsy samples from Alzheimer's disease (AD) brains. Functionally, abnormally clustered tubular ER induces enhanced mitochondrial fission in the early stages of DN formation and eventual mitochondrial degeneration at later stages. Furthermore, such DNs are abrogated when RTN3 is ablated in aging and AD mouse models. Hence, abnormally clustered tubular ER can be pathogenic in brain regions: disrupting mitochondrial integrity, inducing DNs formation and impairing cognitive function in AD and aging brains.

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

Chinthavali, Madhu Sudhan; Campbell, Steven L; Tolbert, Leon M

So far, vehicular power electronics integration is limited to the integration of on-board battery chargers (OBC) into the traction drive system and sometimes to the accessory dc/dc converters in plug-in electric vehicles (PEV). These integration approaches do not provide isolation from the grid although it is an important feature that is required for user interface systems that have grid connections. This is therefore a major limitation that needs to be addressed along with the integrated functionality. Furthermore, there is no previous study that proposes the integration of wireless charger with the other on-board components. This study features a unique waymore » of combining the wired and wireless charging functionalities with vehicle side boost converter integration and maintaining the isolation to provide the best solution to the plug-in electric vehicle users. The new topology is additionally compared with commercially available OBC systems from manufacturers.« less

Multi-voxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

PubMed Central

Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.; Munhall, Kevin G.; Cusack, Rhodri; Johnsrude, Ingrid S.

2013-01-01

The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations within a multi-voxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was employed to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during vocalization, compared to during passive listening. One network of regions appears to encode an ‘error signal’ irrespective of acoustic features of the error: this network, including right angular gyrus, right supplementary motor area, and bilateral cerebellum, yielded consistent neural patterns across acoustically different, distorted feedback types, only during articulation (not during passive listening). In contrast, a fronto-temporal network appears sensitive to the speech features of auditory stimuli during passive listening; this preference for speech features was diminished when the same stimuli were presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Taken together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple, interactive, functionally differentiated neural systems. PMID:23467350

B-spline tight frame based force matching method

NASA Astrophysics Data System (ADS)

Yang, Jianbin; Zhu, Guanhua; Tong, Dudu; Lu, Lanyuan; Shen, Zuowei

2018-06-01

In molecular dynamics simulations, compared with popular all-atom force field approaches, coarse-grained (CG) methods are frequently used for the rapid investigations of long time- and length-scale processes in many important biological and soft matter studies. The typical task in coarse-graining is to derive interaction force functions between different CG site types in terms of their distance, bond angle or dihedral angle. In this paper, an ℓ1-regularized least squares model is applied to form the force functions, which makes additional use of the B-spline wavelet frame transform in order to preserve the important features of force functions. The B-spline tight frames system has a simple explicit expression which is useful for representing our force functions. Moreover, the redundancy of the system offers more resilience to the effects of noise and is useful in the case of lossy data. Numerical results for molecular systems involving pairwise non-bonded, three and four-body bonded interactions are obtained to demonstrate the effectiveness of our approach.

Genome Editing to Study Ca2+ Homeostasis in Zebrafish Cone Photoreceptors.

PubMed

Brockerhoff, Susan E

2017-01-01

Photoreceptors are specialized sensory neurons with unique biological features. Phototransduction is well understood due in part to the exclusive expression and function of the molecular components of this cascade. Many other processes are less well understood, but also extremely important for understanding photoreceptor function and for treating disease. One example is the role of Ca 2+ in the cell body and overall compartmentalization and regulation of Ca 2+ within the cell. The recent development of CRISPR/Cas9 genome editing techniques has made it possible to rapidly and cheaply alter specific genes. This will help to define the biological function of elusive processes that have been more challenging to study. CRISPR/Cas9 has been optimized in many systems including zebrafish, which already has some distinct advantages for studying photoreceptor biology and function. These new genome editing technologies and the continued use of the zebrafish model system will help advance our understanding of important understudied aspects of photoreceptor biology.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Long-term assessment of the physical, mental, and sexual health among transsexual women.

PubMed

Weyers, Steven; Elaut, Els; De Sutter, Petra; Gerris, Jan; T'Sjoen, Guy; Heylens, Gunter; De Cuypere, Griet; Verstraelen, Hans

2009-03-01

Transsexualism is the most extreme form of gender identity disorder and most transsexuals eventually pursue sex reassignment surgery (SRS). In transsexual women, this comprises removal of the male reproductive organs, creation of a neovagina and clitoris, and often implantation of breast prostheses. Studies have shown good sexual satisfaction after transition. However, long-term follow-up data on physical, mental and sexual functioning are lacking. To gather information on physical, mental, and sexual well-being, health-promoting behavior and satisfaction with gender-related body features of transsexual women who had undergone SRS. Fifty transsexual women who had undergone SRS >or=6 months earlier were recruited. Self-reported physical and mental health using the Dutch version of the Short-Form-36 (SF-36) Health Survey; sexual functioning using the Dutch version of the Female Sexual Function Index (FSFI). Satisfaction with gender-related bodily features as well as with perceived female appearance; importance of sex, relationship quality, necessity and advisability of gynecological exams, as well as health concerns and feelings of regret concerning transition were scored. Compared with reference populations, transsexual women scored good on physical and mental level (SF-36). Gender-related bodily features were shown to be of high value. Appreciation of their appearance as perceived by others, as well as their own satisfaction with their self-image as women obtained a good score (8 and 9, respectively). However, sexual functioning as assessed through FSFI was suboptimal when compared with biological women, especially the sublevels concerning arousal, lubrication, and pain. Superior scores concerning sexual function were obtained in those transsexual women who were in a relationship and in heterosexuals. Transsexual women function well on a physical, emotional, psychological and social level. With respect to sexuality, they suffer from specific difficulties, especially concerning arousal, lubrication, and pain.

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.

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.

[Advances of portable electrocardiogram monitor design].

PubMed

Ding, Shenping; Wang, Yinghai; Wu, Weirong; Deng, Lingli; Lu, Jidong

2014-06-01

Portable electrocardiogram monitor is an important equipment in the clinical diagnosis of cardiovascular diseases due to its portable, real-time features. It has a broad application and development prospects in China. In the present review, previous researches on the portable electrocardiogram monitors have been arranged, analyzed and summarized. According to the characteristics of the electrocardiogram (ECG), this paper discusses the ergonomic design of the portable electrocardiogram monitor, including hardware and software. The circuit components and software modules were parsed from the ECG features and system functions. Finally, the development trend and reference are provided for the portable electrocardiogram monitors and for the subsequent research and product design.

Avian Egg and Egg Coat.

PubMed

Okumura, Hiroki

2017-01-01

An ovulated egg of vertebrates is surrounded by unique extracellular matrix, the egg coat or zona pellucida, playing important roles in fertilization and early development. The vertebrate egg coat is composed of two to six zona pellucida (ZP) glycoproteins that are characterized by the evolutionarily conserved ZP-domain module and classified into six subfamilies based on phylogenetic analyses. Interestingly, investigations of biochemical and functional features of the ZP glycoproteins show that the roles of each ZP-glycoprotein family member in the egg-coat formation and the egg-sperm interactions seemingly vary across vertebrates. This might be one reason why comprehensive understandings of the molecular basis of either architecture or physiological functions of egg coat still remain elusive despite more than 3 decades of intensive investigations. In this chapter, an overview of avian egg focusing on the oogenesis are provided in the first section, and unique features of avian egg coat, i.e., perivitelline layer, including the morphology, biogenesis pathway, and physiological functions are discussed mainly on chicken and quail in terms of the characteristics of ZP glycoproteins in the following sections. In addition, these features of avian egg coat are compared to mammalian zona pellucida, from the viewpoint that the structural and functional varieties of ZP glycoproteins might be associated with the evolutionary adaptation to their reproductive strategies. By comparing the egg coat of birds and mammals whose reproductive strategies are largely different, new insights into the molecular mechanisms of vertebrate egg-sperm interactions might be provided.

Conceptualizing neurodevelopmental disorders through a mechanistic understanding of fragile X syndrome and Williams syndrome.

PubMed

Fung, Lawrence K; Quintin, Eve-Marie; Haas, Brian W; Reiss, Allan L

2012-04-01

The overarching goal of this review is to compare and contrast the cognitive-behavioral features of fragile X syndrome (FraX) and Williams syndrome and to review the putative neural and molecular underpinnings of these features. Information is presented in a framework that provides guiding principles for conceptualizing gene-brain-behavior associations in neurodevelopmental disorders. Abnormalities, in particular cognitive-behavioral domains with similarities in underlying neurodevelopmental correlates, occur in both FraX and Williams syndrome including aberrant frontostriatal pathways leading to executive function deficits, and magnocellular/dorsal visual stream, superior parietal lobe, inferior parietal lobe, and postcentral gyrus abnormalities contributing to deficits in visuospatial function. Compelling cognitive-behavioral and neurodevelopmental contrasts also exist in these two disorders, for example, aberrant amygdala and fusiform cortex structure and function occurring in the context of contrasting social behavioral phenotypes, and temporal cortical and cerebellar abnormalities potentially underlying differences in language function. Abnormal dendritic development is a shared neurodevelopmental morphologic feature between FraX and Williams syndrome. Commonalities in molecular machinery and processes across FraX and Williams syndrome occur as well - microRNAs involved in translational regulation of major synaptic proteins; scaffolding proteins in excitatory synapses; and proteins involved in axonal development. Although the genetic variations leading to FraX and Williams syndrome are different, important similarities and contrasts in the phenotype, neurocircuitry, molecular machinery, and cellular processes in these two disorders allow for a unique approach to conceptualizing gene-brain-behavior links occurring in neurodevelopmental disorders.

Classification of pulmonary emphysema from chest CT scans using integral geometry descriptors

NASA Astrophysics Data System (ADS)

van Rikxoort, E. M.; Goldin, J. G.; Galperin-Aizenberg, M.; Brown, M. S.

2011-03-01

To gain insight into the underlying pathways of emphysema and monitor the effect of treatment, methods to quantify and phenotype the different types of emphysema from chest CT scans are of crucial importance. Current standard measures rely on density thresholds for individual voxels, which is influenced by inspiration level and does not take into account the spatial relationship between voxels. Measures based on texture analysis do take the interrelation between voxels into account and therefore might be useful for distinguishing different types of emphysema. In this study, we propose to use Minkowski functionals combined with rotation invariant Gaussian features to distinguish between healthy and emphysematous tissue and classify three different types of emphysema. Minkowski functionals characterize binary images in terms of geometry and topology. In 3D, four Minkowski functionals are defined. By varying the threshold and size of neighborhood around a voxel, a set of Minkowski functionals can be defined for each voxel. Ten chest CT scans with 1810 annotated regions were used to train the method. A set of 108 features was calculated for each training sample from which 10 features were selected to be most informative. A linear discriminant classifier was trained to classify each voxel in the lungs into a subtype of emphysema or normal lung. The method was applied to an independent test set of 30 chest CT scans with varying amounts and types of emphysema with 4347 annotated regions of interest. The method is shown to perform well, with an overall accuracy of 95%.

Uniform functional structure across spatial scales in an intertidal benthic assemblage.

PubMed

Barnes, R S K; Hamylton, Sarah

2015-05-01

To investigate the causes of the remarkable similarity of emergent assemblage properties that has been demonstrated across disparate intertidal seagrass sites and assemblages, this study examined whether their emergent functional-group metrics are scale related by testing the null hypothesis that functional diversity and the suite of dominant functional groups in seagrass-associated macrofauna are robust structural features of such assemblages and do not vary spatially across nested scales within a 0.4 ha area. This was carried out via a lattice of 64 spatially referenced stations. Although densities of individual components were patchily dispersed across the locality, rank orders of importance of the 14 functional groups present, their overall functional diversity and evenness, and the proportions of the total individuals contained within each showed, in contrast, statistically significant spatial uniformity, even at areal scales <2 m(2). Analysis of the proportional importance of the functional groups in their geospatial context also revealed weaker than expected levels of spatial autocorrelation, and then only at the smaller scales and amongst the most dominant groups, and only a small number of negative correlations occurred between the proportional importances of the individual groups. In effect, such patterning was a surface veneer overlying remarkable stability of assemblage functional composition across all spatial scales. Although assemblage species composition is known to be homogeneous in some soft-sediment marine systems over equivalent scales, this combination of patchy individual components yet basically constant functional-group structure seems as yet unreported. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biophysical functionality in polysaccharides: from Lego-blocks to nano-particles.

PubMed

Cesàro, Attilio; Bellich, Barbara; Borgogna, Massimiliano

2012-04-01

The objective of the paper is to show the very important biophysical concepts that have been developed with polysaccharides. In particular, an attempt will be made to relate "a posteriori" the fundamental aspects, both experimental and theoretical, with some industrial applications of polysaccharide-based materials. The overview of chain conformational aspects includes relationships between topological features and local dynamics, exemplified for some naturally occurring carbohydrate polymers. Thus, by using simulation techniques and computational studies, the physicochemical properties of aqueous solutions of polysaccharides are interpreted. The relevance of conformational disorder-order transitions, chain aggregation, and phase separation to the underlying role of the ionic contribution to these processes is discussed. We stress the importance of combining information from analysis of experimental data with that from statistical-thermodynamic models for understanding the conformation, size, and functional stability of industrially important polysaccharides. The peculiar properties of polysaccharides in industrial applications are summarized for the particularly important example of nanoparticles production, a field of growing relevance and scientific interest.

Persistent bias in expert judgments about free will and moral responsibility: a test of the expertise defense.

PubMed

Schulz, Eric; Cokely, Edward T; Feltz, Adam

2011-12-01

Many philosophers appeal to intuitions to support some philosophical views. However, there is reason to be concerned about this practice as scientific evidence has documented systematic bias in philosophically relevant intuitions as a function of seemingly irrelevant features (e.g., personality). One popular defense used to insulate philosophers from these concerns holds that philosophical expertise eliminates the influence of these extraneous factors. Here, we test this assumption. We present data suggesting that verifiable philosophical expertise in the free will debate-as measured by a reliable and validated test of expert knowledge-does not eliminate the influence of one important extraneous feature (i.e., the heritable personality trait extraversion) on judgments concerning freedom and moral responsibility. These results suggest that, in at least some important cases, the expertise defense fails. Implications for the practice of philosophy, experimental philosophy, and applied ethics are discussed. Copyright © 2011 Elsevier Inc. All rights reserved.

Human red blood cell recognition enhancement with three-dimensional morphological features obtained by digital holographic imaging

NASA Astrophysics Data System (ADS)

Jaferzadeh, Keyvan; Moon, Inkyu

2016-12-01

The classification of erythrocytes plays an important role in the field of hematological diagnosis, specifically blood disorders. Since the biconcave shape of red blood cell (RBC) is altered during the different stages of hematological disorders, we believe that the three-dimensional (3-D) morphological features of erythrocyte provide better classification results than conventional two-dimensional (2-D) features. Therefore, we introduce a set of 3-D features related to the morphological and chemical properties of RBC profile and try to evaluate the discrimination power of these features against 2-D features with a neural network classifier. The 3-D features include erythrocyte surface area, volume, average cell thickness, sphericity index, sphericity coefficient and functionality factor, MCH and MCHSD, and two newly introduced features extracted from the ring section of RBC at the single-cell level. In contrast, the 2-D features are RBC projected surface area, perimeter, radius, elongation, and projected surface area to perimeter ratio. All features are obtained from images visualized by off-axis digital holographic microscopy with a numerical reconstruction algorithm, and four categories of biconcave (doughnut shape), flat-disc, stomatocyte, and echinospherocyte RBCs are interested. Our experimental results demonstrate that the 3-D features can be more useful in RBC classification than the 2-D features. Finally, we choose the best feature set of the 2-D and 3-D features by sequential forward feature selection technique, which yields better discrimination results. We believe that the final feature set evaluated with a neural network classification strategy can improve the RBC classification accuracy.

Constrained clusters of gene expression profiles with pathological features.

PubMed

Sese, Jun; Kurokawa, Yukinori; Monden, Morito; Kato, Kikuya; Morishita, Shinichi

2004-11-22

Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

Flexible feature interface for multimedia sources

DOEpatents

Coffland, Douglas R [Livermore, CA

2009-06-09

A flexible feature interface for multimedia sources system that includes a single interface for the addition of features and functions to multimedia sources and for accessing those features and functions from remote hosts. The interface utilizes the export statement: export "C" D11Export void FunctionName(int argc, char ** argv,char * result, SecureSession *ctrl) or the binary equivalent of the export statement.

Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro.

PubMed

Schroeter, Manuel S; Charlesworth, Paul; Kitzbichler, Manfred G; Paulsen, Ole; Bullmore, Edward T

2015-04-08

Recent studies demonstrated that the anatomical network of the human brain shows a "rich-club" organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called "hub neurons"). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a "rich-get-richer" growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. Copyright © 2015 the authors 0270-6474/15/355459-12$15.00/0.

Resting-state fMRI and social cognition: An opportunity to connect.

PubMed

Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

2017-09-01

Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

Multifarious Roles of Intrinsic Disorder in Proteins Illustrate Its Broad Impact on Plant Biology

PubMed Central

Sun, Xiaolin; Rikkerink, Erik H.A.; Jones, William T.; Uversky, Vladimir N.

2013-01-01

Intrinsically disordered proteins (IDPs) are highly abundant in eukaryotic proteomes. Plant IDPs play critical roles in plant biology and often act as integrators of signals from multiple plant regulatory and environmental inputs. Binding promiscuity and plasticity allow IDPs to interact with multiple partners in protein interaction networks and provide important functional advantages in molecular recognition through transient protein–protein interactions. Short interaction-prone segments within IDPs, termed molecular recognition features, represent potential binding sites that can undergo disorder-to-order transition upon binding to their partners. In this review, we summarize the evidence for the importance of IDPs in plant biology and evaluate the functions associated with intrinsic disorder in five different types of plant protein families experimentally confirmed as IDPs. Functional studies of these proteins illustrate the broad impact of disorder on many areas of plant biology, including abiotic stress, transcriptional regulation, light perception, and development. Based on the roles of disorder in the protein–protein interactions, we propose various modes of action for plant IDPs that may provide insight for future experimental approaches aimed at understanding the molecular basis of protein function within important plant pathways. PMID:23362206

Understanding regulatory networks requires more than computing a multitude of graph statistics. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin et al.

NASA Astrophysics Data System (ADS)

Tkačik, Gašper

2016-07-01

The article by O. Martin and colleagues provides a much needed systematic review of a body of work that relates the topological structure of genetic regulatory networks to evolutionary selection for function. This connection is very important. Using the current wealth of genomic data, statistical features of regulatory networks (e.g., degree distributions, motif composition, etc.) can be quantified rather easily; it is, however, often unclear how to interpret the results. On a graph theoretic level the statistical significance of the results can be evaluated by comparing observed graphs to ;randomized; ones (bravely ignoring the issue of how precisely to randomize!) and comparing the frequency of appearance of a particular network structure relative to a randomized null expectation. While this is a convenient operational test for statistical significance, its biological meaning is questionable. In contrast, an in-silico genotype-to-phenotype model makes explicit the assumptions about the network function, and thus clearly defines the expected network structures that can be compared to the case of no selection for function and, ultimately, to data.

Variability in Cadence During Forced Cycling Predicts Motor Improvement in Individuals With Parkinson’s Disease

PubMed Central

Ridgel, Angela L.; Abdar, Hassan Mohammadi; Alberts, Jay L.; Discenzo, Fred M.; Loparo, Kenneth A.

2014-01-01

Variability in severity and progression of Parkinson’s disease symptoms makes it challenging to design therapy interventions that provide maximal benefit. Previous studies showed that forced cycling, at greater pedaling rates, results in greater improvements in motor function than voluntary cycling. The precise mechanism for differences in function following exercise is unknown. We examined the complexity of biomechanical and physiological features of forced and voluntary cycling and correlated these features to improvements in motor function as measured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Heart rate, cadence, and power were analyzed using entropy signal processing techniques. Pattern variability in heart rate and power were greater in the voluntary group when compared to forced group. In contrast, variability in cadence was higher during forced cycling. UPDRS Motor III scores predicted from the pattern variability data were highly correlated to measured scores in the forced group. This study shows how time series analysis methods of biomechanical and physiological parameters of exercise can be used to predict improvements in motor function. This knowledge will be important in the development of optimal exercise-based rehabilitation programs for Parkinson’s disease. PMID:23144045

Molecular Characterization of LubX: Functional Divergence of the U-Box Fold by Legionella pneumophila.

PubMed

Quaile, Andrew T; Urbanus, Malene L; Stogios, Peter J; Nocek, Boguslaw; Skarina, Tatiana; Ensminger, Alexander W; Savchenko, Alexei

2015-08-04

LubX is part of the large arsenal of effectors in Legionella pneumophila that are translocated into the host cytosol during infection. Despite such unique features as the presence of two U-box motifs and its targeting of another effector SidH, the molecular basis of LubX activity remains poorly understood. Here we show that the N terminus of LubX is able to activate an extended number of ubiquitin-conjugating (E2) enzymes including UBE2W, UBEL6, and all tested members of UBE2D and UBE2E families. Crystal structures of LubX alone and in complex with UBE2D2 revealed drastic molecular diversification between the two U-box domains, with only the N-terminal U-box retaining E2 recognition features typical for its eukaryotic counterparts. Extensive mutagenesis followed by functional screening in a yeast model system captured functionally important LubX residues including Arg121, critical for interactions with SidH. Combined, these data provide a new molecular insight into the function of this unique pathogenic factor. Copyright © 2015 Elsevier Ltd. All rights reserved.

Probability mapping of scarred myocardium using texture and intensity features in CMR images

PubMed Central

2013-01-01

Background The myocardium exhibits heterogeneous nature due to scarring after Myocardial Infarction (MI). In Cardiac Magnetic Resonance (CMR) imaging, Late Gadolinium (LG) contrast agent enhances the intensity of scarred area in the myocardium. Methods In this paper, we propose a probability mapping technique using Texture and Intensity features to describe heterogeneous nature of the scarred myocardium in Cardiac Magnetic Resonance (CMR) images after Myocardial Infarction (MI). Scarred tissue and non-scarred tissue are represented with high and low probabilities, respectively. Intermediate values possibly indicate areas where the scarred and healthy tissues are interwoven. The probability map of scarred myocardium is calculated by using a probability function based on Bayes rule. Any set of features can be used in the probability function. Results In the present study, we demonstrate the use of two different types of features. One is based on the mean intensity of pixel and the other on underlying texture information of the scarred and non-scarred myocardium. Examples of probability maps computed using the mean intensity of pixel and the underlying texture information are presented. We hypothesize that the probability mapping of myocardium offers alternate visualization, possibly showing the details with physiological significance difficult to detect visually in the original CMR image. Conclusion The probability mapping obtained from the two features provides a way to define different cardiac segments which offer a way to identify areas in the myocardium of diagnostic importance (like core and border areas in scarred myocardium). PMID:24053280

Feature extraction via KPCA for classification of gait patterns.

PubMed

Wu, Jianning; Wang, Jue; Liu, Li

2007-06-01

Automated recognition of gait pattern change is important in medical diagnostics as well as in the early identification of at-risk gait in the elderly. We evaluated the use of Kernel-based Principal Component Analysis (KPCA) to extract more gait features (i.e., to obtain more significant amounts of information about human movement) and thus to improve the classification of gait patterns. 3D gait data of 24 young and 24 elderly participants were acquired using an OPTOTRAK 3020 motion analysis system during normal walking, and a total of 36 gait spatio-temporal and kinematic variables were extracted from the recorded data. KPCA was used first for nonlinear feature extraction to then evaluate its effect on a subsequent classification in combination with learning algorithms such as support vector machines (SVMs). Cross-validation test results indicated that the proposed technique could allow spreading the information about the gait's kinematic structure into more nonlinear principal components, thus providing additional discriminatory information for the improvement of gait classification performance. The feature extraction ability of KPCA was affected slightly with different kernel functions as polynomial and radial basis function. The combination of KPCA and SVM could identify young-elderly gait patterns with 91% accuracy, resulting in a markedly improved performance compared to the combination of PCA and SVM. These results suggest that nonlinear feature extraction by KPCA improves the classification of young-elderly gait patterns, and holds considerable potential for future applications in direct dimensionality reduction and interpretation of multiple gait signals.

Diverse Supramolecular Nanofiber Networks Assembled by Functional Low-Complexity Domains.

PubMed

An, Bolin; Wang, Xinyu; Cui, Mengkui; Gui, Xinrui; Mao, Xiuhai; Liu, Yan; Li, Ke; Chu, Cenfeng; Pu, Jiahua; Ren, Susu; Wang, Yanyi; Zhong, Guisheng; Lu, Timothy K; Liu, Cong; Zhong, Chao

2017-07-25

Self-assembling supramolecular nanofibers, common in the natural world, are of fundamental interest and technical importance to both nanotechnology and materials science. Despite important advances, synthetic nanofibers still lack the structural and functional diversity of biological molecules, and the controlled assembly of one type of molecule into a variety of fibrous structures with wide-ranging functional attributes remains challenging. Here, we harness the low-complexity (LC) sequence domain of fused in sarcoma (FUS) protein, an essential cellular nuclear protein with slow kinetics of amyloid fiber assembly, to construct random copolymer-like, multiblock, and self-sorted supramolecular fibrous networks with distinct structural features and fluorescent functionalities. We demonstrate the utilities of these networks in the templated, spatially controlled assembly of ligand-decorated gold nanoparticles, quantum dots, nanorods, DNA origami, and hybrid structures. Owing to the distinguishable nanoarchitectures of these nanofibers, this assembly is structure-dependent. By coupling a modular genetic strategy with kinetically controlled complex supramolecular self-assembly, we demonstrate that a single type of protein molecule can be used to engineer diverse one-dimensional supramolecular nanostructures with distinct functionalities.

Thumb-loops up for catalysis: a structure/function investigation of a functional loop movement in a GH11 xylanase

PubMed Central

Paës, Gabriel; Cortés, Juan; Siméon, Thierry; O'Donohue, Michael J.; Tran, Vinh

2012-01-01

Dynamics is a key feature of enzyme catalysis. Unfortunately, current experimental and computational techniques do not yet provide a comprehensive understanding and description of functional macromolecular motions. In this work, we have extended a novel computational technique, which combines molecular modeling methods and robotics algorithms, to investigate functional motions of protein loops. This new approach has been applied to study the functional importance of the so-called thumb-loop in the glycoside hydrolase family 11 xylanase from Thermobacillus xylanilyticus (Tx-xyl). The results obtained provide new insight into the role of the loop in the glycosylation/deglycosylation catalytic cycle, and underline the key importance of the nature of the residue located at the tip of the thumb-loop. The effect of mutations predicted in silico has been validated by in vitro site-directed mutagenesis experiments. Overall, we propose a comprehensive model of Tx-xyl catalysis in terms of substrate and product dynamics by identifying the action of the thumb-loop motion during catalysis. PMID:24688637

Disrupted reward and cognitive control networks contribute to anhedonia in depression.

PubMed

Gong, Liang; He, Cancan; Zhang, Haisan; Zhang, Hongxing; Zhang, Zhijun; Xie, Chunming

2018-08-01

Neuroimaging studies have identified that anhedonia, a core feature of major depressive disorder (MDD), is associated with dysfunction in reward and cognitive control processing. However, it is still not clear how the reward network (β-network) and the cognitive control network (δ-network) are linked to biased anhedonia in MDD patients. Sixty-eight MDD patients and 64 cognitively normal (CN) subjects underwent a resting-state functional magnetic resonance imaging scan. A 2*2 ANCOVA analysis was used to explore the differences in the nucleus accumbens-based, voxelwise functional connectivity (FC) between the groups. Then, the β- and δ-networks were constructed, and the FC intensities were compared within and between theβ- and δ-networks across all subjects. Multiple linear regression analyses were also employed to investigate the relationships between the neural features of the β- and δ-networks and anhedonia in MDD patients. Compared to the CN subjects, the MDD patients showed synergistic functional decoupling in both the β- and δ-networks, as well as decreased FC intensities in the intra- and inter- β- and δ-networks. In addition, the FC in both the β- and δ-networks was significantly correlated with anhedonia severity in the MDD patients. Importantly, the integrated neural features of the β- and δ-networks could more precisely predict anhedonic symptoms. These findings initially demonstrated that the imbalance between β- and δ-network activity successfully predicted anhedonia severity and suggested that the neural features of both the β- and δ-networks could represent a fundamental mechanism that underlies anhedonia in MDD patients. Copyright © 2018 Elsevier Ltd. All rights reserved.

Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

PubMed

Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.

Circular RNAs: analysis, expression and potential functions

PubMed Central

Salzman, Julia

2016-01-01

Just a few years ago, it had been assumed that the dominant RNA isoforms produced from eukaryotic genes were variants of messenger RNA, functioning as intermediates in gene expression. In early 2012, however, a surprising discovery was made: circular RNA (circRNA) was shown to be a transcriptional product in thousands of human and mouse genes and in hundreds of cases constituted the dominant RNA isoform. Subsequent studies revealed that the expression of circRNAs is developmentally regulated, tissue and cell-type specific, and shared across the eukaryotic tree of life. These features suggest important functions for these molecules. Here, we describe major advances in the field of circRNA biology, focusing on the regulation of and functional roles played by these molecules. PMID:27246710

On the structural context and identification of enzyme catalytic residues.

PubMed

Chien, Yu-Tung; Huang, Shao-Wei

2013-01-01

Enzymes play important roles in most of the biological processes. Although only a small fraction of residues are directly involved in catalytic reactions, these catalytic residues are the most crucial parts in enzymes. The study of the fundamental and unique features of catalytic residues benefits the understanding of enzyme functions and catalytic mechanisms. In this work, we analyze the structural context of catalytic residues based on theoretical and experimental structure flexibility. The results show that catalytic residues have distinct structural features and context. Their neighboring residues, whether sequence or structure neighbors within specific range, are usually structurally more rigid than those of noncatalytic residues. The structural context feature is combined with support vector machine to identify catalytic residues from enzyme structure. The prediction results are better or comparable to those of recent structure-based prediction methods.

Functional connectivity between amygdala and facial regions involved in recognition of facial threat

PubMed Central

Harada, Tokiko; Ruffman, Ted; Sadato, Norihiro; Iidaka, Tetsuya

2013-01-01

The recognition of threatening faces is important for making social judgments. For example, threatening facial features of defendants could affect the decisions of jurors during a trial. Previous neuroimaging studies using faces of members of the general public have identified a pivotal role of the amygdala in perceiving threat. This functional magnetic resonance imaging study used face photographs of male prisoners who had been convicted of first-degree murder (MUR) as threatening facial stimuli. We compared the subjective ratings of MUR faces with those of control (CON) faces and examined how they were related to brain activation, particularly, the modulation of the functional connectivity between the amygdala and other brain regions. The MUR faces were perceived to be more threatening than the CON faces. The bilateral amygdala was shown to respond to both MUR and CON faces, but subtraction analysis revealed no significant difference between the two. Functional connectivity analysis indicated that the extent of connectivity between the left amygdala and the face-related regions (i.e. the superior temporal sulcus, inferior temporal gyrus and fusiform gyrus) was correlated with the subjective threat rating for the faces. We have demonstrated that the functional connectivity is modulated by vigilance for threatening facial features. PMID:22156740

The mid-fusiform sulcus: A landmark identifying both cytoarchitectonic and functional divisions of human ventral temporal cortex

PubMed Central

Weiner, Kevin S.; Golarai, Golijeh; Caspers, Julian; Chuapoco, Miguel R.; Mohlberg, Hartmut; Zilles, Karl; Amunts, Katrin; Grill-Spector, Kalanit

2014-01-01

Human ventral temporal cortex (VTC) plays a pivotal role in high-level vision. An under-studied macroanatomical feature of VTC is the mid-fusiform sulcus (MFS), a shallow longitudinal sulcus separating the lateral and medial fusiform gyrus (FG). Here, we quantified the morphological features of the MFS in 69 subjects (ages 7–40), and investigated its relationship to both cytoarchitectonic and functional divisions of VTC with four main findings. First, despite being a minor sulcus, we found that the MFS is a stable macroanatomical structure present in all 138 hemispheres with morphological characteristics developed by age 7. Second, the MFS is the locus of a lateral-medial cytoarchitechtonic transition within the posterior FG serving as the boundary between cytoarchitectonic regions FG1 and FG2. Third, the MFS predicts a lateral-medial functional transition in eccentricity bias representations in children, adolescents, and adults. Fourth, the anterior tip of the MFS predicts the location of a face-selective region, mFus-faces/FFA-2. These findings are the first to illustrate that a macroanatomical landmark identifies both cytoarchitectonic and functional divisions of high-level sensory cortex in humans and have important implications for understanding functional and structural organization in the human brain. PMID:24021838

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

Neuropsychological functioning in Wernicke's encephalopathy

PubMed Central

Behura, Sushree Sangita; Swain, Sarada Prasanna

2015-01-01

Context: Wernicke's encephalopathy (WE) is caused by thiamine (Vitamin B1) deficiency and most commonly found in chronic alcoholism and malnutrition. Clinically, the key features are mental status disturbances (global confusion), oculomotor abnormalities, and gait disturbances (ataxia). Apart from these clinical features, we can find deficits in neuropsychological functioning in patients with WE, which is more prominent after the improvement in the physical conditions. Neuropsychological functioning includes both basic cognitive processes (i.e., attention-concentration) as well as higher order cognitive processes (i.e., memory, executive functioning, reasoning), which is much vital for the maintenance of quality of life of an individual. However, unfortunately, in most of the cases, neuropsychological functioning is ignored by the clinicians. Materials and Methods: In this study four case reports of WE have been presented. The patients were taken from the outdoor department of Mental Health Institute, S.C.B. Medical College, Cuttack, Odisha. Neuropsychological functioning was measured by administration of PGIBBD and Quality of Life was measured by WHO-QOL BREF Odia Version. Discussion: As described in the literature, among the three cardinal signs (global confusion, ataxia, and ocular sings), the first two were present in all cases, but nystagmus was present in only two cases. Memory dysfunction was so disabling that the persons were unable to maintain a good Quality of Life and occupational impairment was prominent. There are disturbances in recent, remote memory, immediate recall, delayed recall, and attention and concentration, ultimately creating both physical and mental disability. PGI-BBD findings also suggest the overall impairment in neuropsychological functioning other than memory, that is, executive functioning, visual acuity, and depth perception. Findings of WHO-QOL BREF suggest the impairment of four domains of QOL in all the cases, but the severity level varies from person to person. Conclusion: Like the three cardinal features, neuropsychological dysfunction in WE should be given importance, which is a most vital component for the maintenance of QOL. As a result, the disability produced by this condition can be well managed. PMID:26257495

The Function of Embryonic Stem Cell-expressed RAS (E-RAS), a Unique RAS Family Member, Correlates with Its Additional Motifs and Its Structural Properties.

PubMed

Nakhaei-Rad, Saeideh; Nakhaeizadeh, Hossein; Kordes, Claus; Cirstea, Ion C; Schmick, Malte; Dvorsky, Radovan; Bastiaens, Philippe I H; Häussinger, Dieter; Ahmadian, Mohammad Reza

2015-06-19

E-RAS is a member of the RAS family specifically expressed in embryonic stem cells, gastric tumors, and hepatic stellate cells. Unlike classical RAS isoforms (H-, N-, and K-RAS4B), E-RAS has, in addition to striking and remarkable sequence deviations, an extended 38-amino acid-long unique N-terminal region with still unknown functions. We investigated the molecular mechanism of E-RAS regulation and function with respect to its sequence and structural features. We found that N-terminal extension of E-RAS is important for E-RAS signaling activity. E-RAS protein most remarkably revealed a different mode of effector interaction as compared with H-RAS, which correlates with deviations in the effector-binding site of E-RAS. Of all these residues, tryptophan 79 (arginine 41 in H-RAS), in the interswitch region, modulates the effector selectivity of RAS proteins from H-RAS to E-RAS features. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Nanoclustering as a dominant feature of plasma membrane organization.

PubMed

Garcia-Parajo, Maria F; Cambi, Alessandra; Torreno-Pina, Juan A; Thompson, Nancy; Jacobson, Ken

2014-12-01

Early studies have revealed that some mammalian plasma membrane proteins exist in small nanoclusters. The advent of super-resolution microscopy has corroborated and extended this picture, and led to the suggestion that many, if not most, membrane proteins are clustered at the plasma membrane at nanoscale lengths. In this Commentary, we present selected examples of glycosylphosphatidyl-anchored proteins, Ras family members and several immune receptors that provide evidence for nanoclustering. We advocate the view that nanoclustering is an important part of the hierarchical organization of proteins in the plasma membrane. According to this emerging picture, nanoclusters can be organized on the mesoscale to form microdomains that are capable of supporting cell adhesion, pathogen binding and immune cell-cell recognition amongst other functions. Yet, a number of outstanding issues concerning nanoclusters remain open, including the details of their molecular composition, biogenesis, size, stability, function and regulation. Notions about these details are put forth and suggestions are made about nanocluster function and why this general feature of protein nanoclustering appears to be so prevalent. © 2014. Published by The Company of Biologists Ltd.

The role of experiential avoidance, psychopathology, and borderline personality features in experiencing positive emotions: a path analysis.

PubMed

Jacob, Gitta A; Ower, Nicole; Buchholz, Angela

2013-03-01

Experiential avoidance (EA) is an important factor in maintaining different forms of psychopathology including borderline personality pathology (BPD). So far little is known about the functions of EA, BPD features and general psychopathology for positive emotions. In this study we investigated three different anticipated pathways of their influence on positive emotions. A total of 334 subjects varying in general psychopathology &/or BPD features completed an online survey including self-ratings of BPD features, psychopathology, negative and positive emotions, and EA. Measures of positive emotions included both a general self-rating (PANAS) and emotional changes induced by two positive movie clips. Data were analyzed by means of path analysis. In comparing the three path models, one model was found clearly superior: In this model, EA acts as a mediator of the influence of psychopathology, BPD features, and negative emotions in the prediction of both measures of positive emotions. EA plays a central role in maintaining lack of positive emotions. Therapeutic implications and study limitations are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Feature-based interference from unattended visual field during attentional tracking in younger and older adults.

PubMed

Störmer, Viola S; Li, Shu-Chen; Heekeren, Hauke R; Lindenberger, Ulman

2011-02-01

The ability to attend to multiple objects that move in the visual field is important for many aspects of daily functioning. The attentional capacity for such dynamic tracking, however, is highly limited and undergoes age-related decline. Several aspects of the tracking process can influence performance. Here, we investigated effects of feature-based interference from distractor objects that appear in unattended regions of the visual field with a hemifield-tracking task. Younger and older participants performed an attentional tracking task in one hemifield while distractor objects were concurrently presented in the unattended hemifield. Feature similarity between objects in the attended and unattended hemifields as well as motion speed and the number of to-be-tracked objects were parametrically manipulated. The results show that increasing feature overlap leads to greater interference from the unattended visual field. This effect of feature-based interference was only present in the slow speed condition, indicating that the interference is mainly modulated by perceptual demands. High-performing older adults showed a similar interference effect as younger adults, whereas low-performing adults showed poor tracking performance overall.

Report of the Regional Literacy Seminar for Representatives of Non-Governmental Organizations in Asia (Colombo, Ceylon, January 18-28, 1970).

ERIC Educational Resources Information Center

World Association of Girl Guides and Girl Scouts, London (England).

This report highlights the main features of each talk and discussion given at the seminar and pinpoints conclusions reached. The seminar made a number of recommendations, which include: (1) that Unesco place greater emphasis in all future functional literacy projects on the importance of literacy as a factor in the civic and political education of…

Second feature of the matter two-point function

NASA Astrophysics Data System (ADS)

Tansella, Vittorio

2018-05-01

We point out the existence of a second feature in the matter two-point function, besides the acoustic peak, due to the baryon-baryon correlation in the early Universe and positioned at twice the distance of the peak. We discuss how the existence of this feature is implied by the well-known heuristic argument that explains the baryon bump in the correlation function. A standard χ2 analysis to estimate the detection significance of the second feature is mimicked. We conclude that, for realistic values of the baryon density, a SKA-like galaxy survey will not be able to detect this feature with standard correlation function analysis.

Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis.

PubMed

Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

2014-01-01

Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. The aims were to describe how to:(i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and(ii) automatically identify the features that best distinguish the groups. The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described - simple or complex; presentation order - which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo 18 were used,which included 200 healthy Brazilians of both genders. A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods.

Stellar Initial Mass Function: Trends With Galaxy Mass And Radius

NASA Astrophysics Data System (ADS)

Parikh, Taniya

2017-06-01

There is currently no consensus about the exact shape and, in particular, the universality of the stellar initial mass function (IMF). For massive galaxies, it has been found that near-infrared (NIR) absorption features, which are sensitive to the ratio of dwarf to giant stars, deviate from a Milky Way-like IMF; their modelling seems to require a larger fraction of low mass stars. There are now increasing results looking at whether the IMF varies not only with galaxy mass, but also radially within galaxies. The SDSS-IV/MaNGA integral-field survey will provide spatially resolved spectroscopy for 10,000 galaxies at R 2000 from 360-1000nm. Spectra of early-type galaxies were stacked to achieve high S/N which is particularly important for features in the NIR. Trends with galaxy radius and mass were compared to stellar population models for a range of absorption features in order to separate degeneracies due to changes in stellar population parameters, such as age, metallicity and element abundances, with potential changes in the IMF. Results for 611 galaxies show that we do not require an IMF steeper than Kroupa as a function of galaxy mass or radius based on the NaI index. The Wing-Ford band hints towards a steeper IMF at large radii however we do not have reliable measurements for the most massive galaxies.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues.

PubMed

Guo, Song; Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues

PubMed Central

Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields. PMID:27034949

Cortical processing of dynamic sound envelope transitions.

PubMed

Zhou, Yi; Wang, Xiaoqin

2010-12-08

Slow envelope fluctuations in the range of 2-20 Hz provide important segmental cues for processing communication sounds. For a successful segmentation, a neural processor must capture envelope features associated with the rise and fall of signal energy, a process that is often challenged by the interference of background noise. This study investigated the neural representations of slowly varying envelopes in quiet and in background noise in the primary auditory cortex (A1) of awake marmoset monkeys. We characterized envelope features based on the local average and rate of change of sound level in envelope waveforms and identified envelope features to which neurons were selective by reverse correlation. Our results showed that envelope feature selectivity of A1 neurons was correlated with the degree of nonmonotonicity in their static rate-level functions. Nonmonotonic neurons exhibited greater feature selectivity than monotonic neurons in quiet and in background noise. The diverse envelope feature selectivity decreased spike-timing correlation among A1 neurons in response to the same envelope waveforms. As a result, the variability, but not the average, of the ensemble responses of A1 neurons represented more faithfully the dynamic transitions in low-frequency sound envelopes both in quiet and in background noise.

Statistics of Shared Components in Complex Component Systems

NASA Astrophysics Data System (ADS)

Mazzolini, Andrea; Gherardi, Marco; Caselle, Michele; Cosentino Lagomarsino, Marco; Osella, Matteo

2018-04-01

Many complex systems are modular. Such systems can be represented as "component systems," i.e., sets of elementary components, such as LEGO bricks in LEGO sets. The bricks found in a LEGO set reflect a target architecture, which can be built following a set-specific list of instructions. In other component systems, instead, the underlying functional design and constraints are not obvious a priori, and their detection is often a challenge of both scientific and practical importance, requiring a clear understanding of component statistics. Importantly, some quantitative invariants appear to be common to many component systems, most notably a common broad distribution of component abundances, which often resembles the well-known Zipf's law. Such "laws" affect in a general and nontrivial way the component statistics, potentially hindering the identification of system-specific functional constraints or generative processes. Here, we specifically focus on the statistics of shared components, i.e., the distribution of the number of components shared by different system realizations, such as the common bricks found in different LEGO sets. To account for the effects of component heterogeneity, we consider a simple null model, which builds system realizations by random draws from a universe of possible components. Under general assumptions on abundance heterogeneity, we provide analytical estimates of component occurrence, which quantify exhaustively the statistics of shared components. Surprisingly, this simple null model can positively explain important features of empirical component-occurrence distributions obtained from large-scale data on bacterial genomes, LEGO sets, and book chapters. Specific architectural features and functional constraints can be detected from occurrence patterns as deviations from these null predictions, as we show for the illustrative case of the "core" genome in bacteria.

Tiled vector data model for the geographical features of symbolized maps.

PubMed

Li, Lin; Hu, Wei; Zhu, Haihong; Li, You; Zhang, Hang

2017-01-01

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Peroxisome protein import: a complex journey.

PubMed

Baker, Alison; Lanyon-Hogg, Thomas; Warriner, Stuart L

2016-06-15

The import of proteins into peroxisomes possesses many unusual features such as the ability to import folded proteins, and a surprising diversity of targeting signals with differing affinities that can be recognized by the same receptor. As understanding of the structure and function of many components of the protein import machinery has grown, an increasingly complex network of factors affecting each step of the import pathway has emerged. Structural studies have revealed the presence of additional interactions between cargo proteins and the PEX5 receptor that affect import potential, with a subtle network of cargo-induced conformational changes in PEX5 being involved in the import process. Biochemical studies have also indicated an interdependence of receptor-cargo import with release of unloaded receptor from the peroxisome. Here, we provide an update on recent literature concerning mechanisms of protein import into peroxisomes. © 2016 The Author(s).

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

Protein domain organisation: adding order.

PubMed

Kummerfeld, Sarah K; Teichmann, Sarah A

2009-01-29

Domains are the building blocks of proteins. During evolution, they have been duplicated, fused and recombined, to produce proteins with novel structures and functions. Structural and genome-scale studies have shown that pairs or groups of domains observed together in a protein are almost always found in only one N to C terminal order and are the result of a single recombination event that has been propagated by duplication of the multi-domain unit. Previous studies of domain organisation have used graph theory to represent the co-occurrence of domains within proteins. We build on this approach by adding directionality to the graphs and connecting nodes based on their relative order in the protein. Most of the time, the linear order of domains is conserved. However, using the directed graph representation we have identified non-linear features of domain organization that are over-represented in genomes. Recognising these patterns and unravelling how they have arisen may allow us to understand the functional relationships between domains and understand how the protein repertoire has evolved. We identify groups of domains that are not linearly conserved, but instead have been shuffled during evolution so that they occur in multiple different orders. We consider 192 genomes across all three kingdoms of life and use domain and protein annotation to understand their functional significance. To identify these features and assess their statistical significance, we represent the linear order of domains in proteins as a directed graph and apply graph theoretical methods. We describe two higher-order patterns of domain organisation: clusters and bi-directionally associated domain pairs and explore their functional importance and phylogenetic conservation. Taking into account the order of domains, we have derived a novel picture of global protein organization. We found that all genomes have a higher than expected degree of clustering and more domain pairs in forward and reverse orientation in different proteins relative to random graphs with identical degree distributions. While these features were statistically over-represented, they are still fairly rare. Looking in detail at the proteins involved, we found strong functional relationships within each cluster. In addition, the domains tended to be involved in protein-protein interaction and are able to function as independent structural units. A particularly striking example was the human Jak-STAT signalling pathway which makes use of a set of domains in a range of orders and orientations to provide nuanced signaling functionality. This illustrated the importance of functional and structural constraints (or lack thereof) on domain organisation.

Baicalein Reduces Airway Injury in Allergen and IL-13 Induced Airway Inflammation

PubMed Central

Mabalirajan, Ulaganathan; Ahmad, Tanveer; Rehman, Rakhshinda; Leishangthem, Geeta Devi; Dinda, Amit Kumar; Agrawal, Anurag; Ghosh, Balaram; Sharma, Surendra Kumar

2013-01-01

Background Baicalein, a bioflavone present in the dry roots of Scutellaria baicalensis Georgi, is known to reduce eotaxin production in human fibroblasts. However, there are no reports of its anti-asthma activity or its effect on airway injury. Methodology/Principal Findings In a standard experimental asthma model, male Balb/c mice that were sensitized with ovalbumin (OVA), treated with baicalein (10 mg/kg, ip) or a vehicle control, either during (preventive use) or after OVA challenge (therapeutic use). In an alternate model, baicalein was administered to male Balb/c mice which were given either IL-4 or IL-13 intranasally. Features of asthma were determined by estimating airway hyperresponsiveness (AHR), histopathological changes and biochemical assays of key inflammatory molecules. Airway injury was determined with apoptotic assays, transmission electron microscopy and assessing key mitochondrial functions. Baicalein treatment reduced AHR and inflammation in both experimental models. TGF-β1, sub-epithelial fibrosis and goblet cell metaplasia, were also reduced. Furthermore, baicalein treatment significantly reduced 12/15-LOX activity, features of mitochondrial dysfunctions, and apoptosis of bronchial epithelia. Conclusion/Significance Our findings demonstrate that baicalein can attenuate important features of asthma, possibly through the reduction of airway injury and restoration of mitochondrial function. PMID:23646158

Open-Source GIS

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

Vatsavai, Raju; Burk, Thomas E; Lime, Steve

2012-01-01

The components making up an Open Source GIS are explained in this chapter. A map server (Sect. 30.1) can broadly be defined as a software platform for dynamically generating spatially referenced digital map products. The University of Minnesota MapServer (UMN Map Server) is one such system. Its basic features are visualization, overlay, and query. Section 30.2 names and explains many of the geospatial open source libraries, such as GDAL and OGR. The other libraries are FDO, JTS, GEOS, JCS, MetaCRS, and GPSBabel. The application examples include derived GIS-software and data format conversions. Quantum GIS, its origin and its applications explainedmore » in detail in Sect. 30.3. The features include a rich GUI, attribute tables, vector symbols, labeling, editing functions, projections, georeferencing, GPS support, analysis, and Web Map Server functionality. Future developments will address mobile applications, 3-D, and multithreading. The origins of PostgreSQL are outlined and PostGIS discussed in detail in Sect. 30.4. It extends PostgreSQL by implementing the Simple Feature standard. Section 30.5 details the most important open source licenses such as the GPL, the LGPL, the MIT License, and the BSD License, as well as the role of the Creative Commons.« less

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

PubMed Central

Forman-Kay, Julie D.; Mittag, Tanja

2015-01-01

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

From sequence and forces to structure, function, and evolution of intrinsically disordered proteins.

PubMed

Forman-Kay, Julie D; Mittag, Tanja

2013-09-03

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics, and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales, and compactness are shaping a unified understanding of structure-dynamics-disorder/function relationships. In the 20(th) anniversary of Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional, and evolutionary properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Single case studies as a means for developing psychological theories.

PubMed

Skvortsov, Anatoliy; Romashchuk, Alexander

2015-12-01

The Socratic function of single case studies (SCSs) is described in its relation to the problem of scientific theory development. Contrary to the traditional point of view, the single case study is not a demonstration or verification of theoretical concepts, but a method of their generation and opportunity for analysis of their interrelations. Considering the case study from the perspective of the Socratic function brings to light important conclusions about the ecological validity of theory development. The essential features of the Socratic function are illustrated using the example of the famous Romantic Essays of Alexandr Luria. © 2015 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

ESC Working Group on Myocardial Function Position Paper: how to study the right ventricle in experimental models.

PubMed

Leite-Moreira, Adelino F; Lourenço, André P; Balligand, Jean-Luc; Bauersachs, Johann; Clerk, Angela; De Windt, Leon J; Heymans, Stephane; Hilfiker-Kleiner, Denise; Hirsch, Emilio; Iaccarino, Guido; Kaminski, Karol A; Knöll, Ralph; Mayr, Manuel; Tarone, Guido; Thum, Thomas; Tocchetti, Carlo G

2014-05-01

The right ventricle has become an increasing focus in cardiovascular research. In this position paper, we give a brief overview of the specific pathophysiological features of the right ventricle, with particular emphasis on functional and molecular modifications as well as therapeutic strategies in chronic overload, highlighting the differences from the left ventricle. Importantly, we put together recommendations on promising topics of research in the field, experimental study design, and functional evaluation of the right ventricle in experimental models, from non-invasive methodologies to haemodynamic evaluation and ex vivo set-ups. © 2014 The Authors. European Journal of Heart Failure © 2014 European Society of Cardiology.

Advanced Inverter Functions and Communication Protocols for Distribution Management

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

Nagarajan, Adarsh; Palmintier, Bryan; Baggu, Murali

2016-05-05

This paper aims at identifying the advanced features required by distribution management systems (DMS) service providers to bring inverter-connected distributed energy resources into use as an intelligent grid resource. This work explores the standard functions needed in the future DMS for enterprise integration of distributed energy resources (DER). The important DMS functionalities such as DER management in aggregate groups, including the discovery of capabilities, status monitoring, and dispatch of real and reactive power are addressed in this paper. It is intended to provide the industry with a point of reference for DER integration with other utility applications and to providemore » guidance to research and standards development organizations.« less

cosmoabc: Likelihood-free inference for cosmology

NASA Astrophysics Data System (ADS)

Ishida, Emille E. O.; Vitenti, Sandro D. P.; Penna-Lima, Mariana; Trindade, Arlindo M.; Cisewski, Jessi; M.; de Souza, Rafael; Cameron, Ewan; Busti, Vinicius C.

2015-05-01

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.

The influence of iron deficiency on the functioning of skeletal muscles: experimental evidence and clinical implications.

PubMed

Stugiewicz, Magdalena; Tkaczyszyn, Michał; Kasztura, Monika; Banasiak, Waldemar; Ponikowski, Piotr; Jankowska, Ewa A

2016-07-01

Skeletal and respiratory myopathy not only constitutes an important pathophysiological feature of heart failure and chronic obstructive pulmonary disease, but also contributes to debilitating symptomatology and predicts worse outcomes in these patients. Accumulated evidence from laboratory experiments, animal models, and interventional studies in sports medicine suggests that undisturbed systemic iron homeostasis significantly contributes to the effective functioning of skeletal muscles. In this review, we discuss the role of iron status for the functioning of skeletal muscle tissue, and highlight iron deficiency as an emerging therapeutic target in chronic diseases accompanied by a marked muscle dysfunction. © 2016 The Authors. European Journal of Heart Failure © 2016 European Society of Cardiology.

Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate

PubMed Central

Padmanaban, Subash; Baker, Justin; Greger, Bradley

2018-01-01

Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding algorithm can be made robust by using optimal features and feature selection algorithms. We believe that even a few percent increase in performance is important and improves the decoding accuracy of the machine learning algorithm potentially increasing the ease of use of a brain machine interface. PMID:29467602

The haloarchaeal MCM proteins: bioinformatic analysis and targeted mutagenesis of the β7-β8 and β9-β10 hairpin loops and conserved zinc binding domain cysteines.

PubMed

Kristensen, Tatjana P; Maria Cherian, Reeja; Gray, Fiona C; MacNeill, Stuart A

2014-01-01

The hexameric MCM complex is the catalytic core of the replicative helicase in eukaryotic and archaeal cells. Here we describe the first in vivo analysis of archaeal MCM protein structure and function relationships using the genetically tractable haloarchaeon Haloferax volcanii as a model system. Hfx. volcanii encodes a single MCM protein that is part of the previously identified core group of haloarchaeal MCM proteins. Three structural features of the N-terminal domain of the Hfx. volcanii MCM protein were targeted for mutagenesis: the β7-β8 and β9-β10 β-hairpin loops and putative zinc binding domain. Five strains carrying single point mutations in the β7-β8 β-hairpin loop were constructed, none of which displayed impaired cell growth under normal conditions or when treated with the DNA damaging agent mitomycin C. However, short sequence deletions within the β7-β8 β-hairpin were not tolerated and neither was replacement of the highly conserved residue glutamate 187 with alanine. Six strains carrying paired alanine substitutions within the β9-β10 β-hairpin loop were constructed, leading to the conclusion that no individual amino acid within that hairpin loop is absolutely required for MCM function, although one of the mutant strains displays greatly enhanced sensitivity to mitomycin C. Deletions of two or four amino acids from the β9-β10 β-hairpin were tolerated but mutants carrying larger deletions were inviable. Similarly, it was not possible to construct mutants in which any of the conserved zinc binding cysteines was replaced with alanine, underlining the likely importance of zinc binding for MCM function. The results of these studies demonstrate the feasibility of using Hfx. volcanii as a model system for reverse genetic analysis of archaeal MCM protein function and provide important confirmation of the in vivo importance of conserved structural features identified by previous bioinformatic, biochemical and structural studies.

Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.

PubMed

Aksu, Yaman; Miller, David J; Kesidis, George; Yang, Qing X

2010-05-01

Feature selection for classification in high-dimensional spaces can improve generalization, reduce classifier complexity, and identify important, discriminating feature "markers." For support vector machine (SVM) classification, a widely used technique is recursive feature elimination (RFE). We demonstrate that RFE is not consistent with margin maximization, central to the SVM learning approach. We thus propose explicit margin-based feature elimination (MFE) for SVMs and demonstrate both improved margin and improved generalization, compared with RFE. Moreover, for the case of a nonlinear kernel, we show that RFE assumes that the squared weight vector 2-norm is strictly decreasing as features are eliminated. We demonstrate this is not true for the Gaussian kernel and, consequently, RFE may give poor results in this case. MFE for nonlinear kernels gives better margin and generalization. We also present an extension which achieves further margin gains, by optimizing only two degrees of freedom--the hyperplane's intercept and its squared 2-norm--with the weight vector orientation fixed. We finally introduce an extension that allows margin slackness. We compare against several alternatives, including RFE and a linear programming method that embeds feature selection within the classifier design. On high-dimensional gene microarray data sets, University of California at Irvine (UCI) repository data sets, and Alzheimer's disease brain image data, MFE methods give promising results.

Spin-Multiplet Components and Energy Splittings by Multistate Density Functional Theory.

PubMed

Grofe, Adam; Chen, Xin; Liu, Wenjian; Gao, Jiali

2017-10-05

Kohn-Sham density functional theory has been tremendously successful in chemistry and physics. Yet, it is unable to describe the energy degeneracy of spin-multiplet components with any approximate functional. This work features two contributions. (1) We present a multistate density functional theory (MSDFT) to represent spin-multiplet components and to determine multiplet energies. MSDFT is a hybrid approach, taking advantage of both wave function theory and density functional theory. Thus, the wave functions, electron densities and energy density-functionals for ground and excited states and for different components are treated on the same footing. The method is illustrated on valence excitations of atoms and molecules. (2) Importantly, a key result is that for cases in which the high-spin components can be determined separately by Kohn-Sham density functional theory, the transition density functional in MSDFT (which describes electronic coupling) can be defined rigorously. The numerical results may be explored to design and optimize transition density functionals for configuration coupling in multiconfigurational DFT.

A Structure-Function Study of RecA: The Structural Basis for ATP Specificity in the Strand Exchange Reaction

NASA Astrophysics Data System (ADS)

Gegner, Julie; Spruill, Natalie; Plesniak, Leigh A.

1999-11-01

The terms "structure" and "function" can assume a variety of meanings. In biochemistry, the "structure" of a protein can refer to its sequence of amino acids, the three-dimensional arrangement of atoms within a subunit, or the arrangement of subunits into a larger oligomeric or filamentous state. Likewise, the function of biological macromolecules can be examined at many levels. The function of a protein can be described by its role in an organism's survival or by a chemical reaction that it promotes. We have designed a three-part biochemical laboratory experiment that characterizes the structure and function of the Escherichia coli RecA protein. The first part examines the importance of RecA in the survival of bacteria that have been exposed to UV light. This is the broadest view of function of the enzyme. Second, the students use an in vitro assay of RecA whereby the protein promotes homologous recombination. Because RecA functions not catalytically, but rather stoichiometrically, in this recombination reaction, the oligomeric state of RecA in complex with DNA must also be discussed. Finally, through molecular modeling of X-ray crystallographic structures, students identify functionally important features of the ATP cofactor binding site of RecA.

Sparse Zero-Sum Games as Stable Functional Feature Selection

PubMed Central

Sokolovska, Nataliya; Teytaud, Olivier; Rizkalla, Salwa; Clément, Karine; Zucker, Jean-Daniel

2015-01-01

In large-scale systems biology applications, features are structured in hidden functional categories whose predictive power is identical. Feature selection, therefore, can lead not only to a problem with a reduced dimensionality, but also reveal some knowledge on functional classes of variables. In this contribution, we propose a framework based on a sparse zero-sum game which performs a stable functional feature selection. In particular, the approach is based on feature subsets ranking by a thresholding stochastic bandit. We provide a theoretical analysis of the introduced algorithm. We illustrate by experiments on both synthetic and real complex data that the proposed method is competitive from the predictive and stability viewpoints. PMID:26325268

Rough sets and Laplacian score based cost-sensitive feature selection

PubMed Central

Yu, Shenglong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of “good” features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. PMID:29912884

Rough sets and Laplacian score based cost-sensitive feature selection.

PubMed

Yu, Shenglong; Zhao, Hong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of "good" features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

Design and development of a novel balancer with variable difficulty for training and evaluation.

PubMed

Ang, W T; Tan, U-X; Tan, H G; Myo, T; Ng, C K; Koh, K L; Cheam, B S

2008-11-01

This paper presents a novel, portable and cost-effective balance trainer with the necessary important features to improve the reach of rehabilitation to the masses. There are three factors that contribute to a person's ability to maintain standing balance: Proprioceptive feedback (from the joints), vision, and the vestibular system. These systems can be affected by injury, infection, or brain damage caused by stroke. One example of such injuries is ankle injury. A large focus of the physiotherapy and sports medicine community is using postural-control tasks to prevent, assess and rehabilitate patients. Unfortunately, there are presently two extreme ends of balance training devices. On one end, there is high-end equipment which only large hospitals are capable of buying. On the other end are the simple balance boards which offer limited features. To develop the new balance trainer - the Pro.Balance - therapists at the Singapore General Hospital drafted a new 'wish list' of requirements. The prototype was built at the Nanyang Technological University, Singapore, and was commercialized by Lab Rehab Pte Ltd as the Pro.Balance. The device has a small footprint, incorporating only the most important and frequently used functions. These functions include being able to provide different levels of difficulty, setting different difficulties in different directions, the storing of a patient's performance, real-time visual feedback to aid the patient and different types of modes for different purposes. Springs are used to vary the amount of supporting moments, thus varying the difficulty levels. This paper describes the design and features of the Pro.Balance.

Chemical reactions directed Peptide self-assembly.

PubMed

Rasale, Dnyaneshwar B; Das, Apurba K

2015-05-13

Fabrication of self-assembled nanostructures is one of the important aspects in nanoscience and nanotechnology. The study of self-assembled soft materials remains an area of interest due to their potential applications in biomedicine. The versatile properties of soft materials can be tuned using a bottom up approach of small molecules. Peptide based self-assembly has significant impact in biology because of its unique features such as biocompatibility, straight peptide chain and the presence of different side chain functionality. These unique features explore peptides in various self-assembly process. In this review, we briefly introduce chemical reaction-mediated peptide self-assembly. Herein, we have emphasised enzymes, native chemical ligation and photochemical reactions in the exploration of peptide self-assembly.

Chemical Reactions Directed Peptide Self-Assembly

PubMed Central

Rasale, Dnyaneshwar B.; Das, Apurba K.

2015-01-01

Fabrication of self-assembled nanostructures is one of the important aspects in nanoscience and nanotechnology. The study of self-assembled soft materials remains an area of interest due to their potential applications in biomedicine. The versatile properties of soft materials can be tuned using a bottom up approach of small molecules. Peptide based self-assembly has significant impact in biology because of its unique features such as biocompatibility, straight peptide chain and the presence of different side chain functionality. These unique features explore peptides in various self-assembly process. In this review, we briefly introduce chemical reaction-mediated peptide self-assembly. Herein, we have emphasised enzymes, native chemical ligation and photochemical reactions in the exploration of peptide self-assembly. PMID:25984603

Mobile personal health records: an evaluation of features and functionality.

PubMed

Kharrazi, Hadi; Chisholm, Robin; VanNasdale, Dean; Thompson, Benjamin

2012-09-01

To evaluate stand-alone mobile personal health record (mPHR) applications for the three leading cellular phone platforms (iOS, BlackBerry, and Android), assessing each for content, function, security, and marketing characteristics. Nineteen stand-alone mPHR applications (8 for iOS, 5 for BlackBerry, and 6 for Android) were identified and evaluated. Main criteria used to include mPHRs were: operating standalone on a mobile platform; not requiring external connectivity; and covering a wide range of health topics. Selected mPHRs were analyzed considering product characteristics, data elements, and application features. We also reviewed additional features such as marketing tactics. Within and between the different mobile platforms attributes for the mPHR were highly variable. None of the mPHRs contained all attributes included in our evaluation. The top four mPHRs contained 13 of the 14 features omitting only the in-case-of emergency feature. Surprisingly, seven mPHRs lacked basic security measures as important as password protection. The mPHRs were relatively inexpensive: ranging from no cost to $9.99. The mPHR application cost varied in some instances based on whether it supported single or multiple users. Ten mPHRs supported multiple user profiles. Notably, eight mPHRs used scare tactics as marketing strategy. mPHR is an emerging health care technology. The majority of existing mPHR apps is limited by at least one of the attributes considered for this study; however, as the mobile market continues to expand it is likely that more comprehensive mPHRs will be developed in the near future. New advancements in mobile technology can be utilized to enhance mPHRs by long-term patient empowerment features. Marketing strategies for mPHRs should target specific subpopulations and avoid scare tactics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Analysis and Prediction of Myristoylation Sites Using the mRMR Method, the IFS Method and an Extreme Learning Machine Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Huang, GuoHua; Chen, Lei; Cai, Yu-Dong

2017-01-01

Myristoylation is an important hydrophobic post-translational modification that is covalently bound to the amino group of Gly residues on the N-terminus of proteins. The many diverse functions of myristoylation on proteins, such as membrane targeting, signal pathway regulation and apoptosis, are largely due to the lipid modification, whereas abnormal or irregular myristoylation on proteins can lead to several pathological changes in the cell. To better understand the function of myristoylated sites and to correctly identify them in protein sequences, this study conducted a novel computational investigation on identifying myristoylation sites in protein sequences. A training dataset with 196 positive and 84 negative peptide segments were obtained. Four types of features derived from the peptide segments following the myristoylation sites were used to specify myristoylatedand non-myristoylated sites. Then, feature selection methods including maximum relevance and minimum redundancy (mRMR), incremental feature selection (IFS), and a machine learning algorithm (extreme learning machine method) were adopted to extract optimal features for the algorithm to identify myristoylation sites in protein sequences, thereby building an optimal prediction model. As a result, 41 key features were extracted and used to build an optimal prediction model. The effectiveness of the optimal prediction model was further validated by its performance on a test dataset. Furthermore, detailed analyses were also performed on the extracted 41 features to gain insight into the mechanism of myristoylation modification. This study provided a new computational method for identifying myristoylation sites in protein sequences. We believe that it can be a useful tool to predict myristoylation sites from protein sequences. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

PubMed Central

Roy, Sushmita; Martinez, Diego; Platero, Harriett; Lane, Terran; Werner-Washburne, Margaret

2009-01-01

Background Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information. Results AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins. Conclusion AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains. PMID:19936254

Designing lymphocyte functional structure for optimal signal detection: voilà, T cells.

PubMed

Noest, A J

2000-11-21

One basic task of immune systems is to detect signals from unknown "intruders" amidst a noisy background of harmless signals. To clarify the functional importance of many observed lymphocyte properties, I ask: What properties would a cell have if one designed it according to the theory of optimal detection, with minimal regard for biological constraints? Sparse and reasonable assumptions about the statistics of available signals prove sufficient for deriving many features of the optimal functional structure, in an incremental and modular design. The use of one common formalism guarantees that all parts of the design collaborate to solve the detection task. Detection performance is computed at several stages of the design. Comparison between design variants reveals e.g. the importance of controlling the signal integration time. This predicts that an appropriate control mechanism should exist. Comparing the design to reality, I find a striking similarity with many features of T cells. For example, the formalism dictates clonal specificity, serial receptor triggering, (grades of) anergy, negative and positive selection, co-stimulation, high-zone tolerance, and clonal production of cytokines. Serious mismatches should be found if T cells were hindered by mechanistic constraints or vestiges of their (co-)evolutionary history, but I have not found clear examples. By contrast, fundamental mismatches abound when comparing the design to immune systems of e.g. invertebrates. The wide-ranging differences seem to hinge on the (in)ability to generate a large diversity of receptors. Copyright 2000 Academic Press.

Conceptualizing neurodevelopmental disorders through a mechanistic understanding of fragile X syndrome and Williams syndrome

PubMed Central

Fung, Lawrence K.; Quintin, Eve-Marie; Haas, Brian W.

2013-01-01

Purpose of review The overarching goal of this review is to compare and contrast the cognitive-behavioral features of fragile X syndrome (FraX) and Williams syndrome and to review the putative neural and molecular underpinnings of these features. Information is presented in a framework that provides guiding principles for conceptualizing gene-brain-behavior associations in neurodevelopmental disorders. Recent findings Abnormalities, in particular cognitive-behavioral domains with similarities in underlying neurodevelopmental correlates, occur in both FraX and Williams syndrome including aberrant frontostriatal pathways leading to executive function deficits, and magnocellular/dorsal visual stream, superior parietal lobe, inferior parietal lobe, and postcentral gyrus abnormalities contributing to deficits in visuospatial function. Compelling cognitive–behavioral and neurodevelopmental contrasts also exist in these two disorders, for example, aberrant amygdala and fusiform cortex structure and function occurring in the context of contrasting social behavioral phenotypes, and temporal cortical and cerebellar abnormalities potentially underlying differences in language function. Abnormal dendritic development is a shared neurodevelopmental morphologic feature between FraX and Williams syndrome. Commonalities in molecular machinery and processes across FraX and Williams syndrome occur as well – microRNAs involved in translational regulation of major synaptic proteins; scaffolding proteins in excitatory synapses; and proteins involved in axonal development. Summary Although the genetic variations leading to FraX and Williams syndrome are different, important similarities and contrasts in the phenotype, neurocircuitry, molecular machinery, and cellular processes in these two disorders allow for a unique approach to conceptualizing gene–brain–behavior links occurring in neurodevelopmental disorders. PMID:22395002

Structure and Function in Homodimeric Enzymes: Simulations of Cooperative and Independent Functional Motions.

PubMed

Wells, Stephen A; van der Kamp, Marc W; McGeagh, John D; Mulholland, Adrian J

2015-01-01

Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes.

Structure and Function in Homodimeric Enzymes: Simulations of Cooperative and Independent Functional Motions

PubMed Central

McGeagh, John D.; Mulholland, Adrian J.

2015-01-01

Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes. PMID:26241964

The domain organization of the bacterial intermediate filament-like protein crescentin is important for assembly and function

PubMed Central

Cabeen, Matthew T; Herrmann, Harald; Jacobs-Wagner, Christine

2011-01-01

Crescentin is a bacterial filament-forming protein that exhibits domain organization features found in metazoan intermediate filament (IF) proteins. Structure-function studies of eukaryotic IFs have been hindered by a lack of simple genetic systems and easily quantifiable phenotypes. Here we exploit the characteristic localization of the crescentin structure along the inner curvature of Caulobacter crescentus cells and the loss of cell curvature associated with impaired crescentin function to analyze the importance of the domain organization of crescentin. By combining biochemistry and ultrastructural analysis in vitro with cellular localization and functional studies, we show that crescentin requires its distinctive domain organization, and furthermore that different structural elements have distinct structural and functional contributions. The head domain can be functionally subdivided into two subdomains; the first (amino-terminal) is required for function but not assembly, while the second is necessary for structure assembly. The rod domain is similarly required for structure assembly, and the linker L1 appears important to prevent runaway assembly into nonfunctional aggregates. The data also suggest that the stutter and the tail domain have critical functional roles in stabilizing crescentin structures against disassembly by monovalent cations in the cytoplasm. This study suggests that the IF-like behavior of crescentin is a consequence of its domain organization, implying that the IF protein layout is an adaptable cytoskeletal motif, much like the actin and tubulin folds, that is broadly exploited for various functions throughout life from bacteria to humans. © 2011 Wiley-Liss, Inc. PMID:21360832

Do understorey or overstorey traits drive tree encroachment on a drained raised bog?

PubMed

Jagodziński, A M; Horodecki, P; Rawlik, K; Dyderski, M K

2017-07-01

One of the most important threats to peatland ecosystems is drainage, resulting in encroachment of woody species. Our main aim was to check which features - overstorey or understorey vegetation - are more important for shaping the seedling bank of pioneer trees colonising peatlands (Pinus sylvestris and Betula pubescens). We hypothesised that tree stand parameters will be more important predictors of natural regeneration density than understorey vegetation parameters, and the former will be negatively correlated with species diversity and richness and also with functional richness and functional dispersion, which indicate a high level of habitat filtering. The study was conducted in the 'Zielone Bagna' nature reserve (NW Poland). We assessed the structure of tree stands and natural regeneration (of B. pubescens and P. sylvestris) and vegetation species composition. Random forest and DCA were applied to assess relationships between variables studied. Understorey vegetation traits affected tree seedling density (up to 0.5-m height) more than tree stand traits. Density of older seedlings depended more on tree stand traits. We did not find statistically significant relationships between natural regeneration densities and functional diversity components, except for functional richness, which was positively correlated with density of the youngest tree seedlings. Seedling densities were higher in plots with lower functional dispersion and functional divergence, which indicated that habitat filtering is more important than competition. Presence of an abundant seedling bank is crucial for the process of woody species encroachment on drained peatlands, thus its dynamics should be monitored in protected areas. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.

A rhythm-based authentication scheme for smart media devices.

PubMed

Lee, Jae Dong; Jeong, Young-Sik; Park, Jong Hyuk

2014-01-01

In recent years, ubiquitous computing has been rapidly emerged in our lives and extensive studies have been conducted in a variety of areas related to smart devices, such as tablets, smartphones, smart TVs, smart refrigerators, and smart media devices, as a measure for realizing the ubiquitous computing. In particular, smartphones have significantly evolved from the traditional feature phones. Increasingly higher-end smartphone models that can perform a range of functions are now available. Smart devices have become widely popular since they provide high efficiency and great convenience for not only private daily activities but also business endeavors. Rapid advancements have been achieved in smart device technologies to improve the end users' convenience. Consequently, many people increasingly rely on smart devices to store their valuable and important data. With this increasing dependence, an important aspect that must be addressed is security issues. Leaking of private information or sensitive business data due to loss or theft of smart devices could result in exorbitant damage. To mitigate these security threats, basic embedded locking features are provided in smart devices. However, these locking features are vulnerable. In this paper, an original security-locking scheme using a rhythm-based locking system (RLS) is proposed to overcome the existing security problems of smart devices. RLS is a user-authenticated system that addresses vulnerability issues in the existing locking features and provides secure confidentiality in addition to convenience.

A Rhythm-Based Authentication Scheme for Smart Media Devices

PubMed Central

Lee, Jae Dong; Park, Jong Hyuk

2014-01-01

In recent years, ubiquitous computing has been rapidly emerged in our lives and extensive studies have been conducted in a variety of areas related to smart devices, such as tablets, smartphones, smart TVs, smart refrigerators, and smart media devices, as a measure for realizing the ubiquitous computing. In particular, smartphones have significantly evolved from the traditional feature phones. Increasingly higher-end smartphone models that can perform a range of functions are now available. Smart devices have become widely popular since they provide high efficiency and great convenience for not only private daily activities but also business endeavors. Rapid advancements have been achieved in smart device technologies to improve the end users' convenience. Consequently, many people increasingly rely on smart devices to store their valuable and important data. With this increasing dependence, an important aspect that must be addressed is security issues. Leaking of private information or sensitive business data due to loss or theft of smart devices could result in exorbitant damage. To mitigate these security threats, basic embedded locking features are provided in smart devices. However, these locking features are vulnerable. In this paper, an original security-locking scheme using a rhythm-based locking system (RLS) is proposed to overcome the existing security problems of smart devices. RLS is a user-authenticated system that addresses vulnerability issues in the existing locking features and provides secure confidentiality in addition to convenience. PMID:25110743

Content and Methodological Formation Model of a Younger Pupil Value-Oriented Attitude to Reality Based on Historical and Social Science Knowledge

ERIC Educational Resources Information Center

Zakirova, Ranija R.; Shamigulova, Oksana ?.

2016-01-01

One of the most important functions of historical and pedagogical education in modern educational the system is connected with a pupil's character features development, a value apprehension of social events and a formation of a value-oriented attitude to reality. The main aim of the present article is to describe and analyze the results of a…

Recent Advances in Conotoxin Classification by Using Machine Learning Methods.

PubMed

Dao, Fu-Ying; Yang, Hui; Su, Zhen-Dong; Yang, Wuritu; Wu, Yun; Hui, Ding; Chen, Wei; Tang, Hua; Lin, Hao

2017-06-25

Conotoxins are disulfide-rich small peptides, which are invaluable peptides that target ion channel and neuronal receptors. Conotoxins have been demonstrated as potent pharmaceuticals in the treatment of a series of diseases, such as Alzheimer's disease, Parkinson's disease, and epilepsy. In addition, conotoxins are also ideal molecular templates for the development of new drug lead compounds and play important roles in neurobiological research as well. Thus, the accurate identification of conotoxin types will provide key clues for the biological research and clinical medicine. Generally, conotoxin types are confirmed when their sequence, structure, and function are experimentally validated. However, it is time-consuming and costly to acquire the structure and function information by using biochemical experiments. Therefore, it is important to develop computational tools for efficiently and effectively recognizing conotoxin types based on sequence information. In this work, we reviewed the current progress in computational identification of conotoxins in the following aspects: (i) construction of benchmark dataset; (ii) strategies for extracting sequence features; (iii) feature selection techniques; (iv) machine learning methods for classifying conotoxins; (v) the results obtained by these methods and the published tools; and (vi) future perspectives on conotoxin classification. The paper provides the basis for in-depth study of conotoxins and drug therapy research.

Geometric characterization and simulation of planar layered elastomeric fibrous biomaterials

PubMed Central

Carleton, James B.; D'Amore, Antonio; Feaver, Kristen R.; Rodin, Gregory J.; Sacks, Michael S.

2014-01-01

Many important biomaterials are composed of multiple layers of networked fibers. While there is a growing interest in modeling and simulation of the mechanical response of these biomaterials, a theoretical foundation for such simulations has yet to be firmly established. Moreover, correctly identifying and matching key geometric features is a critically important first step for performing reliable mechanical simulations. The present work addresses these issues in two ways. First, using methods of geometric probability we develop theoretical estimates for the mean linear and areal fiber intersection densities for two-dimensional fibrous networks. These densities are expressed in terms of the fiber density and the orientation distribution function, both of which are relatively easy-to-measure properties. Secondly, we develop a random walk algorithm for geometric simulation of two-dimensional fibrous networks which can accurately reproduce the prescribed fiber density and orientation distribution function. Furthermore, the linear and areal fiber intersection densities obtained with the algorithm are in agreement with the theoretical estimates. Both theoretical and computational results are compared with those obtained by post-processing of SEM images of actual scaffolds. These comparisons reveal difficulties inherent to resolving fine details of multilayered fibrous networks. The methods provided herein can provide a rational means to define and generate key geometric features from experimentally measured or prescribed scaffold structural data. PMID:25311685

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

PubMed Central

Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

2018-01-01

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function. PMID:29320526

ClearTK 2.0: Design Patterns for Machine Learning in UIMA

PubMed Central

Bethard, Steven; Ogren, Philip; Becker, Lee

2014-01-01

ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework. PMID:29104966

ClearTK 2.0: Design Patterns for Machine Learning in UIMA.

PubMed

Bethard, Steven; Ogren, Philip; Becker, Lee

2014-05-01

ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework.

[Polycystic ovary syndrome: an example of obesity-related cardiovascular complication affecting young women].

PubMed

Orio, Francesco; Cascella, Teresa; Giallauria, Francesco; Palomba, Stefano; De Lorenzo, Anna; Lucci, Rosa; Ambrosino, Elena; Lombardi, Gaetano; Colao, Annamaria; Vigorito, Carlo

2006-03-01

Polycystic ovary syndrome (PCOS) is a good example of obesity-related cardiovascular complication affecting young women. PCOS is not only considered a reproductive problem but rather represents a complex endocrine, multifaceted syndrome with important health implications. Several evidences suggest an increased cardiovascular risk of cardiovascular disease associated with this syndrome, characterized by an impairment of heart structure and function, endothelial dysfunction and lipid abnormalities. All these features, probably linked to insulin-resistance, are often present in obese PCOS patients. Cardiovascular abnormalities represent important long-term sequelae of PCOS that need further investigations.

Salient features of the ciliated organ of asymmetry

PubMed Central

Amack, Jeffrey D.

2014-01-01

Many internal organs develop distinct left and right sides that are essential for their functions. In several vertebrate embryos, motile cilia generate an asymmetric fluid flow that plays an important role in establishing left-right (LR) signaling cascades. These ‘LR cilia’ are found in the ventral node and posterior notochordal plate in mammals, the gastrocoel roof plate in amphibians and Kupffer’s vesicle in teleost fish. I consider these transient ciliated structures as the ‘organ of asymmetry’ that directs LR patterning of the developing embryo. Variations in size and morphology of the organ of asymmetry in different vertebrate species have raised questions regarding the fundamental features that are required for LR determination. Here, I review current models for how LR asymmetry is established in vertebrates, discuss the cellular architecture of the ciliated organ of asymmetry and then propose key features of this organ that are critical for orienting the LR body axis. PMID:24481178

Eyes Matched to the Prize: The State of Matched Filters in Insect Visual Circuits.

PubMed

Kohn, Jessica R; Heath, Sarah L; Behnia, Rudy

2018-01-01

Confronted with an ever-changing visual landscape, animals must be able to detect relevant stimuli and translate this information into behavioral output. A visual scene contains an abundance of information: to interpret the entirety of it would be uneconomical. To optimally perform this task, neural mechanisms exist to enhance the detection of important features of the sensory environment while simultaneously filtering out irrelevant information. This can be accomplished by using a circuit design that implements specific "matched filters" that are tuned to relevant stimuli. Following this rule, the well-characterized visual systems of insects have evolved to streamline feature extraction on both a structural and functional level. Here, we review examples of specialized visual microcircuits for vital behaviors across insect species, including feature detection, escape, and estimation of self-motion. Additionally, we discuss how these microcircuits are modulated to weigh relevant input with respect to different internal and behavioral states.

Identification of a motor to auditory pathway important for vocal learning

PubMed Central

Roberts, Todd F.; Hisey, Erin; Tanaka, Masashi; Kearney, Matthew; Chattree, Gaurav; Yang, Cindy F.; Shah, Nirao M.; Mooney, Richard

2017-01-01

Summary Learning to vocalize depends on the ability to adaptively modify the temporal and spectral features of vocal elements. Neurons that convey motor-related signals to the auditory system are theorized to facilitate vocal learning, but the identity and function of such neurons remain unknown. Here we identify a previously unknown neuron type in the songbird brain that transmits vocal motor signals to the auditory cortex. Genetically ablating these neurons in juveniles disrupted their ability to imitate features of an adult tutor’s song. Ablating these neurons in adults had little effect on previously learned songs, but interfered with their ability to adaptively modify the duration of vocal elements and largely prevented the degradation of song’s temporal features normally caused by deafening. These findings identify a motor to auditory circuit essential to vocal imitation and to the adaptive modification of vocal timing. PMID:28504672

A Cross-Sectional Investigation of the Importance of Park Features for Promoting Regular Physical Activity in Parks.

PubMed

Costigan, Sarah A; Veitch, Jenny; Crawford, David; Carver, Alison; Timperio, Anna

2017-11-02

Parks in the US and Australia are generally underutilised, and park visitors typically engage in low levels of physical activity (PA). Better understanding park features that may encourage visitors to be active is important. This study examined the perceived importance of park features for encouraging park-based PA and examined differences by sex, age, parental-status and participation in PA. Cross-sectional surveys were completed by local residents ( n = 2775) living near two parks (2013/2015). Demographic variables, park visitation and leisure-time PA were self-reported, respondents rated the importance of 20 park features for encouraging park-based PA in the next fortnight. Chi-square tests of independence examined differences in importance of park features for PA among sub-groups of local residents (sex, age, parental-status, PA). Park features ranked most important for park-based PA were: well maintained (96.2%), feel safe (95.4%), relaxing atmosphere (91.2%), easy to get to (91.7%), and shady trees (90.3%). All subgroups ranked 'well maintained' as most important. Natural and built environment features of parks are important for promoting adults' park-based PA, and should be considered in park (re)design.

The functions of immediate echolalia in autistic children.

PubMed

Prizant, B M; Duchan, J F

1981-08-01

This research was intended to discover how immediate echolalia functioned for autistic children in interactions with familial adults. For echolalic children were videotaped at school and at home, in both group and dyadic interactions in natural situations such as lunchtime, family activities, and play activities in school. After conducting a multilevel analysis (of over 1,000 utterances) of verbal and nonverbal factors, response latency, and intonation, it was discovered that immediate echolalia is far more than a meaningless behavior, as has been previously reported. Seven functional categories of echolalia were discovered and are discussed in reference to behavioral and linguistic features of each category. It is argue that researchers who propose intervention programs of ech-abatement may be overlooking the important communicative and cognitive functions echolalia may serve for the autistic child.

Segregated Systems of Human Brain Networks.

PubMed

Wig, Gagan S

2017-12-01

The organization of the brain network enables its function. Evaluation of this organization has revealed that large-scale brain networks consist of multiple segregated subnetworks of interacting brain areas. Descriptions of resting-state network architecture have provided clues for understanding the functional significance of these segregated subnetworks, many of which correspond to distinct brain systems. The present report synthesizes accumulating evidence to reveal how maintaining segregated brain systems renders the human brain network functionally specialized, adaptable to task demands, and largely resilient following focal brain damage. The organizational properties that support system segregation are harmonious with the properties that promote integration across the network, but confer unique and important features to the brain network that are central to its function and behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

A method for measuring quality of life through subjective weighting of functional status.

PubMed

Stineman, Margaret G; Wechsler, Barbara; Ross, Richard; Maislin, Greg

2003-04-01

To apply a new tool to understand the quality of life (QOL) implications of patients' functional status. Results from the Features-Resource Trade-Off Game were used to form utility weights by ranking functional activities by the relative value of achieving independence in each activity compared with all other component activities. The utility weights were combined with patients' actual levels of performance across the same activities to produce QOL-weighted functional status scores and to form "value rulers" to order activities by perceived importance. Persons with severe disabilities living in the community and clinicians practicing in various rehabilitation disciplines. Two panels of 5 consumers with disabilities and 2 panels of 5 rehabilitation clinicians. The 4 panels played the Features Resource Trade-Off Game by using the FIMT(TM) instrument definitions. Utility weights for each of the 18 FIM items, QOL-weighted FIM scores, and value rulers. All 4 panels valued the achievement of independence in cognitive and communication activities more than independence in physical activities. Consequently, the unweighted FIM scores of patients who have severe physical disabilities but relatively intact cognitive skills will underestimate QOL, while inflating QOL in those with low levels of independence in cognition and communication but higher physical function. Independence in some activities is more valued than in others; thus, 2 people with the same numeric functional status score could experience very different QOL. QOL-weighted functional status scores translate objectively measured functional status into its subjective meaning. This new technology for measuring subjective function-related QOL has a variety of applications to clinical, educational, and research practices.

Accurate in silico prediction of species-specific methylation sites based on information gain feature optimization.

PubMed

Wen, Ping-Ping; Shi, Shao-Ping; Xu, Hao-Dong; Wang, Li-Na; Qiu, Jian-Ding

2016-10-15

As one of the most important reversible types of post-translational modification, protein methylation catalyzed by methyltransferases carries many pivotal biological functions as well as many essential biological processes. Identification of methylation sites is prerequisite for decoding methylation regulatory networks in living cells and understanding their physiological roles. Experimental methods are limitations of labor-intensive and time-consuming. While in silicon approaches are cost-effective and high-throughput manner to predict potential methylation sites, but those previous predictors only have a mixed model and their prediction performances are not fully satisfactory now. Recently, with increasing availability of quantitative methylation datasets in diverse species (especially in eukaryotes), there is a growing need to develop a species-specific predictor. Here, we designed a tool named PSSMe based on information gain (IG) feature optimization method for species-specific methylation site prediction. The IG method was adopted to analyze the importance and contribution of each feature, then select the valuable dimension feature vectors to reconstitute a new orderly feature, which was applied to build the finally prediction model. Finally, our method improves prediction performance of accuracy about 15% comparing with single features. Furthermore, our species-specific model significantly improves the predictive performance compare with other general methylation prediction tools. Hence, our prediction results serve as useful resources to elucidate the mechanism of arginine or lysine methylation and facilitate hypothesis-driven experimental design and validation. The tool online service is implemented by C# language and freely available at http://bioinfo.ncu.edu.cn/PSSMe.aspx CONTACT: jdqiu@ncu.edu.cnSupplementary information: 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.

The LAILAPS search engine: a feature model for relevance ranking in life science databases.

PubMed

Lange, Matthias; Spies, Karl; Colmsee, Christian; Flemming, Steffen; Klapperstück, Matthias; Scholz, Uwe

2010-03-25

Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

Hierarchical semantic cognition for urban functional zones with VHR satellite images and POI data

NASA Astrophysics Data System (ADS)

Zhang, Xiuyuan; Du, Shihong; Wang, Qiao

2017-10-01

As the basic units of urban areas, functional zones are essential for city planning and management, but functional-zone maps are hardly available in most cities, as traditional urban investigations focus mainly on land-cover objects instead of functional zones. As a result, an automatic/semi-automatic method for mapping urban functional zones is highly required. Hierarchical semantic cognition (HSC) is presented in this study, and serves as a general cognition structure for recognizing urban functional zones. Unlike traditional classification methods, the HSC relies on geographic cognition and considers four semantic layers, i.e., visual features, object categories, spatial object patterns, and zone functions, as well as their hierarchical relations. Here, we used HSC to classify functional zones in Beijing with a very-high-resolution (VHR) satellite image and point-of-interest (POI) data. Experimental results indicate that this method can produce more accurate results than Support Vector Machine (SVM) and Latent Dirichlet Allocation (LDA) with a larger overall accuracy of 90.8%. Additionally, the contributions of diverse semantic layers are quantified: the object-category layer is the most important and makes 54% contribution to functional-zone classification; while, other semantic layers are less important but their contributions cannot be ignored. Consequently, the presented HSC is effective in classifying urban functional zones, and can further support urban planning and management.

Decreased functional connectivity in an executive control network is related to impaired executive function in Internet gaming disorder.

PubMed

Dong, Guangheng; Lin, Xiao; Potenza, Marc N

2015-03-03

Resting brain spontaneous neural activities across cortical regions have been correlated with specific functional properties in psychiatric groups. Individuals with Internet gaming disorder (IGD) demonstrate impaired executive control. Thus, it is important to examine executive control networks (ECNs) during resting states and their relationships to executive control during task performance. Thirty-five IGD and 36 healthy control participants underwent a resting-state fMRI scan and performed a Stroop task inside and outside of the MRI scanner. Correlations between Stroop effect and functional connectivity among ECN regions of interest (ROIs) were calculated within and between groups. IGD subjects show lower functional connectivity in ECNs than do HC participants during resting state; functional-connectivity measures in ECNs were negatively correlated with Stroop effect and positively correlated with brain activations in executive-control regions across groups. Within groups, negative trends were found between Stroop effect and functional connectivity in ECNs in IGD and HC groups, separately; positive trends were found between functional connectivity in ECNs and brain activations in Stroop task in IGD and HC groups, separately. Higher functional connectivity in ECNs may underlie better executive control and may provide resilience with respect to IGD. Lower functional connectivity in ECNs may represent an important feature in understanding and treating IGD. Copyright © 2013 Elsevier Inc. All rights reserved.

Pancreatic cancer cell lines as patient-derived avatars: genetic characterisation and functional utility.

PubMed

Knudsen, Erik S; Balaji, Uthra; Mannakee, Brian; Vail, Paris; Eslinger, Cody; Moxom, Christopher; Mansour, John; Witkiewicz, Agnieszka K

2018-03-01

Pancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities. 27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC. The cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC. These data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Kinematic Features of Jaw and Lips Distinguish Symptomatic From Presymptomatic Stages of Bulbar Decline in Amyotrophic Lateral Sclerosis.

PubMed

Bandini, Andrea; Green, Jordan R; Wang, Jun; Campbell, Thomas F; Zinman, Lorne; Yunusova, Yana

2018-05-17

The goals of this study were to (a) classify speech movements of patients with amyotrophic lateral sclerosis (ALS) in presymptomatic and symptomatic phases of bulbar function decline relying solely on kinematic features of lips and jaw and (b) identify the most important measures that detect the transition between early and late bulbar changes. One hundred ninety-two recordings obtained from 64 patients with ALS were considered for the analysis. Feature selection and classification algorithms were used to analyze lip and jaw movements recorded with Optotrak Certus (Northern Digital Inc.) during a sentence task. A feature set, which included 35 measures of movement range, velocity, acceleration, jerk, and area measures of lips and jaw, was used to classify sessions according to the speaking rate into presymptomatic (> 160 words per minute) and symptomatic (< 160 words per minute) groups. Presymptomatic and symptomatic phases of bulbar decline were distinguished with high accuracy (87%), relying only on lip and jaw movements. The best features that allowed detecting the differences between early and later bulbar stages included cumulative path of lower lip and jaw, peak values of velocity, acceleration, and jerk of lower lip and jaw. The results established a relationship between facial kinematics and bulbar function decline in ALS. Considering that facial movements can be recorded by means of novel inexpensive and easy-to-use, video-based methods, this work supports the development of an automatic system for facial movement analysis to help clinicians in tracking the disease progression in ALS.

Biogenesis and functions of lipid droplets in plants: Thematic Review Series: Lipid Droplet Synthesis and Metabolism: from Yeast to Man.

PubMed

Chapman, Kent D; Dyer, John M; Mullen, Robert T

2012-02-01

The compartmentation of neutral lipids in plants is mostly associated with seed tissues, where triacylglycerols (TAGs) stored within lipid droplets (LDs) serve as an essential physiological energy and carbon reserve during postgerminative growth. However, some nonseed tissues, such as leaves, flowers and fruits, also synthesize and store TAGs, yet relatively little is known about the formation or function of LDs in these tissues. Characterization of LD-associated proteins, such as oleosins, caleosins, and sterol dehydrogenases (steroleosins), has revealed surprising features of LD function in plants, including stress responses, hormone signaling pathways, and various aspects of plant growth and development. Although oleosin and caleosin proteins are specific to plants, LD-associated sterol dehydrogenases also are present in mammals, and in both plants and mammals these enzymes have been shown to be important in (steroid) hormone metabolism and signaling. In addition, several other proteins known to be important in LD biogenesis in yeasts and mammals are conserved in plants, suggesting that at least some aspects of LD biogenesis and/or function are evolutionarily conserved.

Advanced magnetic resonance imaging of neurodegenerative diseases.

PubMed

Agosta, Federica; Galantucci, Sebastiano; Filippi, Massimo

2017-01-01

Magnetic resonance imaging (MRI) is playing an increasingly important role in the study of neurodegenerative diseases, delineating the structural and functional alterations determined by these conditions. Advanced MRI techniques are of special interest for their potential to characterize the signature of each neurodegenerative condition and aid both the diagnostic process and the monitoring of disease progression. This aspect will become crucial when disease-modifying (personalized) therapies will be established. MRI techniques are very diverse and go from the visual inspection of MRI scans to more complex approaches, such as manual and automatic volume measurements, diffusion tensor MRI, and functional MRI. All these techniques allow us to investigate the different features of neurodegeneration. In this review, we summarize the most recent advances concerning the use of MRI in some of the most important neurodegenerative conditions, putting an emphasis on the advanced techniques.

Modifications at the A-domain of the chloroplast import receptor Toc159.

PubMed

Agne, Birgit; Kessler, Felix

2010-11-01

Two families of GTPases, the Toc34 and Toc159 GTPase families, take on the task of preprotein recognition at the translocon at the outer membrane of chloroplasts (TOC translocon). The major Toc159 family members have highly acidic N-terminal domains (A-domains) that are non-essential and so far have escaped functional characterization. But recently, interest in the role of the A-domain has strongly increased. The new data of three independent studies provide evidence that the Toc159 A-domain I) participates in preprotein selectivity, II) has typical features of intrinsically unfolded proteins and III) is highly phosphorylated and possibly released from the rest of the protein by a proteolytic event. This hints to a complex regulation of A-domain function that is important for the maintenance of the preprotein selectivity at the TOC translocons.

n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation

PubMed Central

Palma Orozco, Rosaura

2018-01-01

Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe the signal behavior. Thus, great importance should be taken to feature extraction which is complicated for the Parameter Estimation (PE)–System Identification (SI) process. When based on an average approximation, nonstationary characteristics are presented. For PE the comparison of three forms of iterative-recursive uses of the Exponential Forgetting Factor (EFF) combined with a linear function to identify a synthetic stochastic signal is presented. The one with best results seen through the functional error is applied to approximate an EEG signal for a simple classification example, showing the effectiveness of our proposal. PMID:29568310

What vehicle features are considered important when buying an automobile? An examination of driver preferences by age and gender.

PubMed

Vrkljan, Brenda H; Anaby, Dana

2011-02-01

Certain vehicle features can help drivers avoid collisions and/or protect occupants in the event of a crash, and therefore, might play an important role when deciding which vehicle to purchase. The objective of this study was to examine the importance attributed to key vehicle features (including safety) that drivers consider when buying a car and its association with age and gender. A sample of 2,002 Canadian drivers aged 18 years and older completed a survey that asked them to rank the importance of eight vehicle features if they were to purchase a vehicle (storage, mileage, safety, price, comfort, performance, design, and reliability). ANOVA tests were performed to: (a) determine if there were differences in the level of importance between features and; (b) examine the effect of age and gender on the importance attributed to these features. Of the features examined, safety and reliability were the most highly rated in terms of importance, whereas design and performance had the lowest rating. Differences in safety and performance across age groups were dependent on gender. This effect was most evident in the youngest and oldest age groups. Safety and reliability were considered the most important features. Age and gender play a significant role in explaining the importance of certain features. Targeted efforts for translating safety-related information to the youngest and oldest consumers should be emphasized due to their high collision, injury, and fatality rates. Copyright © 2011 National Safety Council and Elsevier Ltd. All rights reserved.

Atomic force microscopy study of the structure function relationships of the biofilm-forming bacterium Streptococcus mutans

NASA Astrophysics Data System (ADS)

Cross, Sarah E.; Kreth, Jens; Zhu, Lin; Qi, Fengxia; Pelling, Andrew E.; Shi, Wenyuan; Gimzewski, James K.

2006-02-01

Atomic force microscopy (AFM) has garnered much interest in recent years for its ability to probe the structure, function and cellular nanomechanics inherent to specific biological cells. In particular, we have used AFM to probe the important structure-function relationships of the bacterium Streptococcus mutans. S. mutans is the primary aetiological agent in human dental caries (tooth decay), and is of medical importance due to the virulence properties of these cells in biofilm initiation and formation, leading to increased tolerance to antibiotics. We have used AFM to characterize the unique surface structures of distinct mutants of S. mutans. These mutations are located in specific genes that encode surface proteins, thus using AFM we have resolved characteristic surface features for mutant strains compared to the wild type. Ultimately, our characterization of surface morphology has shown distinct differences in the local properties displayed by various S. mutans strains on the nanoscale, which is imperative for understanding the collective properties of these cells in biofilm formation.

NDST1 missense mutations in autosomal recessive intellectual disability.

PubMed

Reuter, Miriam S; Musante, Luciana; Hu, Hao; Diederich, Stefan; Sticht, Heinrich; Ekici, Arif B; Uebe, Steffen; Wienker, Thomas F; Bartsch, Oliver; Zechner, Ulrich; Oppitz, Cornelia; Keleman, Krystyna; Jamra, Rami Abou; Najmabadi, Hossein; Schweiger, Susann; Reis, André; Kahrizi, Kimia

2014-11-01

NDST1 was recently proposed as a candidate gene for autosomal recessive intellectual disability in two families. It encodes a bifunctional GlcNAc N-deacetylase/N-sulfotransferase with important functions in heparan sulfate biosynthesis. In mice, Ndst1 is crucial for embryonic development and homozygous null mutations are perinatally lethal. We now report on two additional unrelated families with homozygous missense NDST1 mutations. All mutations described to date predict the substitution of conserved amino acids in the sulfotransferase domain, and mutation modeling predicts drastic alterations in the local protein conformation. Comparing the four families, we noticed significant overlap in the clinical features, including both demonstrated and apparent intellectual disability, muscular hypotonia, epilepsy, and postnatal growth deficiency. Furthermore, in Drosophila, knockdown of sulfateless, the NDST ortholog, impairs long-term memory, highlighting its function in cognition. Our data confirm NDST1 mutations as a cause of autosomal recessive intellectual disability with a distinctive phenotype, and support an important function of NDST1 in human development. © 2014 Wiley Periodicals, Inc.

Global study of holistic morphological effectors in the budding yeast Saccharomyces cerevisiae.

PubMed

Suzuki, Godai; Wang, Yang; Kubo, Karen; Hirata, Eri; Ohnuki, Shinsuke; Ohya, Yoshikazu

2018-02-20

The size of the phenotypic effect of a gene has been thoroughly investigated in terms of fitness and specific morphological traits in the budding yeast Saccharomyces cerevisiae, but little is known about gross morphological abnormalities. We identified 1126 holistic morphological effectors that cause severe gross morphological abnormality when deleted, and 2241 specific morphological effectors with weak holistic effects but distinctive effects on yeast morphology. Holistic effectors fell into many gene function categories and acted as network hubs, affecting a large number of morphological traits, interacting with a large number of genes, and facilitating high protein expression. Holistic morphological abnormality was useful for estimating the importance of a gene to morphology. The contribution of gene importance to fitness and morphology could be used to efficiently classify genes into functional groups. Holistic morphological abnormality can be used as a reproducible and reliable gene feature for high-dimensional morphological phenotyping. It can be used in many functional genomic applications.

Genetic resources offer efficient tools for rice functional genomics research.

PubMed

Lo, Shuen-Fang; Fan, Ming-Jen; Hsing, Yue-Ie; Chen, Liang-Jwu; Chen, Shu; Wen, Ien-Chie; Liu, Yi-Lun; Chen, Ku-Ting; Jiang, Mirng-Jier; Lin, Ming-Kuang; Rao, Meng-Yen; Yu, Lin-Chih; Ho, Tuan-Hua David; Yu, Su-May

2016-05-01

Rice is an important crop and major model plant for monocot functional genomics studies. With the establishment of various genetic resources for rice genomics, the next challenge is to systematically assign functions to predicted genes in the rice genome. Compared with the robustness of genome sequencing and bioinformatics techniques, progress in understanding the function of rice genes has lagged, hampering the utilization of rice genes for cereal crop improvement. The use of transfer DNA (T-DNA) insertional mutagenesis offers the advantage of uniform distribution throughout the rice genome, but preferentially in gene-rich regions, resulting in direct gene knockout or activation of genes within 20-30 kb up- and downstream of the T-DNA insertion site and high gene tagging efficiency. Here, we summarize the recent progress in functional genomics using the T-DNA-tagged rice mutant population. We also discuss important features of T-DNA activation- and knockout-tagging and promoter-trapping of the rice genome in relation to mutant and candidate gene characterizations and how to more efficiently utilize rice mutant populations and datasets for high-throughput functional genomics and phenomics studies by forward and reverse genetics approaches. These studies may facilitate the translation of rice functional genomics research to improvements of rice and other cereal crops. © 2015 John Wiley & Sons Ltd.

A preliminary investigation of sleep quality in functional neurological disorders: Poor sleep appears common, and is associated with functional impairment.

PubMed

Graham, Christopher D; Kyle, Simon D

2017-07-15

Functional neurological disorders (FND) are disabling conditions for which there are few empirically-supported treatments. Disturbed sleep appears to be part of the FND context; however, the clinical importance of sleep disturbance (extent, characteristics and impact) remains largely unknown. We described sleep quality in two samples, and investigated the relationship between sleep and FND-related functional impairment. We included a sample recruited online via patient charities (N=205) and a consecutive clinical sample (N=20). Participants completed validated measures of sleep quality and sleep characteristics (e.g. total sleep time, sleep efficiency), mood, and FND-related functional impairment. Poor sleep was common in both samples (89% in the clinical range), which was characterised by low sleep efficiency (M=65.40%) and low total sleep time (M=6.05h). In regression analysis, sleep quality was negatively associated with FND-related functional impairment, accounting for 16% of the variance and remaining significant after the introduction of mood variables. These preliminary analyses suggest that subjective sleep disturbance (low efficiency, short sleep) is common in FND. Sleep quality was negatively associated with the functional impairment attributed to FND, independent of depression. Therefore, sleep disturbance may be a clinically important feature of FND. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of support vector machine for the separation of mineralised zones in the Takht-e-Gonbad porphyry deposit, SE Iran

NASA Astrophysics Data System (ADS)

Mahvash Mohammadi, Neda; Hezarkhani, Ardeshir

2018-07-01

Classification of mineralised zones is an important factor for the analysis of economic deposits. In this paper, the support vector machine (SVM), a supervised learning algorithm, based on subsurface data is proposed for classification of mineralised zones in the Takht-e-Gonbad porphyry Cu-deposit (SE Iran). The effects of the input features are evaluated via calculating the accuracy rates on the SVM performance. Ultimately, the SVM model, is developed based on input features namely lithology, alteration, mineralisation, the level and, radial basis function (RBF) as a kernel function. Moreover, the optimal amount of parameters λ and C, using n-fold cross-validation method, are calculated at level 0.001 and 0.01 respectively. The accuracy of this model is 0.931 for classification of mineralised zones in the Takht-e-Gonbad porphyry deposit. The results of the study confirm the efficiency of SVM method for classification the mineralised zones.

First de novo ANK3 nonsense mutation in a boy with intellectual disability, speech impairment and autistic features.

PubMed

Kloth, Katja; Denecke, Jonas; Hempel, Maja; Johannsen, Jessika; Strom, Tim M; Kubisch, Christian; Lessel, Davor

2017-09-01

Ankyrin-G, encoded by ANK3, plays an important role in neurodevelopment and neuronal function. There are multiple isoforms of Ankyrin-G resulting in differential tissue expression and function. Heterozygous missense mutations in ANK3 have been associated with autism spectrum disorder. Further, in three siblings a homozygous frameshift mutation affecting only the longest isoform and a patient with a balanced translocation disrupting all isoforms were documented. The latter four patients were affected by a variable degree of intellectual disability, attention deficit hyperactivity disorder and autism. Here, we report on a boy with speech impairment, intellectual disability, autistic features, macrocephaly, macrosomia, chronic hunger and an altered sleeping pattern. By trio-whole-exome sequencing, we identified the first de novo nonsense mutation affecting all ANK3 transcripts. Thus, our data expand the phenotype of ANK3-associated diseases and suggest an isoform-based, phenotypic continuum between dominant and recessive ANK3-associated pathologies. Copyright © 2017. Published by Elsevier Masson SAS.

Diagnosis of Misalignment in Overhung Rotor using the K-S Statistic and A2 Test

NASA Astrophysics Data System (ADS)

Garikapati, Diwakar; Pacharu, RaviKumar; Munukurthi, Rama Satya Satyanarayana

2018-02-01

Vibration measurement at the bearings of rotating machinery has become a useful technique for diagnosing incipient fault conditions. In particular, vibration measurement can be used to detect unbalance in rotor, bearing failure, gear problems or misalignment between a motor shaft and coupled shaft. This is a particular problem encountered in turbines, ID fans and FD fans used for power generation. For successful fault diagnosis, it is important to adopt motor current signature analysis (MCSA) techniques capable of identifying the faults. It is also useful to develop techniques for inferring information such as the severity of fault. It is proposed that modeling the cumulative distribution function of motor current signals with respect to appropriate theoretical distributions, and quantifying the goodness of fit with the Kolmogorov-Smirnov (KS) statistic and A2 test offers a suitable signal feature for diagnosis. This paper demonstrates the successful comparison of the K-S feature and A2 test for discriminating the misalignment fault from normal function.

Word Durations in Non-Native English

PubMed Central

Baker, Rachel E.; Baese-Berk, Melissa; Bonnasse-Gahot, Laurent; Kim, Midam; Van Engen, Kristin J.; Bradlow, Ann R.

2010-01-01

In this study, we compare the effects of English lexical features on word duration for native and non-native English speakers and for non-native speakers with different L1s and a range of L2 experience. We also examine whether non-native word durations lead to judgments of a stronger foreign accent. We measured word durations in English paragraphs read by 12 American English (AE), 20 Korean, and 20 Chinese speakers. We also had AE listeners rate the `accentedness' of these non-native speakers. AE speech had shorter durations, greater within-speaker word duration variance, greater reduction of function words, and less between-speaker variance than non-native speech. However, both AE and non-native speakers showed sensitivity to lexical predictability by reducing second mentions and high frequency words. Non-native speakers with more native-like word durations, greater within-speaker word duration variance, and greater function word reduction were perceived as less accented. Overall, these findings identify word duration as an important and complex feature of foreign-accented English. PMID:21516172

Automatic classification of sleep stages based on the time-frequency image of EEG signals.

PubMed

Bajaj, Varun; Pachori, Ram Bilas

2013-12-01

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A hybrid filtering method based on a novel empirical mode decomposition for friction signals

NASA Astrophysics Data System (ADS)

Li, Chengwei; Zhan, Liwei

2015-12-01

During a measurement, the measured signal usually contains noise. To remove the noise and preserve the important feature of the signal, we introduce a hybrid filtering method that uses a new intrinsic mode function (NIMF) and a modified Hausdorff distance. The NIMF is defined as the difference between the noisy signal and each intrinsic mode function (IMF), which is obtained by empirical mode decomposition (EMD), ensemble EMD, complementary ensemble EMD, or complete ensemble EMD with adaptive noise (CEEMDAN). The relevant mode selecting is based on the similarity between the first NIMF and the rest of the NIMFs. With this filtering method, the EMD and improved versions are used to filter the simulation and friction signals. The friction signal between an airplane tire and the runaway is recorded during a simulated airplane touchdown and features spikes of various amplitudes and noise. The filtering effectiveness of the four hybrid filtering methods are compared and discussed. The results show that the filtering method based on CEEMDAN outperforms other signal filtering methods.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: The Fractal Dimensions of Complex Networks

NASA Astrophysics Data System (ADS)

Guo, Long; Cai, XU

2009-08-01

It is shown that many real complex networks share distinctive features, such as the small-world effect and the heterogeneous property of connectivity of vertices, which are different from random networks and regular lattices. Although these features capture the important characteristics of complex networks, their applicability depends on the style of networks. To unravel the universal characteristics many complex networks have in common, we study the fractal dimensions of complex networks using the method introduced by Shanker. We find that the average 'density' (ρ(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df, which is defined as the fractal dimension, in some real complex networks. Furthermore, we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices. Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.

Structural Determination of Functional Domains in Early B-cell Factor (EBF) Family of Transcription Factors Reveals Similarities to Rel DNA-binding Proteins and a Novel Dimerization Motif*

PubMed Central

Siponen, Marina I.; Wisniewska, Magdalena; Lehtiö, Lari; Johansson, Ida; Svensson, Linda; Raszewski, Grzegorz; Nilsson, Lennart; Sigvardsson, Mikael; Berglund, Helena

2010-01-01

The early B-cell factor (EBF) transcription factors are central regulators of development in several organs and tissues. This protein family shows low sequence similarity to other protein families, which is why structural information for the functional domains of these proteins is crucial to understand their biochemical features. We have used a modular approach to determine the crystal structures of the structured domains in the EBF family. The DNA binding domain reveals a striking resemblance to the DNA binding domains of the Rel homology superfamily of transcription factors but contains a unique zinc binding structure, termed zinc knuckle. Further the EBF proteins contain an IPT/TIG domain and an atypical helix-loop-helix domain with a novel type of dimerization motif. The data presented here provide insights into unique structural features of the EBF proteins and open possibilities for detailed molecular investigations of this important transcription factor family. PMID:20592035

Structural insights of ZIP4 extracellular domain critical for optimal zinc transport

NASA Astrophysics Data System (ADS)

Zhang, Tuo; Sui, Dexin; Hu, Jian

2016-06-01

The ZIP zinc transporter family is responsible for zinc uptake from the extracellular milieu or intracellular vesicles. The LIV-1 subfamily, containing nine out of the 14 human ZIP proteins, is featured with a large extracellular domain (ECD). The critical role of the ECD is manifested by disease-causing mutations on ZIP4, a representative LIV-1 protein. Here we report the first crystal structure of a mammalian ZIP4-ECD, which reveals two structurally independent subdomains and an unprecedented dimer centred at the signature PAL motif. Structure-guided mutagenesis, cell-based zinc uptake assays and mapping of the disease-causing mutations indicate that the two subdomains play pivotal but distinct roles and that the bridging region connecting them is particularly important for ZIP4 function. These findings lead to working hypotheses on how ZIP4-ECD exerts critical functions in zinc transport. The conserved dimeric architecture in ZIP4-ECD is also demonstrated to be a common structural feature among the LIV-1 proteins.

Evolutionary divergence and functions of the human interleukin (IL) gene family

PubMed Central

2010-01-01

Cytokines play a very important role in nearly all aspects of inflammation and immunity. The term 'interleukin' (IL) has been used to describe a group of cytokines with complex immunomodulatory functions -- including cell proliferation, maturation, migration and adhesion. These cytokines also play an important role in immune cell differentiation and activation. Determining the exact function of a particular cytokine is complicated by the influence of the producing cell type, the responding cell type and the phase of the immune response. ILs can also have pro- and anti-inflammatory effects, further complicating their characterisation. These molecules are under constant pressure to evolve due to continual competition between the host's immune system and infecting organisms; as such, ILs have undergone significant evolution. This has resulted in little amino acid conservation between orthologous proteins, which further complicates the gene family organisation. Within the literature there are a number of overlapping nomenclature and classification systems derived from biological function, receptor-binding properties and originating cell type. Determining evolutionary relationships between ILs therefore can be confusing. More recently, crystallographic data and the identification of common structural motifs have led to a more accurate classification system. To date, the known ILs can be divided into four major groups based on distinguishing structural features. These groups include the genes encoding the IL1-like cytokines, the class I helical cytokines (IL4-like, γ-chain and IL6/12-like), the class II helical cytokines (IL10-like and IL28-like) and the IL17-like cytokines. In addition, there are a number of ILs that do not fit into any of the above groups, due either to their unique structural features or lack of structural information. This suggests that the gene family organisation may be subject to further change in the near future. PMID:21106488

The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli.

PubMed

Crosse, Michael J; Di Liberto, Giovanni M; Bednar, Adam; Lalor, Edmund C

2016-01-01

Understanding how brains process sensory signals in natural environments is one of the key goals of twenty-first century neuroscience. While brain imaging and invasive electrophysiology will play key roles in this endeavor, there is also an important role to be played by noninvasive, macroscopic techniques with high temporal resolution such as electro- and magnetoencephalography. But challenges exist in determining how best to analyze such complex, time-varying neural responses to complex, time-varying and multivariate natural sensory stimuli. There has been a long history of applying system identification techniques to relate the firing activity of neurons to complex sensory stimuli and such techniques are now seeing increased application to EEG and MEG data. One particular example involves fitting a filter-often referred to as a temporal response function-that describes a mapping between some feature(s) of a sensory stimulus and the neural response. Here, we first briefly review the history of these system identification approaches and describe a specific technique for deriving temporal response functions known as regularized linear regression. We then introduce a new open-source toolbox for performing this analysis. We describe how it can be used to derive (multivariate) temporal response functions describing a mapping between stimulus and response in both directions. We also explain the importance of regularizing the analysis and how this regularization can be optimized for a particular dataset. We then outline specifically how the toolbox implements these analyses and provide several examples of the types of results that the toolbox can produce. Finally, we consider some of the limitations of the toolbox and opportunities for future development and application.

Structural and functional studies of a 50 kDa antigenic protein from Salmonella enterica serovar Typhi.

PubMed

Choong, Yee Siew; Lim, Theam Soon; Chew, Ai Lan; Aziah, Ismail; Ismail, Asma

2011-04-01

The high typhoid incidence rate in developing and under-developed countries emphasizes the need for a rapid, affordable and accessible diagnostic test for effective therapy and disease management. TYPHIDOT®, a rapid dot enzyme immunoassay test for typhoid, was developed from the discovery of a ∼50 kDa protein specific for Salmonella enterica serovar Typhi. However, the structure of this antigen remains unknown till today. Studies on the structure of this antigen are important to elucidate its function, which will in turn increase the efficiency of the development and improvement of the typhoid detection test. This paper described the predictive structure and function of the antigenically specific protein. The homology modeling approach was employed to construct the three-dimensional structure of the antigen. The built structure possesses the features of TolC-like outer membrane protein. Molecular docking simulation was also performed to further probe the functionality of the antigen. Docking results showed that hexamminecobalt, Co(NH(3))(6)(3+), as an inhibitor of TolC protein, formed favorable hydrogen bonds with D368 and D371 of the antigen. The single point (D368A, D371A) and double point (D368A and D371A) mutations of the antigen showed a decrease (single point mutation) and loss (double point mutations) of binding affinity towards hexamminecobalt. The architecture features of the built model and the docking simulation reinforced and supported that this antigen is indeed the variant of outer membrane protein, TolC. As channel proteins are important for the virulence and survival of bacteria, therefore this ∼50 kDa channel protein is a good specific target for typhoid detection test. Copyright © 2011 Elsevier Inc. All rights reserved.

Electronic connection between the quinone and cytochrome C redox pools and its role in regulation of mitochondrial electron transport and redox signaling.

PubMed

Sarewicz, Marcin; Osyczka, Artur

2015-01-01

Mitochondrial respiration, an important bioenergetic process, relies on operation of four membranous enzymatic complexes linked functionally by mobile, freely diffusible elements: quinone molecules in the membrane and water-soluble cytochromes c in the intermembrane space. One of the mitochondrial complexes, complex III (cytochrome bc1 or ubiquinol:cytochrome c oxidoreductase), provides an electronic connection between these two diffusible redox pools linking in a fully reversible manner two-electron quinone oxidation/reduction with one-electron cytochrome c reduction/oxidation. Several features of this homodimeric enzyme implicate that in addition to its well-defined function of contributing to generation of proton-motive force, cytochrome bc1 may be a physiologically important point of regulation of electron flow acting as a sensor of the redox state of mitochondria that actively responds to changes in bioenergetic conditions. These features include the following: the opposing redox reactions at quinone catalytic sites located on the opposite sides of the membrane, the inter-monomer electronic connection that functionally links four quinone binding sites of a dimer into an H-shaped electron transfer system, as well as the potential to generate superoxide and release it to the intermembrane space where it can be engaged in redox signaling pathways. Here we highlight recent advances in understanding how cytochrome bc1 may accomplish this regulatory physiological function, what is known and remains unknown about catalytic and side reactions within the quinone binding sites and electron transfers through the cofactor chains connecting those sites with the substrate redox pools. We also discuss the developed molecular mechanisms in the context of physiology of mitochondria. Copyright © 2015 the American Physiological Society.

Electronic Connection Between the Quinone and Cytochrome c Redox Pools and Its Role in Regulation of Mitochondrial Electron Transport and Redox Signaling

PubMed Central

Sarewicz, Marcin; Osyczka, Artur

2015-01-01

Mitochondrial respiration, an important bioenergetic process, relies on operation of four membranous enzymatic complexes linked functionally by mobile, freely diffusible elements: quinone molecules in the membrane and water-soluble cytochromes c in the intermembrane space. One of the mitochondrial complexes, complex III (cytochrome bc1 or ubiquinol:cytochrome c oxidoreductase), provides an electronic connection between these two diffusible redox pools linking in a fully reversible manner two-electron quinone oxidation/reduction with one-electron cytochrome c reduction/oxidation. Several features of this homodimeric enzyme implicate that in addition to its well-defined function of contributing to generation of proton-motive force, cytochrome bc1 may be a physiologically important point of regulation of electron flow acting as a sensor of the redox state of mitochondria that actively responds to changes in bioenergetic conditions. These features include the following: the opposing redox reactions at quinone catalytic sites located on the opposite sides of the membrane, the inter-monomer electronic connection that functionally links four quinone binding sites of a dimer into an H-shaped electron transfer system, as well as the potential to generate superoxide and release it to the intermembrane space where it can be engaged in redox signaling pathways. Here we highlight recent advances in understanding how cytochrome bc1 may accomplish this regulatory physiological function, what is known and remains unknown about catalytic and side reactions within the quinone binding sites and electron transfers through the cofactor chains connecting those sites with the substrate redox pools. We also discuss the developed molecular mechanisms in the context of physiology of mitochondria. PMID:25540143

Relationship between involvement and functional milk desserts intention to purchase. Influence on attitude towards packaging characteristics.

PubMed

Ares, Gastón; Besio, Mariángela; Giménez, Ana; Deliza, Rosires

2010-10-01

Consumers perceive functional foods as member of the particular food category to which they belong. In this context, apart from health and sensory characteristics, non-sensory factors such as packaging might have a key role on determining consumers' purchase decisions regarding functional foods. The aims of the present work were to study the influence of different package attributes on consumer willingness to purchase regular and functional chocolate milk desserts; and to assess if the influence of these attributes was affected by consumers' level of involvement with the product. A conjoint analysis task was carried out with 107 regular milk desserts consumers, who were asked to score their willingness to purchase of 16 milk dessert package concepts varying in five features of the package, and to complete a personal involvement inventory questionnaire. Consumers' level of involvement with the product affected their interest in the evaluated products and their reaction towards the considered conjoint variables, suggesting that it could be a useful segmentation tool during food development. Package colour and the presence of a picture on the label were the variables with the highest relative importance, regardless of consumers' involvement with the product. The importance of these variables was higher than the type of dessert indicating that packaging may play an important role in consumers' perception and purchase intention of functional foods.

Splicing regulatory factors, ageing and age-related disease.

PubMed

Latorre, Eva; Harries, Lorna W

2017-07-01

Alternative splicing is a co-transcriptional process, which allows for the production of multiple transcripts from a single gene and is emerging as an important control point for gene expression. Alternatively expressed isoforms often have antagonistic function and differential temporal or spatial expression patterns, yielding enormous plasticity and adaptability to cells and increasing their ability to respond to environmental challenge. The regulation of alternative splicing is critical for numerous cellular functions in both pathological and physiological conditions, and deregulated alternative splicing is a key feature of common chronic diseases. Isoform choice is controlled by a battery of splicing regulatory proteins, which include the serine arginine rich (SRSF) proteins and the heterogeneous ribonucleoprotein (hnRNP) classes of genes. These important splicing regulators have been implicated in age-related disease, and in the ageing process itself. This review will outline the important contribution of splicing regulator proteins to ageing and age-related disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Troublesome toxins: Time to re-think plant-herbivore interactions in vertebrate ecology

USGS Publications Warehouse

Swihart, R.K.; DeAngelis, D.L.; Feng, Z.; Bryant, J.P.

2009-01-01

Earlier models of plant-herbivore interactions relied on forms of functional response that related rates of ingestion by herbivores to mechanical or physical attributes such as bite size and rate. These models fail to predict a growing number of findings that implicate chemical toxins as important determinants of plant-herbivore dynamics. Specifically, considerable evidence suggests that toxins set upper limits on food intake for many species of herbivorous vertebrates. Herbivores feeding on toxin-containing plants must avoid saturating their detoxification systems, which often occurs before ingestion rates are limited by mechanical handling of food items. In light of the importance of plant toxins, a new approach is needed to link herbivores to their food base. We discuss necessary features of such an approach, note recent advances in herbivore functional response models that incorporate effects of plant toxins, and mention predictions that are consistent with observations in natural systems. Future ecological studies will need to address explicitly the importance of plant toxins in shaping plant and herbivore communities.

Great Lakes rivermouth ecosystems: scientific synthesis and management implications

USGS Publications Warehouse

Larson, James H.; Trebitz, Anett S.; Steinman, Alan D.; Wiley, Michael J.; Carlson Mazur, Martha; Pebbles, Victoria; Braun, Heather A.; Seelbach, Paul W.

2013-01-01

At the interface of the Great Lakes and their tributary rivers lies the rivermouths, a class of aquatic ecosystem where lake and lotic processes mix and distinct features emerge. Many rivermouths are the focal point of both human interaction with the Great Lakes and human impacts to the lakes; many cities, ports, and beaches are located in rivermouth ecosystems, and these human pressures often degrade key ecological functions that rivermouths provide. Despite their ecological uniqueness and apparent economic importance, there has been relatively little research on these ecosystems as a class relative to studies on upstream rivers or the open-lake waters. Here we present a synthesis of current knowledge about ecosystem structure and function in Great Lakes rivermouths based on studies in both Laurentian rivermouths, coastal wetlands, and marine estuarine systems. A conceptual model is presented that establishes a common semantic framework for discussing the characteristic spatial features of rivermouths. This model then is used to conceptually link ecosystem structure and function to ecological services provided by rivermouths. This synthesis helps identify the critical gaps in understanding rivermouth ecology. Specifically, additional information is needed on how rivermouths collectively influence the Great Lakes ecosystem, how human alterations influence rivermouth functions, and how ecosystem services provided by rivermouths can be managed to benefit the surrounding socioeconomic networks.

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis

PubMed Central

Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

2014-01-01

Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. Objective The aims were to describe how to: (i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and (ii) automatically identify the features that best distinguish the groups. Methods The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described – simple or complex; presentation order – which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo18 were used,which included 200 healthy Brazilians of both genders. Results and Conclusion A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods. PMID:29213908

Influence of contrast morphogenetic features of urban constructed soils on the functioning of Moscow green lawn urban ecosystems: analysis based on the field model experiment

NASA Astrophysics Data System (ADS)

Epikhina, Anna; Vizirskaya, Mariya; Mazirov, Ilya; Vasenev, Vyacheslav; Vasenev, Ivan; Valentini, Riccardo

2014-05-01

Green lawns are the key element of the urban environment. They occupy a considerable part of the city area and locate in different urban functional zones. Urban constructed soils under green lawns have a unique spatial variability in chemical and morphogenetic features. So far, there is lack of information on the influence of morphogenetic features of urban soils on the functioning of the green lawn ecosystems especially in Moscow - the biggest megalopolis in Europe. Urban lawns perform a number of principal functions including both aesthetic and environmental. The role of the green lawn ecosystems in global carbon cycle is one of their main environmental functions. It is traditionally assessed through carbon stocks and fluxes in the basic ecosystem components. So far, such a data for the urban lawn ecosystems of the Moscow megapolis is lacking. In addition to environmental functions, green lawns perform an important ornamental role, which is also a critical criterion of their optimal functioning. Considering the variability of driving factors, influencing green lawns in urban environment, we carry out the model experiment in order to analyze "pure" effect of soil morphogenetic features. The current study aimed to analyze the influence of contrast morphogenetic features of urban constructed soils on the environmental and aesthetic functions of lawn ecosystems in Moscow megapolis basing in the model experiment. We carry out the model experiment located at the experimental field of the Russian State Agrarian University. Special transparent containers developed for the experiment, provided an option to observe soil morphogenetic features dynamics, including the depth and material of the organic transformation. At the same soil body inside the containers was united with the outside environment through the system of holes in the bottom and walls. The set of urban constructed soils includ four contrast types of the top soil (turf (T), turf-sand (TSa), turf-soil (TSo) and sand-soil (SS)) with three version of the depths (5, 10 and 20 cm). Soil construction with 10 cm organic horizon from TS top soil was taken as a reference. Grass mixture used for the green lawn including: Lolium perenne, Poa pratensis and Festuca rubra. For all the containers we measured soil CO2 emission by Li-820, soil temperature and moisture and the grass ornamental quality based on the 30-score scale (Laptev; 1988). All the measurements have been done in June-October 2013 with two-week time steps. We also observed the dynamic in soil chemical features (Corg, Ntot and pHKCl) monthly. We found high seasonal dynamics for all the observed functioning parameters. The highest CO2 emission was obtained in the beginning of July, whereas the lowest one - at the end of August. Maximal averaged CO2 emission was shown for the TSa and TSo substrates with the 20 cm depth. The lowest flux has been fixed for the more mineralized substrat. Soil moisture was shown as the main driving factor influencing CO2 emission both for the seasonal dynamics and for the averaged values for different substrates and depths (r=0.5, p<0.05). As for the aesthetic function the highest grass ornamental quality was shown for 20 cm TS and 5 cm T substrate (30 scores), whereas the lowest one was obtained for SS substrate with 5 and 20 cm depths (5 scores). We also obtained high positive correlation between the grass ornamental quality and the CO2 emissions (r=0.84, p>0.05). This outcome highlights that the standards of urban constructed soils' optimal features should be the compromise between the beauty of the green lawn and climate mitigation demands. Supported by the RF governmental grant 11.G34.31.0079

[FEATURES OF CONSTITUTIONAL CHARACTERISTICS OF YOUNG MALES AGED OF 17-20 YEARS, NATIVES OF THE BAIKAL REGION WITH REGARD TO THEIR FUNCTIONAL GROUPS OF HEALTH].

PubMed

Kolokoltsev, M M

2016-01-01

The study of somatotypes of the constitution is an important point in planning of the improvements of measures among the population in various regions of Russia. The purpose of the work was to reveal features of age dynamics of somatotypes of the constitution in students of youthful age of the Baikal Region by means of somatotyping according to scheme by Nikityuk B. A. and Kozlova A.I (1990) with taking into account their functional group of health. There were examined 1286 Slavic young males, natives of the Irkutsk region, aged of 17-20 years, from them, according to data of the medical examination 996 were referred to the 1st (main) and 290--to the 2nd (preparatory) functional group of health for physical exercises. There were established significant differences in somatotypes of the constitution in young men of the 1st and 2nd functional groups of health. In both functional groups there is noted a significant amount of young males with transitional somatotypes that testifies to incompleteness of growth processes of their organism. The obtained results of a somatotyping are used in the educational process for a training individualization on physical culture of students of IRGTU, and also in construction of independent physical--improving programs.

miRNet - dissecting miRNA-target interactions and functional associations through network-based visual analysis

PubMed Central

Fan, Yannan; Siklenka, Keith; Arora, Simran K.; Ribeiro, Paula; Kimmins, Sarah; Xia, Jianguo

2016-01-01

MicroRNAs (miRNAs) can regulate nearly all biological processes and their dysregulation is implicated in various complex diseases and pathological conditions. Recent years have seen a growing number of functional studies of miRNAs using high-throughput experimental technologies, which have produced a large amount of high-quality data regarding miRNA target genes and their interactions with small molecules, long non-coding RNAs, epigenetic modifiers, disease associations, etc. These rich sets of information have enabled the creation of comprehensive networks linking miRNAs with various biologically important entities to shed light on their collective functions and regulatory mechanisms. Here, we introduce miRNet, an easy-to-use web-based tool that offers statistical, visual and network-based approaches to help researchers understand miRNAs functions and regulatory mechanisms. The key features of miRNet include: (i) a comprehensive knowledge base integrating high-quality miRNA-target interaction data from 11 databases; (ii) support for differential expression analysis of data from microarray, RNA-seq and quantitative PCR; (iii) implementation of a flexible interface for data filtering, refinement and customization during network creation; (iv) a powerful fully featured network visualization system coupled with enrichment analysis. miRNet offers a comprehensive tool suite to enable statistical analysis and functional interpretation of various data generated from current miRNA studies. miRNet is freely available at http://www.mirnet.ca. PMID:27105848

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

PubMed

Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

2016-12-01

The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

Transcriptome Analysis of the Arabidopsis Megaspore Mother Cell Uncovers the Importance of RNA Helicases for Plant Germline Development

PubMed Central

Schmidt, Anja; Wuest, Samuel E.; Vijverberg, Kitty; Baroux, Célia; Kleen, Daniela; Grossniklaus, Ueli

2011-01-01

Germ line specification is a crucial step in the life cycle of all organisms. For sexual plant reproduction, the megaspore mother cell (MMC) is of crucial importance: it marks the first cell of the plant “germline” lineage that gets committed to undergo meiosis. One of the meiotic products, the functional megaspore, subsequently gives rise to the haploid, multicellular female gametophyte that harbours the female gametes. The MMC is formed by selection and differentiation of a single somatic, sub-epidermal cell in the ovule. The transcriptional network underlying MMC specification and differentiation is largely unknown. We provide the first transcriptome analysis of an MMC using the model plant Arabidopsis thaliana with a combination of laser-assisted microdissection and microarray hybridizations. Statistical analyses identified an over-representation of translational regulation control pathways and a significant enrichment of DEAD/DEAH-box helicases in the MMC transcriptome, paralleling important features of the animal germline. Analysis of two independent T-DNA insertion lines suggests an important role of an enriched helicase, MNEME (MEM), in MMC differentiation and the restriction of the germline fate to only one cell per ovule primordium. In heterozygous mem mutants, additional enlarged MMC-like cells, which sometimes initiate female gametophyte development, were observed at higher frequencies than in the wild type. This closely resembles the phenotype of mutants affected in the small RNA and DNA-methylation pathways important for epigenetic regulation. Importantly, the mem phenotype shows features of apospory, as female gametophytes initiate from two non-sister cells in these mutants. Moreover, in mem gametophytic nuclei, both higher order chromatin structure and the distribution of LIKE HETEROCHROMATIN PROTEIN1 were affected, indicating epigenetic perturbations. In summary, the MMC transcriptome sets the stage for future functional characterization as illustrated by the identification of MEM, a novel gene involved in the restriction of germline fate. PMID:21949639

On the structure of Bayesian network for Indonesian text document paraphrase identification

NASA Astrophysics Data System (ADS)

Prayogo, Ario Harry; Syahrul Mubarok, Mohamad; Adiwijaya

2018-03-01

Paraphrase identification is an important process within natural language processing. The idea is to automatically recognize phrases that have different forms but contain same meanings. For examples if we input query “causing fire hazard”, then the computer has to recognize this query that this query has same meaning as “the cause of fire hazard. Paraphrasing is an activity that reveals the meaning of an expression, writing, or speech using different words or forms, especially to achieve greater clarity. In this research we will focus on classifying two Indonesian sentences whether it is a paraphrase to each other or not. There are four steps in this research, first is preprocessing, second is feature extraction, third is classifier building, and the last is performance evaluation. Preprocessing consists of tokenization, non-alphanumerical removal, and stemming. After preprocessing we will conduct feature extraction in order to build new features from given dataset. There are two kinds of features in the research, syntactic features and semantic features. Syntactic features consist of normalized levenshtein distance feature, term-frequency based cosine similarity feature, and LCS (Longest Common Subsequence) feature. Semantic features consist of Wu and Palmer feature and Shortest Path Feature. We use Bayesian Networks as the method of training the classifier. Parameter estimation that we use is called MAP (Maximum A Posteriori). For structure learning of Bayesian Networks DAG (Directed Acyclic Graph), we use BDeu (Bayesian Dirichlet equivalent uniform) scoring function and for finding DAG with the best BDeu score, we use K2 algorithm. In evaluation step we perform cross-validation. The average result that we get from testing the classifier as follows: Precision 75.2%, Recall 76.5%, F1-Measure 75.8% and Accuracy 75.6%.

AMPK-mediated regulation of neuronal metabolism and function in brain diseases.

PubMed

Liu, Yu-Ju; Chern, Yijuang

2015-01-01

The AMP-activated protein kinase (AMPK) is a serine/threonine kinase that functions as a key energy sensor in a wide variety of tissues. This kinase has been a major drug target for metabolic diseases (e.g., type 2 diabetes) and cancers. For example, metformin (an activator of AMPK) is a first-line diabetes drug that protects against cancers. Abnormal regulation of AMPK has been implicated in several brain diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and stroke. Given the emerging importance of neurodegenerative diseases in our aging societies, this review features the recent studies that have delineated the functions of AMPK in brain diseases and discusses their potential clinical implications or roles as drug targets in brain diseases.

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

PubMed

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

2013-10-01

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

Effect of X-ray Line Spectra Profile Fitting with Pearson VII, Pseudo-Voigt and Generalized Fermi Functions on Asphalt Binder Aromaticity and Crystallite Parameters

NASA Astrophysics Data System (ADS)

Gebresellasie, K.; Shirokoff, J.; Lewis, J. C.

2012-12-01

X-ray line spectra profile fitting using Pearson VII, pseudo-Voigt and generalized Fermi functions was performed on asphalt binders prior to the calculation of aromaticity and crystallite size parameters. The effects of these functions on the results are presented and discussed in terms of the peak profile fit parameters, the uncertainties in calculated values that can arise owing to peak shape, peak features in the pattern and crystallite size according to the asphalt models (Yen, modified Yen or Yen-Mullins) and theories. Interpretation of these results is important in terms of evaluating the performance of asphalt binders widely used in the application of transportation systems (roads, highways, airports).

Learning to associate orientation with color in early visual areas by associative decoded fMRI neurofeedback

PubMed Central

Amano, Kaoru; Shibata, Kazuhisa; Kawato, Mitsuo; Sasaki, Yuka; Watanabe, Takeo

2016-01-01

Summary Associative learning is an essential brain process where the contingency of different items increases after training. Associative learning has been found to occur in many brain regions [1-4]. However, there is no clear evidence that associative learning of visual features occurs in early visual areas, although a number of studies have indicated that learning of a single visual feature (perceptual learning) involves early visual areas [5-8]. Here, via decoded functional magnetic resonance imaging (fMRI) neurofeedback, termed “DecNef” [9], we tested whether associative learning of color and orientation can be created in early visual areas. During three days' training, DecNef induced fMRI signal patterns that corresponded to a specific target color (red) mostly in early visual areas while a vertical achromatic grating was physically presented to participants. As a result, participants came to perceive “red” significantly more frequently than “green” in an achromatic vertical grating. This effect was also observed 3 to 5 months after the training. These results suggest that long-term associative learning of the two different visual features such as color and orientation was created most likely in early visual areas. This newly extended technique that induces associative learning is called “A(ssociative)-DecNef” and may be used as an important tool for understanding and modifying brain functions, since associations are fundamental and ubiquitous functions in the brain. PMID:27374335

Using Anisotropic 3D Minkowski Functionals for Trabecular Bone Characterization and Biomechanical Strength Prediction in Proximal Femur Specimens

PubMed Central

Nagarajan, Mahesh B.; De, Titas; Lochmüller, Eva-Maria; Eckstein, Felix; Wismüller, Axel

2017-01-01

The ability of Anisotropic Minkowski Functionals (AMFs) to capture local anisotropy while evaluating topological properties of the underlying gray-level structures has been previously demonstrated. We evaluate the ability of this approach to characterize local structure properties of trabecular bone micro-architecture in ex vivo proximal femur specimens, as visualized on multi-detector CT, for purposes of biomechanical bone strength prediction. To this end, volumetric AMFs were computed locally for each voxel of volumes of interest (VOI) extracted from the femoral head of 146 specimens. The local anisotropy captured by such AMFs was quantified using a fractional anisotropy measure; the magnitude and direction of anisotropy at every pixel was stored in histograms that served as a feature vectors that characterized the VOIs. A linear multi-regression analysis algorithm was used to predict the failure load (FL) from the feature sets; the predicted FL was compared to the true FL determined through biomechanical testing. The prediction performance was measured by the root mean square error (RMSE) for each feature set. The best prediction performance was obtained from the fractional anisotropy histogram of AMF Euler Characteristic (RMSE = 1.01 ± 0.13), which was significantly better than MDCT-derived mean BMD (RMSE = 1.12 ± 0.16, p<0.05). We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding regional trabecular bone quality and contribute to improved bone strength prediction, which is important for improving the clinical assessment of osteoporotic fracture risk. PMID:29170581

Key structural features of nonsteroidal ligands for binding and activation of the androgen receptor.

PubMed

Yin, Donghua; He, Yali; Perera, Minoli A; Hong, Seoung Soo; Marhefka, Craig; Stourman, Nina; Kirkovsky, Leonid; Miller, Duane D; Dalton, James T

2003-01-01

The purposes of the present studies were to examine the androgen receptor (AR) binding ability and in vitro functional activity of multiple series of nonsteroidal compounds derived from known antiandrogen pharmacophores and to investigate the structure-activity relationships (SARs) of these nonsteroidal compounds. The AR binding properties of sixty-five nonsteroidal compounds were assessed by a radioligand competitive binding assay with the use of cytosolic AR prepared from rat prostates. The AR agonist and antagonist activities of high-affinity ligands were determined by the ability of the ligand to regulate AR-mediated transcriptional activation in cultured CV-1 cells, using a cotransfection assay. Nonsteroidal compounds with diverse structural features demonstrated a wide range of binding affinity for the AR. Ten compounds, mainly from the bicalutamide-related series, showed a binding affinity superior to the structural pharmacophore from which they were derived. Several SARs regarding nonsteroidal AR binding were revealed from the binding data, including stereoisomeric conformation, steric effect, and electronic effect. The functional activity of high-affinity ligands ranged from antagonist to full agonist for the AR. Several structural features were found to be determinative of agonist and antagonist activities. The nonsteroidal AR agonists identified from the present studies provided a pool of candidates for further development of selective androgen receptor modulators (SARMs) for androgen therapy. Also, these studies uncovered or confirmed numerous important SARs governing AR binding and functional properties by nonsteroidal molecules, which would be valuable in the future structural optimization of SARMs.

Particle Swarm Optimization approach to defect detection in armour ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2017-03-01

In this research, various extracted features were used in the development of an automated ultrasonic sensor based inspection system that enables defect classification in each ceramic component prior to despatch to the field. Classification is an important task and large number of irrelevant, redundant features commonly introduced to a dataset reduces the classifiers performance. Feature selection aims to reduce the dimensionality of the dataset while improving the performance of a classification system. In the context of a multi-criteria optimization problem (i.e. to minimize classification error rate and reduce number of features) such as one discussed in this research, the literature suggests that evolutionary algorithms offer good results. Besides, it is noted that Particle Swarm Optimization (PSO) has not been explored especially in the field of classification of high frequency ultrasonic signals. Hence, a binary coded Particle Swarm Optimization (BPSO) technique is investigated in the implementation of feature subset selection and to optimize the classification error rate. In the proposed method, the population data is used as input to an Artificial Neural Network (ANN) based classification system to obtain the error rate, as ANN serves as an evaluator of PSO fitness function. Copyright © 2016. Published by Elsevier B.V.

Numerical study on tailoring the shock sensitivity of TATB-based explosives using mesostructural features

NASA Astrophysics Data System (ADS)

Springer, H. Keo

2017-06-01

Advanced manufacturing techniques offer control of explosive mesostructures necessary to tailor its shock sensitivity. However, structure-property relationships are not well established for explosives so there is little material design guidance for these techniques. The objective of this numerical study is to demonstrate how TATB-based explosives can be sensitized to shocks using mesostructural features. For this study, we use LX-17 (92.5%wt TATB, 7.5%wt Kel-F 800) as the prototypical TATB-based explosive. We employ features with different geometries and materials. HMX-based explosive features, high shock impedance features, and pores are used to sensitive the LX-17. Simulations are performed in the multi-physics hydrocode, ALE3D. A reactive flow model is used to simulate the shock initiation response of the explosives. Our metric for shock sensitivity in this study is run distance to detonation as a function of applied pressure. These numerical studies are important because they guide the design of novel energetic materials. This work was performed under the auspices of the United States Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-724986.

Deep neural mapping support vector machines.

PubMed

Li, Yujian; Zhang, Ting

2017-09-01

The choice of kernel has an important effect on the performance of a support vector machine (SVM). The effect could be reduced by NEUROSVM, an architecture using multilayer perceptron for feature extraction and SVM for classification. In binary classification, a general linear kernel NEUROSVM can be theoretically simplified as an input layer, many hidden layers, and an SVM output layer. As a feature extractor, the sub-network composed of the input and hidden layers is first trained together with a virtual ordinary output layer by backpropagation, then with the output of its last hidden layer taken as input of the SVM classifier for further training separately. By taking the sub-network as a kernel mapping from the original input space into a feature space, we present a novel model, called deep neural mapping support vector machine (DNMSVM), from the viewpoint of deep learning. This model is also a new and general kernel learning method, where the kernel mapping is indeed an explicit function expressed as a sub-network, different from an implicit function induced by a kernel function traditionally. Moreover, we exploit a two-stage procedure of contrastive divergence learning and gradient descent for DNMSVM to jointly training an adaptive kernel mapping instead of a kernel function, without requirement of kernel tricks. As a whole of the sub-network and the SVM classifier, the joint training of DNMSVM is done by using gradient descent to optimize the objective function with the sub-network layer-wise pre-trained via contrastive divergence learning of restricted Boltzmann machines. Compared to the separate training of NEUROSVM, the joint training is a new algorithm for DNMSVM to have advantages over NEUROSVM. Experimental results show that DNMSVM can outperform NEUROSVM and RBFSVM (i.e., SVM with the kernel of radial basis function), demonstrating its effectiveness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

PubMed

Cheng, Wen; Yan, Changhui

2017-01-01

Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, we present a graph-mining method for discovering biological patterns in the protein-RNA interfaces. We represented known protein-RNA interfaces using graphs and then discovered graph patterns enriched in the interfaces. Comparison of the discovered graph patterns with UniProt annotations showed that the graph patterns had a significant overlap with residue sites that had been proven crucial for the RNA binding by experimental methods. Using 200 patterns as input features, a support vector machine method was able to classify protein surface patches into RNA-binding sites and non-RNA-binding sites with 84.0% accuracy and 88.9% precision. We built a simple scoring function that calculated the total number of the graph patterns that occurred in a protein-RNA interface. That scoring function was able to discriminate near-native protein-RNA complexes from docking decoys with a performance comparable with that of a state-of-the-art complex scoring function. Our work also revealed possible patterns that might be important for binding affinity.

Defining functional groups based on running kinematics using Self-Organizing Maps and Support Vector Machines.

PubMed

Hoerzer, Stefan; von Tscharner, Vinzenz; Jacob, Christian; Nigg, Benno M

2015-07-16

A functional group is a collection of individuals who react in a similar way to a specific intervention/product such as a sport shoe. Matching footwear features to a functional group can possibly enhance footwear-related comfort, improve running performance, and decrease the risk of movement-related injuries. To match footwear features to a functional group, one has to first define the different groups using their distinctive movement patterns. Therefore, the main objective of this study was to propose and apply a methodological approach to define functional groups with different movement patterns using Self-Organizing Maps and Support Vector Machines. Further study objectives were to identify differences in age, gender and footwear-related comfort preferences between the functional groups. Kinematic data and subjective comfort preferences of 88 subjects (16-76 years; 45 m/43 f) were analysed. Eight functional groups with distinctive movement patterns were defined. The findings revealed that most of the groups differed in age or gender. Certain functional groups differed in their comfort preferences and, therefore, had group-specific footwear requirements to enhance footwear-related comfort. Some of the groups, which had group-specific footwear requirements, did not show any differences in age or gender. This is important because when defining functional groups simply using common grouping criteria like age or gender, certain functional groups with group-specific movement patterns and footwear requirements might not be detected. This emphasises the power of the proposed pattern recognition approach to automatically define groups by their distinctive movement patterns in order to be able to address their group-specific product requirements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Where and what is the paralaminar nucleus? A review on a unique and frequently overlooked area of the primate amygdala

PubMed Central

deCampo, Danielle; Fudge, Julie

2011-01-01

The primate amygdala is composed of multiple subnuclei that play distinct roles in amygdala function. While some nuclei have been areas of focused investigation, others remain virtually unknown. One of the more obscure regions of the amygdala is the paralaminar nucleus (PL). The PL in humans and non-human primates is relatively expanded compared to lower species. Long considered to be part of the basal nucleus, the PL has several interesting features that make it unique. These features include a dense concentration of small cells, high concentrations of receptors for corticotropin releasing hormone and benzodiazepines, and dense innervation of serotonergic fibers. More recently, high concentrations of immature-appearing cells have been noted in the primate PL, suggesting special mechanisms of neural plasticity. Following a brief overview of amygdala structure and function, this review will provide an introduction to the history, embryology, anatomical connectivity, immunohistochemical and cytoarchitectural properties of the PL. Our conclusion based on the following information, is that the PL is a unique subregion of the amygdala that may yield important clues about the normal growth and function of the amygdala, particularly in higher species. PMID:21906624

Incidence, Clinical Correlates and Treatment Effect of Rage in Anxious Children

PubMed Central

Salloum, Alison; De Nadai, Alessandro S.; McBride, Nicole; Crawford, Erika A.; Lewin, Adam B.; Storch, Eric A.

2015-01-01

Episodic rage represents an important and underappreciated clinical feature in pediatric anxiety. This study examined the incidence and clinical correlates of rage in children with anxiety disorders. Change in rage during treatment for anxiety was also examined. Participants consisted of 107 children diagnosed with an anxiety disorder and their parents. Participants completed structured clinical interviews and questionnaire measures to assess rage, anxiety, functional impairment, family accommodation and caregiver strain, as well as the quality of the child's relationship with family and peers. Rage was a common feature amongst children with anxiety disorders. Rage was associated with a more severe clinical profile, including increased anxiety severity, functional impairment, family accommodation and caregiver strain, as well as poorer relationships with parents, siblings, extended family and peers. Rage was more common in children with separation anxiety, comorbid anxiety, attention deficit/hyperactivity disorder and behavioral disorders, but not depressive symptoms. Rage predicted higher levels of functional impairment, beyond the effect of anxiety severity. Rage severity reduced over treatment in line with changes in anxiety symptoms. Findings suggest that rage is a marker of greater psychopathology in anxious youth. Standard cognitive behavioral treatment for anxiety appears to reduce rage without adjunctive treatment. PMID:26235476

Structural disorder in plant proteins: where plasticity meets sessility.

PubMed

Covarrubias, Alejandra A; Cuevas-Velazquez, Cesar L; Romero-Pérez, Paulette S; Rendón-Luna, David F; Chater, Caspar C C

2017-09-01

Plants are sessile organisms. This intriguing nature provokes the question of how they survive despite the continual perturbations caused by their constantly changing environment. The large amount of knowledge accumulated to date demonstrates the fascinating dynamic and plastic mechanisms, which underpin the diverse strategies selected in plants in response to the fluctuating environment. This phenotypic plasticity requires an efficient integration of external cues to their growth and developmental programs that can only be achieved through the dynamic and interactive coordination of various signaling networks. Given the versatility of intrinsic structural disorder within proteins, this feature appears as one of the leading characters of such complex functional circuits, critical for plant adaptation and survival in their wild habitats. In this review, we present information of those intrinsically disordered proteins (IDPs) from plants for which their high level of predicted structural disorder has been correlated with a particular function, or where there is experimental evidence linking this structural feature with its protein function. Using examples of plant IDPs involved in the control of cell cycle, metabolism, hormonal signaling and regulation of gene expression, development and responses to stress, we demonstrate the critical importance of IDPs throughout the life of the plant.

Histone Variants and Composition in the Developing Brain: Should MeCP2 Care?

PubMed

Zago, Valentina; Pinar-CabezaDeVaca, Cristina; Vincent, John B; Ausio, Juan

2017-01-01

Specific compositional chromatin features distinguish brain/neuronal chromatin from that of other tissues and are critical to this organ and cell type development and neuroplasticity. These features include a significant turnover of the major constitutive chromosomal proteins, including the (canonical) replication-dependent histones, the replication-independent replacement histone variants, as well as the chromatin associated transcriptional regulator MeCP2 (methyl CpG binding protein 2). Alterations of histones and MeCP2 have already been implicated in many brain disorders. Despite the relevance of histone variants to chromatin structure and function, only recently has some exciting literature started to re-emerge that directly relates them to neuron plasticity and cognition. However, the amount of information available on the functional role of these histones is still very limited. The purpose of this review is to focus attention to this important group of chromatin proteins, which, in the brain, possess overlapping structural and functional roles with the highly abundant presence of MeCP2. There is an imperative need to understand how all these proteins communicate with each other, and future research will hopefully provide us with answers.

Discovering cancer vulnerabilities using high-throughput micro-RNA screening.

PubMed

Nikolic, Iva; Elsworth, Benjamin; Dodson, Eoin; Wu, Sunny Z; Gould, Cathryn M; Mestdagh, Pieter; Marshall, Glenn M; Horvath, Lisa G; Simpson, Kaylene J; Swarbrick, Alexander

2017-12-15

Micro-RNAs (miRNAs) are potent regulators of gene expression and cellular phenotype. Each miRNA has the potential to target hundreds of transcripts within the cell thus controlling fundamental cellular processes such as survival and proliferation. Here, we exploit this important feature of miRNA networks to discover vulnerabilities in cancer phenotype, and map miRNA-target relationships across different cancer types. More specifically, we report the results of a functional genomics screen of 1280 miRNA mimics and inhibitors in eight cancer cell lines, and its presentation in a sophisticated interactive data portal. This resource represents the most comprehensive survey of miRNA function in oncology, incorporating breast cancer, prostate cancer and neuroblastoma. A user-friendly web portal couples this experimental data with multiple tools for miRNA target prediction, pathway enrichment analysis and visualization. In addition, the database integrates publicly available gene expression and perturbation data enabling tailored and context-specific analysis of miRNA function in a particular disease. As a proof-of-principle, we use the database and its innovative features to uncover novel determinants of the neuroblastoma malignant phenotype. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

[Associative Learning between Orientation and Color in Early Visual Areas].

PubMed

Amano, Kaoru; Shibata, Kazuhisa; Kawato, Mitsuo; Sasaki, Yuka; Watanabe, Takeo

2017-08-01

Associative learning is an essential neural phenomenon where the contingency of different items increases after training. Although associative learning has been found to occur in many brain regions, there is no clear evidence that associative learning of visual features occurs in early visual areas. Here, we developed an associative decoded functional magnetic resonance imaging (fMRI) neurofeedback (A-DecNef) to determine whether associative learning of color and orientation can be induced in early visual areas. During the three days' training, A-DecNef induced fMRI signal patterns that corresponded to a specific target color (red) mostly in early visual areas while a vertical achromatic grating was simultaneously, physically presented to participants. Consequently, participants' perception of "red" was significantly more frequently than that of "green" in an achromatic vertical grating. This effect was also observed 3 to 5 months after training. These results suggest that long-term associative learning of two different visual features such as color and orientation, was induced most likely in early visual areas. This newly extended technique that induces associative learning may be used as an important tool for understanding and modifying brain function, since associations are fundamental and ubiquitous with respect to brain function.

An essential role for IL-2 receptor in regulatory T cell function

PubMed Central

Levine, Andrew G; Fan, Xiying; Klein, Ulf; Zheng, Ye; Gasteiger, Georg; Feng, Yongqiang; Fontenot, Jason D.; Rudensky, Alexander Y.

2016-01-01

Regulatory T (Treg) cells, expressing abundant amounts of the IL-2 receptor (IL-2R), are reliant on IL-2 produced by activated T cells. This feature implied a key role for a simple network based on IL-2 consumption by Treg cells in their suppressor function. However, congenital deficiency in IL-2R results in reduced expression of the Treg cell lineage specification factor Foxp3, confounding experimental efforts to understand the role of IL-2R expression and signaling in Treg suppressor function. Using genetic gain and loss of function approaches, we demonstrate that IL-2 capture is dispensable for control of CD4+ T cells, but is important for limiting CD8+ T cell activation, and that IL-2R dependent STAT5 transcription factor activation plays an essential role in Treg cell suppressor function separable from T cell receptor signaling. PMID:27595233

[Morphogenesis of vaginal aplasia. Therapeutic deductions].

PubMed

Minh, H N; Smadja, A; Belaisch, J

1985-01-01

On the basis of the studies of the embryogenesis of the vagina, the authors consider that malformations classically described as being partial aplasia should not be separated from the total absence of the vagina. The important feature is the association of a functioning or non functioning uterus with the absence of the vagina. They believe that it is incorrect to describe the pouch of menstrual retention associated with a functioning uterus as "haematocolpos" and that is not justified to describe the cup-shaped vestibular depression as "hemi-vagina". According to the authors, although vaginal aplasia with a functioning uterus forming a pouch of menstrual retention constitutes an absolute indication for surgery, surgery is not justified in cases of vaginal aplasia with a non functioning uterus. If Frank's method fails in these cases, the patient or the couple should be referred to a sexologist, as women with this anomaly retain a perfect femininity, although unable to conceive.

Requirements for a documentation of the image manipulation processes within PACS

NASA Astrophysics Data System (ADS)

Retter, Klaus; Rienhoff, Otto; Karsten, Ch.; Prince, Hazel E.

1990-08-01

This paper discusses to which extent manipulation functions which have been applied to images handled in PACS should be documented. After postulating an increasing amount of postprocessing features on PACS-consoles, legal, educational and medical reasons for a documentation of image manipulation processes are presented. Besides legal necessities, aspects of storage capacity, response time, and potential uses determine the extent of this documentation. Is there a specific kind of manipulation functions which has to be documented generally? Should the physician decide which parts of the various pathways he tries are recorded by the system? To distinguish, for example, between reversible and irreversible functions or between interactive and non-interactive functions is one step towards a solution. Another step is to establish definitions for terms like "raw" and "final" image. The paper systematizes these questions and offers strategic help. The answers will have an important impact on PACS design and functionality.

Laser shape setting of superelastic nitinol wires: Functional properties and microstructure

NASA Astrophysics Data System (ADS)

Tuissi, Ausonio; Coduri, Mauro; Biffi, Carlo Alberto

Shape setting is one of the most important steps in the production route of Nitinol Shape Memory Alloys (SMAs), as it can fix the functional properties, such as the shape memory effect and the superelasticity (SE). The conventional method for making the shape setting is performed at 400-500∘C in furnaces. In this work, a laser beam was adopted for performing straight shape setting on commercially available austenitic Nitinol thin wires. The laser beam, at different power levels, was moved along the wire length for inducing the functional performances. Calorimetric, pseudo-elastic and microstructural features of the laser annealed wires were studied through differential scanning calorimetry, tensile testing and high energy X-ray diffraction, respectively. It can be stated that the laser technology can induce SE in thin Nitinol wires: the wire performances can be modulated in function of the laser power and improved functional properties can be obtained.

Using LabView for real-time monitoring and tracking of multiple biological objects

NASA Astrophysics Data System (ADS)

Nikolskyy, Aleksandr I.; Krasilenko, Vladimir G.; Bilynsky, Yosyp Y.; Starovier, Anzhelika

2017-04-01

Today real-time studying and tracking of movement dynamics of various biological objects is important and widely researched. Features of objects, conditions of their visualization and model parameters strongly influence the choice of optimal methods and algorithms for a specific task. Therefore, to automate the processes of adaptation of recognition tracking algorithms, several Labview project trackers are considered in the article. Projects allow changing templates for training and retraining the system quickly. They adapt to the speed of objects and statistical characteristics of noise in images. New functions of comparison of images or their features, descriptors and pre-processing methods will be discussed. The experiments carried out to test the trackers on real video files will be presented and analyzed.

A neuro-fuzzy architecture for real-time applications

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.; Huang, Song

1992-01-01

Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach.

nextPARS: parallel probing of RNA structures in Illumina

PubMed Central

Saus, Ester; Willis, Jesse R.; Pryszcz, Leszek P.; Hafez, Ahmed; Llorens, Carlos; Himmelbauer, Heinz

2018-01-01

RNA molecules play important roles in virtually every cellular process. These functions are often mediated through the adoption of specific structures that enable RNAs to interact with other molecules. Thus, determining the secondary structures of RNAs is central to understanding their function and evolution. In recent years several sequencing-based approaches have been developed that allow probing structural features of thousands of RNA molecules present in a sample. Here, we describe nextPARS, a novel Illumina-based implementation of in vitro parallel probing of RNA structures. Our approach achieves comparable accuracy to previous implementations, while enabling higher throughput and sample multiplexing. PMID:29358234

Biomimicry in metal-organic materials

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

Zhang, MW; Gu, ZY; Bosch, M

2015-06-15

Nature has evolved a great number of biological molecules which serve as excellent constructional or functional units for metal-organic materials (MOMs). Even though the study of biomimetic MOMs is still at its embryonic stage, considerable progress has been made in the past few years. In this critical review, we will highlight the recent advances in the design, development and application of biomimetic MOMs, and illustrate how the incorporation of biological components into MOMs could further enrich their structural and functional diversity. More importantly, this review will provide a systematic overview of different methods for rational design of MOMs with biomimeticmore » features. Published by Elsevier B.V.« less

On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

PubMed

Gomez-Ramirez, Jaime; Sanz, Ricardo

2013-09-01

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem.

PubMed

Dehzangi, Abdollah; Paliwal, Kuldip; Sharma, Alok; Dehzangi, Omid; Sattar, Abdul

2013-01-01

Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches to solve this problem, it still remains as an unsolved issue for bioinformatics that demands more attention and exploration. In this study, we propose a novel feature extraction model that incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation-based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, naive Bayes, multilayer perceptron (MLP), and support vector machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks.

Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier.

PubMed

Zhang, Baochang; Yang, Yun; Chen, Chen; Yang, Linlin; Han, Jungong; Shao, Ling

2017-10-01

Human action recognition is an important yet challenging task. This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three orthogonal Cartesian planes, i.e., the frontal, side, and top planes, and thus compactly characterize the salient information of a specific action, on which texture features are calculated to represent the action. Besides this fast feature descriptor, a new multi-class boosting classifier (MBC) is also proposed to efficiently exploit different kinds of features in a unified framework for action classification. Compared with the existing boosting frameworks, we add a new multi-class constraint into the objective function, which helps to maintain a better margin distribution by maximizing the mean of margin, whereas still minimizing the variance of margin. Experiments on the MSRAction3D, MSRGesture3D, MSRActivity3D, and UTD-MHAD data sets demonstrate that the proposed system combining 3DHoTs and MBC is superior to the state of the art.

Bayesian learning for spatial filtering in an EEG-based brain-computer interface.

PubMed

Zhang, Haihong; Yang, Huijuan; Guan, Cuntai

2013-07-01

Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.

MPO4:Nd3+ (M=Ca, Gd), Luminomagnetic Nanophosphors with Optical and Magnetic Features for Multimodal Imaging Applications

NASA Astrophysics Data System (ADS)

Rightsell, Chris; Mimun, Lawrence C.; Kumar, Ajith G.; Sardar, Dhiraj K.

2015-03-01

Nanomaterials with multiple functionalities play a very important role in several high technology applications. A major area of such applications is the biomedical industry, where contrast agents with multiple imaging modalities can provide better results than conventional materials. Many of the contrast agents available now have drawbacks such as toxicity, photobleaching, low contrast, size restrictions, and overall cost of the imaging system. Rare-earth doped inorganic nanophosphors are alternatives to circumvent several of these issues, together with the added advantage of super high resolution imaging due to the excellent near infrared sensitivity of the phosphors. In addition to optical imaging features, by adding a magnetic ion such as Gd3+ at suitable lattice positions, the phosphor can be made magnetic, yielding dual imaging functionalities. In this research, we are presenting the optical and magnetic imaging features of sub-nanometer size MPO4:Nd3+ (M=Ca, Gd) phosphors for the potential application of these nanophosphors as multimodal contrast agents. Cytotoxicity, in vitro and in vivo imaging, penetration depth etc. are studied for various phosphor compositions, and optimized compositions are explored. This research was funded by the National Science Foundation Partnerships for Research and Education in Materials (NSF-PREM) Grant N0-DMR-0934218.

An Innovative Approach to Automatically Detect and Interpret Salient Spatiotemporal Features of a Numeric Field: A Case Study in Electrocardiographic Imaging

NASA Astrophysics Data System (ADS)

Ironi, Liliana; Tentoni, Stefania

2009-08-01

The last decade has witnessed major advancements in the direct application of functional imaging techniques to several clinical contexts. Unfortunately, this is not the case of Electrocardiology. As a matter of fact, epicardial maps, which can hit electrical conduction pathologies that routine surface ECG's analysis may miss, can be obtained non invasively from body surface data through mathematical model-based reconstruction methods. But, their interpretation still requires highly specialized skills that belong to few experts. The automated detection of salient patterns in the map, grounded on the existing interpretation rationale, would therefore represent a major contribution towards the clinical use of such valuable tools, whose diagnostic potential is still largely unexploited. We focus on epicardial activation isochronal maps, which convey information about the heart electric function in terms of the depolarization wavefront kinematics. An approach grounded on the integration of a Spatial Aggregation (SA) method with concepts borrowed from Computational Geometry provides a computational framework to extract, from the given activation data, a few basic features that characterize the wavefront propagation, as well as a more specific set of features that identify an important class of heart rhythm pathologies, namely reentry arrhythmias due to block of conduction.

Morphology captures diet and locomotor types in rodents.

PubMed

Verde Arregoitia, Luis D; Fisher, Diana O; Schweizer, Manuel

2017-01-01

To understand the functional meaning of morphological features, we need to relate what we know about morphology and ecology in a meaningful, quantitative framework. Closely related species usually share more phenotypic features than distant ones, but close relatives do not necessarily have the same ecologies. Rodents are the most diverse group of living mammals, with impressive ecomorphological diversification. We used museum collections and ecological literature to gather data on morphology, diet and locomotion for 208 species of rodents from different bioregions to investigate how morphological similarity and phylogenetic relatedness are associated with ecology. After considering differences in body size and shared evolutionary history, we find that unrelated species with similar ecologies can be characterized by a well-defined suite of morphological features. Our results validate the hypothesized ecological relevance of the chosen traits. These cranial, dental and external (e.g. ears) characters predicted diet and locomotion and showed consistent differences among species with different feeding and substrate use strategies. We conclude that when ecological characters do not show strong phylogenetic patterns, we cannot simply assume that close relatives are ecologically similar. Museum specimens are valuable records of species' phenotypes and with the characters proposed here, morphology can reflect functional similarity, an important component of community ecology and macroevolution.

DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

PubMed Central

Sagendorf, Jared M.

2017-01-01

Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

Evolutionary and developmental implications of asymmetric brain folding in a large primate pedigree

PubMed Central

Atkinson, Elizabeth G.; Rogers, Jeffrey; Cheverud, James M.

2016-01-01

Bilateral symmetry is a fundamental property of the vertebrate central nervous system. Local deviations from symmetry provide various types of information about the development, evolution and function of elements within the CNS, especially the cerebral hemispheres. Here, we quantify the pattern and extent of asymmetry in cortical folding within the cerebrum of Papio baboons and assess the evolutionary and developmental implications of the findings. Analyses of directional asymmetry show a population-level trend in length measurements indicating that baboons are genetically predisposed to be asymmetrical, with the right side longer than the left in the anterior cerebrum while the left side is longer than the right posteriorly. We also find a corresponding bias to display a right frontal petalia (overgrowth of the anterior pole of the cerebral cortex on the right side). By quantifying fluctuating asymmetry, we assess canalization of brain features and the susceptibility of the baboon brain to developmental perturbations. We find that features are differentially canalized depending on their ontogenetic timing. We further deduce that development of the two hemispheres is to some degree independent. This independence has important implications for the evolution of cerebral hemispheres and their separate specialization. Asymmetry is a major feature of primate brains and is characteristic of both brain structure and function. PMID:26813679

Morphologic-echocardiographic correlates of Ebstein's malformation.

PubMed

Rusconi, P G; Zuberbuhler, J R; Anderson, R H; Rigby, M L

1991-07-01

The cross-sectional echocardiographic findings were analysed retrospectively in 26 patients with Ebstein's malformation in the light of studies of autopsied specimens from different patients showing this lesion. The salient anatomical feature in diagnosis is the finding of the hinge point of the septal and mural leaflets of the valve within the inlet component of the right ventricle rather than at the atrioventricular junction. The other important feature is the nature of the distal attachment of the leaflets, particularly the anterosuperior one, which can either be in focal or linear fashion. The hinge point of the septal leaflet was noted echocardiographically to be displaced in 19 patients but, significantly, the leaflet was absent in the other seven. Also significant was that the hinge point of the mural leaflet at the crux had been visualized in only 15 of the patients. The anterosuperior leaflet had a distal linear attachment in 20 of the patients, with the anteroseptal commissure becoming a keyhole in six of these through which blood passed to the functional right ventricle. The valve remained a competent structure, even though closing at the junction of atrialized and functional components of the right ventricle rather than at the atrioventricular junction. Cross-sectional echocardiography is the technique of choice with which to display the salient morphological features of Ebstein's malformation.

LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information.

PubMed

Zahiri, Javad; Mohammad-Noori, Morteza; Ebrahimpour, Reza; Saadat, Samaneh; Bozorgmehr, Joseph H; Goldberg, Tatyana; Masoudi-Nejad, Ali

2014-12-01

Protein-protein interaction (PPI) detection is one of the central goals of functional genomics and systems biology. Knowledge about the nature of PPIs can help fill the widening gap between sequence information and functional annotations. Although experimental methods have produced valuable PPI data, they also suffer from significant limitations. Computational PPI prediction methods have attracted tremendous attentions. Despite considerable efforts, PPI prediction is still in its infancy in complex multicellular organisms such as humans. Here, we propose a novel ensemble learning method, LocFuse, which is useful in human PPI prediction. This method uses eight different genomic and proteomic features along with four types of different classifiers. The prediction performance of this classifier selection method was found to be considerably better than methods employed hitherto. This confirms the complex nature of the PPI prediction problem and also the necessity of using biological information for classifier fusion. The LocFuse is available at: http://lbb.ut.ac.ir/Download/LBBsoft/LocFuse. The results revealed that if we divide proteome space according to the cellular localization of proteins, then the utility of some classifiers in PPI prediction can be improved. Therefore, to predict the interaction for any given protein pair, we can select the most accurate classifier with regard to the cellular localization information. Based on the results, we can say that the importance of different features for PPI prediction varies between differently localized proteins; however in general, our novel features, which were extracted from position-specific scoring matrices (PSSMs), are the most important ones and the Random Forest (RF) classifier performs best in most cases. LocFuse was developed with a user-friendly graphic interface and it is freely available for Linux, Mac OSX and MS Windows operating systems. Copyright © 2014 Elsevier Inc. All rights reserved.

Hippocampal Sleep Features: Relations to Human Memory Function

PubMed Central

Ferrara, Michele; Moroni, Fabio; De Gennaro, Luigi; Nobili, Lino

2012-01-01

The recent spread of intracranial electroencephalographic (EEG) recording techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific patterns of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, non-REM sleep) in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples) that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate sleep function. PMID:22529835

Combined fluorescence, reflectance, and ground measurements of a stressed Norway spruce forest for forest damage assessment

NASA Technical Reports Server (NTRS)

Banninger, C.

1991-01-01

The detection and monitoring of stress and damage in forested areas is of utmost importance to forest managers for planning purposes. Remote sensing are the most suitable means to obtain this information. This requires that remote sensing data employed in a forest survey be properly chosen and utilized for their ability to measure canopy spectral features directly related to key tree and canopy properties that are indicators of forest health and vitality. Plant reflectance in the visible to short wave IR regions (400 to 2500 nm) provides information on its biochemical, biophysical, and morphological make up, whereas plant fluorescence in the 400 to 750 nm region is more indicative of the capacity and functioning of its photosynthetic apparatus. A measure of both these spectral properties can be used to provide an accurate assessment of stress and damage within the forest canopy. Foliar chlorophyll and nitrogen are essential biochemical constituents required for the proper functioning and maintenance of a plant's biological processes. Chlorophyll-a is the prime reactive center for photosynthesis, by which a plant converts CO2 and H2O into necessary plant products. Nitrogen forms an important component of the amino-acids, enzymes, proteins, alkaloids, and cyanogenic compounds that make up a plant, including its pigments. Both chlorophyll and nitrogen have characteristic absorption features in the visible to short wave IR region. By measuring the wavelength position and depth of these features and the fluorescence response of the foliage, the health and vitality of a canopy can be ascertained. Examples for a stressed Norway spruce forest in south-eastern Austria are presented.

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

Epigenomics and the concept of degeneracy in biological systems

PubMed Central

Mason, Paul H.; Barron, Andrew B.

2014-01-01

Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy—referring to the multiple pathways that a system recruits to achieve functional plasticity—is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability. PMID:24335757

Advanced technique for long term culture of epithelia in a continuous luminal-basal medium gradient.

PubMed

Schumacher, Karl; Strehl, Raimund; de, Vries Uwe; Minuth, Will W

2002-02-01

The majority of epithelia in our organism perform barrier functions on being exposed to different fluids at the luminal and basal sides. To simulate this natural situation under in vitro conditions for biomaterial testing and tissue engineering the epithelia have to withstand mechanical and fluid stress over a prolonged period of time. Leakage, edge damage and pressure differences in the culture system have to be avoided so that the epithelial barrier function is maintained. Besides, the environmental influences on important cell biological features such as, sealing or transport functions, have to remain upregulated and a loss of characteristics by dedifferentiation is prevented. Our aim is to expose embryonic renal collecting duct (CD) epithelia as model tissue for 14 days to fluid gradients and to monitor the development of tissue-specific features. For these experiments, cultured embryonic epithelia are placed in tissue carriers and in gradient containers, where different media are superfused at the luminal and basal sides. Epithelia growing on the tissue carriers act as a physiological barrier during the whole culture period. To avoid mechanical damage of the tissue and to suppress fluid pressure differences between the luminal and basal compartments improved transport of the medium and an elimination of unilaterally accumulated gas bubbles in the gradient container compartments by newly developed gas expander modules is introduced. By the application of these tools the yield of embryonic renal collecting duct epithelia with intact barrier function on a fragile natural support material could be increased significantly as compared to earlier experiments. Epithelia treated with a luminal NaCl load ranging from 3 to 24 mmol l were analyzed by immunohistochemical methods to determine the degree of differentiation. The tissue showed an upregulation of individual CD cell features as compared to embryonic epithelia in the neonatal kidney.

Genome-wide loss of 5-hmC is a novel epigenetic feature of Huntington's disease.

PubMed

Wang, Fengli; Yang, Yeran; Lin, Xiwen; Wang, Jiu-Qiang; Wu, Yong-Sheng; Xie, Wenjuan; Wang, Dandan; Zhu, Shu; Liao, You-Qi; Sun, Qinmiao; Yang, Yun-Gui; Luo, Huai-Rong; Guo, Caixia; Han, Chunsheng; Tang, Tie-Shan

2013-09-15

5-Hydroxymethylcytosine (5-hmC) may represent a new epigenetic modification of cytosine. While the dynamics of 5-hmC during neurodevelopment have recently been reported, little is known about its genomic distribution and function(s) in neurodegenerative diseases such as Huntington's disease (HD). We here observed a marked reduction of the 5-hmC signal in YAC128 (yeast artificial chromosome transgene with 128 CAG repeats) HD mouse brain tissues when compared with age-matched wild-type (WT) mice, suggesting a deficiency of 5-hmC reconstruction in HD brains during postnatal development. Genome-wide distribution analysis of 5-hmC further confirmed the diminishment of the 5-hmC signal in striatum and cortex in YAC128 HD mice. General genomic features of 5-hmC are highly conserved, not being affected by either disease or brain regions. Intriguingly, we have identified disease-specific (YAC128 versus WT) differentially hydroxymethylated regions (DhMRs), and found that acquisition of DhmRs in gene body is a positive epigenetic regulator for gene expression. Ingenuity pathway analysis (IPA) of genotype-specific DhMR-annotated genes revealed that alternation of a number of canonical pathways involving neuronal development/differentiation (Wnt/β-catenin/Sox pathway, axonal guidance signaling pathway) and neuronal function/survival (glutamate receptor/calcium/CREB, GABA receptor signaling, dopamine-DARPP32 feedback pathway, etc.) could be important for the onset of HD. Our results indicate that loss of the 5-hmC marker is a novel epigenetic feature in HD, and that this aberrant epigenetic regulation may impair the neurogenesis, neuronal function and survival in HD brain. Our study also opens a new avenue for HD treatment; re-establishing the native 5-hmC landscape may have the potential to slow/halt the progression of HD.

Biomaterial design for specific cellular interactions: Role of surface functionalization and geometric features

NASA Astrophysics Data System (ADS)

Kolhar, Poornima

The areas of drug delivery and tissue engineering have experienced extraordinary growth in recent years with the application of engineering principles and their potential to support and improve the field of medicine. The tremendous progress in nanotechnology and biotechnology has lead to this explosion of research and development in biomedical applications. Biomaterials can now be engineered at a nanoscale and their specific interactions with the biological tissues can be modulated. Various design parameters are being established and researched for design of drug-delivery carriers and scaffolds to be implanted into humans. Nanoparticles made from versatile biomaterial can deliver both small-molecule drugs and various classes of bio-macromolecules, such as proteins and oligonucleotides. Similarly in the field of tissue engineering, current approaches emphasize nanoscale control of cell behavior by mimicking the natural extracellular matrix (ECM) unlike, traditional scaffolds. Drug delivery and tissue engineering are closely connected fields and both of these applications require materials with exceptional physical, chemical, biological, and biomechanical properties to provide superior therapy. In the current study the surface functionalization and the geometric features of the biomaterials has been explored. In particular, a synthetic surface for culture of human embryonic stem cells has been developed, demonstrating the importance of surface functionalization in maintaining the pluripotency of hESCs. In the second study, the geometric features of the drug delivery carriers are investigated and the polymeric nanoneedles mediated cellular permeabilization and direct cytoplasmic delivery is reported. In the third study, the combined effect of surface functionalization and geometric modification of carriers for vascular targeting is enunciated. These studies illustrate how the biomaterials can be designed to achieve various cellular behaviors and control the interactions with cells in vivo .

Ecological planning of urbanized areas in the south of the Far East (Birobidzhan city as an example)

NASA Astrophysics Data System (ADS)

Kalmanova, V. B.

2018-01-01

Ecological planning of urbanized areas is an urgent demand of the time, because more than 70% of Russia’s population lives in cities. The article describes that the city’s ecological planning is an important part of the area’s organization in its development strategy. The principles and features of the urban area’s ecological organization are proposed. The basis for environmental planning is the ecological and functional zoning of urban areas. The algorithm of ecological-functional zoning is developed to optimize the quality of the urban environment. Based on it, it is possible to identify the planning structure’s features, justify anthropogenic pressure on the natural components of the urban environment, etc. The article briefly presents the possibility of using the main conditions of the ecological framework in the planning of urban areas. Considering the perspective trends of the formation and development of cities in the south of the Far East, the ecological problems caused by regional natural and anthropogenic causes (features of relief, climate, functional-planning structure) are considered. The need for environmental planning of cities in the south of the Far East is shown. The results of the ecological framework’s formation of Birobidzhan city based on its ecological and functional zoning are described. The total area of open unreformed spaces in the city is calculated to be 60.8%, which can serve as the main elements of the ecological framework and perspective reserve areas for ecological planning. The cartographic model of Birobidzhan’s ecological framework is presented, which is the result and model of this type of planning. The practical use of the proposed model will facilitate the adoption of effective management decisions aimed at stabilized development of the city.

The evolutionary history of plant T2/S-type ribonucleases

PubMed Central

Igić, Boris

2017-01-01

A growing number of T2/S-RNases are being discovered in plant genomes. Members of this protein family have a variety of known functions, but the vast majority are still uncharacterized. We present data and analyses of phylogenetic relationships among T2/S-RNases, and pay special attention to the group that contains the female component of the most widespread system of self-incompatibility in flowering plants. The returned emphasis on the initially identified component of this mechanism yields important conjectures about its evolutionary context. First, we find that the clade involved in self-rejection (class III) is found exclusively in core eudicots, while the remaining clades contain members from other vascular plants. Second, certain features, such as intron patterns, isoelectric point, and conserved amino acid regions, help differentiate S-RNases, which are necessary for expression of self-incompatibility, from other T2/S-RNase family members. Third, we devise and present a set of approaches to clarify new S-RNase candidates from existing genome assemblies. We use genomic features to identify putative functional and relictual S-loci in genomes of plants with unknown mechanisms of self-incompatibility. The widespread occurrence of possible relicts suggests that the loss of functional self-incompatibility may leave traces long after the fact, and that this manner of molecular fossil-like data could be an important source of information about the history and distribution of both RNase-based and other mechanisms of self-incompatibility. Finally, we release a public resource intended to aid the search for S-locus RNases, and help provide increasingly detailed information about their taxonomic distribution. PMID:28924504

Structural–Functional Features of the Thyrotropin Receptor: A Class A G-Protein-Coupled Receptor at Work

PubMed Central

Kleinau, Gunnar; Worth, Catherine L.; Kreuchwig, Annika; Biebermann, Heike; Marcinkowski, Patrick; Scheerer, Patrick; Krause, Gerd

2017-01-01

The thyroid-stimulating hormone receptor (TSHR) is a member of the glycoprotein hormone receptors, a sub-group of class A G-protein-coupled receptors (GPCRs). TSHR and its endogenous ligand thyrotropin (TSH) are of essential importance for growth and function of the thyroid gland and proper function of the TSH/TSHR system is pivotal for production and release of thyroid hormones. This receptor is also important with respect to pathophysiology, such as autoimmune (including ophthalmopathy) or non-autoimmune thyroid dysfunctions and cancer development. Pharmacological interventions directly targeting the TSHR should provide benefits to disease treatment compared to currently available therapies of dysfunctions associated with the TSHR or the thyroid gland. Upon TSHR activation, the molecular events conveying conformational changes from the extra- to the intracellular side of the cell across the membrane comprise reception, conversion, and amplification of the signal. These steps are highly dependent on structural features of this receptor and its intermolecular interaction partners, e.g., TSH, antibodies, small molecules, G-proteins, or arrestin. For better understanding of signal transduction, pathogenic mechanisms such as autoantibody action and mutational modifications or for developing new pharmacological strategies, it is essential to combine available structural data with functional information to generate homology models of the entire receptor. Although so far these insights are fragmental, in the past few decades essential contributions have been made to investigate in-depth the involved determinants, such as by structure determination via X-ray crystallography. This review summarizes available knowledge (as of December 2016) concerning the TSHR protein structure, associated functional aspects, and based on these insights we suggest several receptor complex models. Moreover, distinct TSHR properties will be highlighted in comparison to other class A GPCRs to understand the molecular activation mechanisms of this receptor comprehensively. Finally, limitations of current knowledge and lack of information are discussed highlighting the need for intensified efforts toward TSHR structure elucidation. PMID:28484426

Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

PubMed

Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

2015-11-01

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

[Diversity of arbuscular mycorrhizal fungi in special habitats: a review].

PubMed

Li, Su-Mei; Wang, Yin-Qiao; Liu, Run-Jin

2013-11-01

Arbuscular mycorrhizal fungi (AMF) are one of the important components in ecosystems, which not only have the diversity in genetics, species composition, and function, but also have the diversity in distribution and habitat. AMF infect plant root, form mycorrhiza, and nourish as obligate biotroph symbiont, with strong ecological adaptability. They not only distribute in forest, prairie, and farm land, but also distribute in the special habitats with less plant species diversity, such as commercial greenhouse soil, saline-alkali soil, mining pollution land, petroleum-contaminated land, pesticide-polluted soil, desert, dry land, wetland, marsh, plateau, volcanic, cooler, and arctic tundra, composing a unique community structure and playing an important irreplaceable role in the physiological and ecological functions. This paper summarized the species diversity and mycorrhizal morphological features of AMF in special habitats, aimed to provide essential information for the further studies on the AMF in these special habitats and extreme environments.

Alterations in Ca2+ Signalling via ER-Mitochondria Contact Site Remodelling in Cancer.

PubMed

Kerkhofs, Martijn; Giorgi, Carlotta; Marchi, Saverio; Seitaj, Bruno; Parys, Jan B; Pinton, Paolo; Bultynck, Geert; Bittremieux, Mart

2017-01-01

Inter-organellar contact sites establish microdomains for localised Ca 2+ -signalling events. One of these microdomains is established between the ER and the mitochondria. Importantly, the so-called mitochondria-associated ER membranes (MAMs) contain, besides structural proteins and proteins involved in lipid exchange, several Ca 2+ -transport systems, mediating efficient Ca 2+ transfer from the ER to the mitochondria. These Ca 2+ signals critically control several mitochondrial functions, thereby impacting cell metabolism, cell death and survival, proliferation and migration. Hence, the MAMs have emerged as critical signalling hubs in physiology, while their dysregulation is an important factor that drives or at least contributes to oncogenesis and tumour progression. In this book chapter, we will provide an overview of the role of the MAMs in cell function and how alterations in the MAM composition contribute to oncogenic features and behaviours.

Redox-dependent regulation of epidermal growth factor receptor signaling.

PubMed

Heppner, David E; van der Vliet, Albert

2016-08-01

Tyrosine phosphorylation-dependent cell signaling represents a unique feature of multicellular organisms, and is important in regulation of cell differentiation and specialized cell functions. Multicellular organisms also contain a diverse family of NADPH oxidases (NOXs) that have been closely linked with tyrosine kinase-based cell signaling and regulate tyrosine phosphorylation via reversible oxidation of cysteine residues that are highly conserved within many proteins involved in this signaling pathway. An example of redox-regulated tyrosine kinase signaling involves the epidermal growth factor receptor (EGFR), a widely studied receptor system with diverse functions in normal cell biology as well as pathologies associated with oxidative stress such as cancer. The purpose of this Graphical Redox Review is to highlight recently emerged concepts with respect to NOX-dependent regulation of this important signaling pathway. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Research resource: Update and extension of a glycoprotein hormone receptors web application.

PubMed

Kreuchwig, Annika; Kleinau, Gunnar; Kreuchwig, Franziska; Worth, Catherine L; Krause, Gerd

2011-04-01

The SSFA-GPHR (Sequence-Structure-Function-Analysis of Glycoprotein Hormone Receptors) database provides a comprehensive set of mutation data for the glycoprotein hormone receptors (covering the lutropin, the FSH, and the TSH receptors). Moreover, it provides a platform for comparison and investigation of these homologous receptors and helps in understanding protein malfunctions associated with several diseases. Besides extending the data set (> 1100 mutations), the database has been completely redesigned and several novel features and analysis tools have been added to the web site. These tools allow the focused extraction of semiquantitative mutant data from the GPHR subtypes and different experimental approaches. Functional and structural data of the GPHRs are now linked interactively at the web interface, and new tools for data visualization (on three-dimensional protein structures) are provided. The interpretation of functional findings is supported by receptor morphings simulating intramolecular changes during the activation process, which thus help to trace the potential function of each amino acid and provide clues to the local structural environment, including potentially relocated spatial counterpart residues. Furthermore, double and triple mutations are newly included to allow the analysis of their functional effects related to their spatial interrelationship in structures or homology models. A new important feature is the search option and data visualization by interactive and user-defined snake-plots. These new tools allow fast and easy searches for specific functional data and thereby give deeper insights in the mechanisms of hormone binding, signal transduction, and signaling regulation. The web application "Sequence-Structure-Function-Analysis of GPHRs" is accessible on the internet at http://www.ssfa-gphr.de/.

The role of corridors in conservation: Solution or bandwagon?

PubMed

Hobbs, R J

1992-11-01

Corridors are currently a major buzzword in conservation biology and landscape ecology. These linear landscape features may perform numerous functions, but it is their role in facilitating movement of fauna that has attracted much recent debate. The database supporting the idea of corridors acting as faunal conduits is remarkably small, and few studies have actually demonstrated that movement along corridors is important for any given species. Such data are very difficult to obtain, and conservation biologists are thus faced with the problem of whether to recommend the allocation of resources to corridors on the assumption that they may be important. Copyright © 1992. Published by Elsevier Ltd.

Landscape of the spliced leader trans-splicing mechanism in Schistosoma mansoni.

PubMed

Boroni, Mariana; Sammeth, Michael; Gava, Sandra Grossi; Jorge, Natasha Andressa Nogueira; Macedo, Andréa Mara; Machado, Carlos Renato; Mourão, Marina Moraes; Franco, Glória Regina

2018-03-01

Spliced leader dependent trans-splicing (SLTS) has been described as an important RNA regulatory process that occurs in different organisms, including the trematode Schistosoma mansoni. We identified more than seven thousand putative SLTS sites in the parasite, comprising genes with a wide spectrum of functional classes, which underlines the SLTS as a ubiquitous mechanism in the parasite. Also, SLTS gene expression levels span several orders of magnitude, showing that SLTS frequency is not determined by the expression level of the target gene, but by the presence of particular gene features facilitating or hindering the trans-splicing mechanism. Our in-depth investigation of SLTS events demonstrates widespread alternative trans-splicing (ATS) acceptor sites occurring in different regions along the entire gene body, highlighting another important role of SLTS generating alternative RNA isoforms in the parasite, besides the polycistron resolution. Particularly for introns where SLTS directly competes for the same acceptor substrate with cis-splicing, we identified for the first time additional and important features that might determine the type of splicing. Our study substantially extends the current knowledge of RNA processing by SLTS in S. mansoni, and provide basis for future studies on the trans-splicing mechanism in other eukaryotes.

Sockeye: A 3D Environment for Comparative Genomics

PubMed Central

Montgomery, Stephen B.; Astakhova, Tamara; Bilenky, Mikhail; Birney, Ewan; Fu, Tony; Hassel, Maik; Melsopp, Craig; Rak, Marcin; Robertson, A. Gordon; Sleumer, Monica; Siddiqui, Asim S.; Jones, Steven J.M.

2004-01-01

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization. PMID:15123592

Impact of Recent Hardware and Software Trends on High Performance Transaction Processing and Analytics

NASA Astrophysics Data System (ADS)

Mohan, C.

In this paper, I survey briefly some of the recent and emerging trends in hardware and software features which impact high performance transaction processing and data analytics applications. These features include multicore processor chips, ultra large main memories, flash storage, storage class memories, database appliances, field programmable gate arrays, transactional memory, key-value stores, and cloud computing. While some applications, e.g., Web 2.0 ones, were initially built without traditional transaction processing functionality in mind, slowly system architects and designers are beginning to address such previously ignored issues. The availability, analytics and response time requirements of these applications were initially given more importance than ACID transaction semantics and resource consumption characteristics. A project at IBM Almaden is studying the implications of phase change memory on transaction processing, in the context of a key-value store. Bitemporal data management has also become an important requirement, especially for financial applications. Power consumption and heat dissipation properties are also major considerations in the emergence of modern software and hardware architectural features. Considerations relating to ease of configuration, installation, maintenance and monitoring, and improvement of total cost of ownership have resulted in database appliances becoming very popular. The MapReduce paradigm is now quite popular for large scale data analysis, in spite of the major inefficiencies associated with it.

Identification of landscape features influencing gene flow: How useful are habitat selection models?

USGS Publications Warehouse

Roffler, Gretchen H.; Schwartz, Michael K.; Pilgrim, Kristy L.; Talbot, Sandra L.; Sage, Kevin; Adams, Layne G.; Luikart, Gordon

2016-01-01

Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider explicit assumptions and spatial scales of measurement. We calculated pairwise genetic distance among 301 Dall's sheep (Ovis dalli dalli) in southcentral Alaska using an intensive noninvasive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important during summer (rugged terrain, mid-range elevation) were not influential to effective dispersal. This work underscores that consideration of both habitat selection and landscape genetics models may be useful in developing management strategies to both meet the immediate survival of a species and allow for long-term genetic connectivity.

Cell–material interactions on biphasic polyurethane matrix

PubMed Central

Dicesare, Patrick; Fox, Wade M.; Hill, Michael J.; Krishnan, G. Rajesh; Yang, Shuying; Sarkar, Debanjan

2013-01-01

Cell–matrix interaction is a key regulator for controlling stem cell fate in regenerative tissue engineering. These interactions are induced and controlled by the nanoscale features of extracellular matrix and are mimicked on synthetic matrices to control cell structure and functions. Recent studies have shown that nanostructured matrices can modulate stem cell behavior and exert specific role in tissue regeneration. In this study, we have demonstrated that nanostructured phase morphology of synthetic matrix can control adhesion, proliferation, organization and migration of human mesenchymal stem cells (MSCs). Nanostructured biodegradable polyurethanes (PU) with segmental composition exhibit biphasic morphology at nanoscale dimensions and can control cellular features of MSCs. Biodegradable PU with polyester soft segment and hard segment composed of aliphatic diisocyanates and dipeptide chain extender were designed to examine the effect polyurethane phase morphology. By altering the polyurethane composition, morphological architecture of PU was modulated and its effect was examined on MSC. Results show that MSCs can sense the nanoscale morphology of biphasic polyurethane matrix to exhibit distinct cellular features and, thus, signifies the relevance of matrix phase morphology. The role of nanostructured phases of a synthetic matrix in controlling cell–matrix interaction provides important insights for regulation of cell behavior on synthetic matrix and, therefore, is an important tool for engineering tissue regeneration. PMID:23255285

Patient-related constraints on get- and be-passive uses in English: evidence from paraphrasing

PubMed Central

Thompson, Dominic; Ling, S. P.; Myachykov, Andriy; Ferreira, Fernanda; Scheepers, Christoph

2013-01-01

In English, transitive events can be described in various ways. The main possibilities are active-voice and passive-voice, which are assumed to have distinct semantic and pragmatic functions. Within the passive, there are two further options, namely be-passive or get-passive. While these two forms are generally understood to differ, there is little agreement on precisely how and why. The passive Patient is frequently cited as playing a role, though again agreement on the specifics is rare. Here we present three paraphrasing experiments investigating Patient-related constraints on the selection of active vs. passive voice, and be- vs. get-passive, respectively. Participants either had to re-tell short stories in their own words (Experiments 1 and 2) or had to answer specific questions about the Patient in those short stories (Experiment 3). We found that a given Agent in a story promotes the use of active-voice, while a given Patient promotes be-passives specifically. Meanwhile, get-passive use increases when the Patient is marked as important. We argue that the three forms of transitive description are functionally and semantically distinct, and can be arranged along two dimensions: Patient Prominence and Patient Importance. We claim that active-voice has a near-complementary relationship with the be-passive, driven by which protagonist is given. Since both get and be are passive, they share the features of a Patient-subject and an optional Agent by-phrase; however, get specifically responds to a Patient being marked as important. Each of these descriptions has its own set of features that differentiate it from the others. PMID:24273527

A feature refinement approach for statistical interior CT reconstruction

NASA Astrophysics Data System (ADS)

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-01

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

A feature refinement approach for statistical interior CT reconstruction.

PubMed

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-21

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

The clinical and cultural factors in classifying low back pain patients within Greece: a qualitative exploration of Greek health professionals.

PubMed

Billis, Evdokia V; McCarthy, Christopher J; Stathopoulos, Ioannis; Kapreli, Eleni; Pantzou, Paulina; Oldham, Jacqueline A

2007-06-01

Identifying homogenous subgroups of low back pain (LBP) patients is considered a priority in musculoskeletal rehabilitation and is believed to enhance clinical outcomes. In order to achieve this, the specific features of each subgroup need to be identified. The aim of this study was to develop a list of clinical and cultural features that are included in the assessment of LBP patients in Greece, among health professionals. This 'list' will be, utilized in a clinical study for developing LBP subgroups. Three focus groups were conducted, each one comprising health professionals with homogenous characteristics and all coordinated by a single moderator. There were: 11 physiotherapists (PTs) with clinical experience in LBP patients, seven PTs specialized in LBP management, and five doctors with a particular spinal interest. The focus of discussions was to develop a list of clinical and cultural features that were important in the examination of LBP. Content analysis was performed by two researchers. Clinicians and postgraduates developed five categories within the History (Present Symptoms, History of Symptoms, Function, Psychosocial, Medical History) and six categories within the Physical Examination (Observation, Neurological Examination, Active and Passive Movements, Muscle Features and Palpation). The doctors identified four categories in History (Symptomatology, Function, Psychosocial, Medical History) and an additional in Physical Examination (Special Tests). All groups identified three cultural categories; Attitudes of Health Professionals, Patients' Attitudes and Health System influences. An extensive Greek 'list' of clinical and cultural features was developed from the groups' analysis. Although similarities existed in most categories, there were several differences across the three focus groups which will be discussed.

National Airspace System Delay Estimation Using Weather Weighted Traffic Counts

NASA Technical Reports Server (NTRS)

Chatterji, Gano B.; Sridhar, Banavar

2004-01-01

Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.

Strategic Functionalization of Single Walled Carbon Nanotubes to Manipulate Their Electronic and Optical Properties

NASA Astrophysics Data System (ADS)

Gifford, Brendan Joel

Single-walled carbon nanotubes (SWCNTs) are unique materials that exhibit chirality-specific properties due to their one-dimensional confinement. As a result, they are explored for a wide range of applications including single-photon sources in communications devices. Despite progress in this area, SWCNTs still suffer from a relatively narrow range of energies of emission features that fall short of the 1500 nm desired for long-distance lossless data transfer. One approach that is frequently used to resolve this involves chemical functionalization with aryl groups. However, this approach is met with a number of fundamental issues. First, chirality-specific SWCNTs must be acquired for subsequent functionalization. Synthesis of such samples has thus far eluded experimental efforts. As such, post-synthetic non-covalent functionalization is required to break bundles and create disperse SWCNTs that can undergo further separation, processing, and functionalization. Second, a number of low-energy emission features are introduced upon functionalization across a 200 nm range. The origin of such diverse emission features remains unknown. The research presented here focuses on computationally addressing these issues. A series of polyfluorene polymers possessing sidechains of varying length are explored using molecular mechanics to determine the impact of alkyl sidechains on SWCNT-conjugated polymer interaction strength and morphology. Additionally, density functional theory (DFT) and linear-response time-dependent DFT (TDDFT) are used to explore the effect of functionalization on emission features. A prerequisite to these calculations involves constructing finite-length SWCNT systems with similar electronic structure to their infinite counterparts: a methodological approach for the formation of such systems is presented. The optical features for aryl-functionalized SWCNTs are then explored. It is shown that the predominant effect on the energies of emission features involves the configuration of functionalization, with the identity of the functional group only playing a minor role. While the qualitative effect of such functionalization is determined, a quantitative comparison to experiment requires correction for several sources of computational error. A model to correct for such effects is also developed. This research not only explains the origin of the multiple emission features in functionalized SWCNTs for the first time but also lays the groundwork for their further computational exploration.

Computer/gaming station use in youth: Correlations among use, addiction and functional impairment

PubMed Central

Baer, Susan; Saran, Kelly; Green, David A

2012-01-01

OBJECTIVE: Computer/gaming station use is ubiquitous in the lives of youth today. Overuse is a concern, but it remains unclear whether problems arise from addictive patterns of use or simply excessive time spent on use. The goal of the present study was to evaluate computer/gaming station use in youth and to examine the relationship between amounts of use, addictive features of use and functional impairment. METHOD: A total of 110 subjects (11 to 17 years of age) from local schools participated. Time spent on television, video gaming and non-gaming recreational computer activities was measured. Addictive features of computer/gaming station use were ascertained, along with emotional/behavioural functioning. Multiple linear regressions were used to understand how youth functioning varied with time of use and addictive features of use. RESULTS: Mean (± SD) total screen time was 4.5±2.4 h/day. Addictive features of use were consistently correlated with functional impairment across multiple measures and informants, whereas time of use, after controlling for addiction, was not. CONCLUSIONS: Youth are spending many hours each day in front of screens. In the absence of addictive features of computer/gaming station use, time spent is not correlated with problems; however, youth with addictive features of use show evidence of poor emotional/ behavioural functioning. PMID:24082802

The IRM fluxgate magnetometer

NASA Technical Reports Server (NTRS)

Luehr, H.; Kloecker, N.; Oelschlaegel, W.; Haeusler, B.; Acuna, M.

1985-01-01

This report describes the three-axis fluxgate magnetometer instrument on board the AMPTE IRM spacecraft. Important features of the instrument are its wide dynamic range (0.1-60,000 nT), a high resolution (16-bit analog to digital conversion) and the capability to operate automatically or via telecommand in two gain states. In addition, the wave activity is monitored in all three components up to 50 Hz. Inflight checkout proved the nominal functioning of the instrument in all modes.