Attention improves encoding of task-relevant features in the human visual cortex

Science.gov (United States)

Jehee, Janneke F.M.; Brady, Devin K.; Tong, Frank

2011-01-01

When spatial attention is directed towards a particular stimulus, increased activity is commonly observed in corresponding locations of the visual cortex. Does this attentional increase in activity indicate improved processing of all features contained within the attended stimulus, or might spatial attention selectively enhance the features relevant to the observer’s task? We used fMRI decoding methods to measure the strength of orientation-selective activity patterns in the human visual cortex while subjects performed either an orientation or contrast discrimination task, involving one of two laterally presented gratings. Greater overall BOLD activation with spatial attention was observed in areas V1-V4 for both tasks. However, multivariate pattern analysis revealed that orientation-selective responses were enhanced by attention only when orientation was the task-relevant feature, and not when the grating’s contrast had to be attended. In a second experiment, observers discriminated the orientation or color of a specific lateral grating. Here, orientation-selective responses were enhanced in both tasks but color-selective responses were enhanced only when color was task-relevant. In both experiments, task-specific enhancement of feature-selective activity was not confined to the attended stimulus location, but instead spread to other locations in the visual field, suggesting the concurrent involvement of a global feature-based attentional mechanism. These results suggest that attention can be remarkably selective in its ability to enhance particular task-relevant features, and further reveal that increases in overall BOLD amplitude are not necessarily accompanied by improved processing of stimulus information. PMID:21632942

EOG feature relevance determination for microsleep detection

OpenAIRE

Golz Martin; Wollner Sebastian; Sommer David; Schnieder Sebastian

2017-01-01

Automatic relevance determination (ARD) was applied to two-channel EOG recordings for microsleep event (MSE) recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC) and logarithmic power spectral densities (PSD) averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ) was used as ARD...

The Effects of Goal Relevance and Perceptual Features on Emotional Items and Associative Memory

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Wei B. Mao

2017-07-01

Full Text Available Showing an emotional item in a neutral background scene often leads to enhanced memory for the emotional item and impaired associative memory for background details. Meanwhile, both top–down goal relevance and bottom–up perceptual features played important roles in memory binding. We conducted two experiments and aimed to further examine the effects of goal relevance and perceptual features on emotional items and associative memory. By manipulating goal relevance (asking participants to categorize only each item image as living or non-living or to categorize each whole composite picture consisted of item image and background scene as natural scene or manufactured scene and perceptual features (controlling visual contrast and visual familiarity in two experiments, we found that both high goal relevance and salient perceptual features (high salience of items vs. high familiarity of items could promote emotional item memory, but they had different effects on associative memory for emotional items and neutral backgrounds. Specifically, high goal relevance and high perceptual-salience of items could jointly impair the associative memory for emotional items and neutral backgrounds, while the effect of item familiarity on associative memory for emotional items would be modulated by goal relevance. High familiarity of items could increase associative memory for negative items and neutral backgrounds only in the low goal relevance condition. These findings suggest the effect of emotion on associative memory is not only related to attentional capture elicited by emotion, but also can be affected by goal relevance and perceptual features of stimulus.

'Fish matters': the relevance of fish skin biology to investigative dermatology.

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Rakers, Sebastian; Gebert, Marina; Uppalapati, Sai; Meyer, Wilfried; Maderson, Paul; Sell, Anne F; Kruse, Charli; Paus, Ralf

2010-04-01

Fish skin is a multi-purpose tissue that serves numerous vital functions including chemical and physical protection, sensory activity, behavioural purposes or hormone metabolism. Further, it is an important first-line defense system against pathogens, as fish are continuously exposed to multiple microbial challenges in their aquatic habitat. Fish skin excels in highly developed antimicrobial features, many of which have been preserved throughout evolution, and infection defense principles employed by piscine skin are still operative in human skin. This review argues that it is both rewarding and important for investigative dermatologists to revive their interest in fish skin biology, as it provides insights into numerous fundamental issues that are of major relevance to mammalian skin. The basic molecular insights provided by zebrafish in vivo-genomics for genetic, regeneration and melanoma research, the complex antimicrobial defense systems of fish skin and the molecular controls of melanocyte stem cells are just some of the fascinating examples that illustrate the multiple potential uses of fish skin models in investigative dermatology. We synthesize the essentials of fish skin biology and highlight selected aspects that are of particular comparative interest to basic and clinically applied human skin research.

Making developmental biology relevant to undergraduates in an era of economic rationalism in Australia.

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Key, Brian; Nurcombe, Victor

2003-01-01

This report describes the road map we followed at our university to accommodate three main factors: financial pressure within the university system; desire to enhance the learning experience of undergraduates; and motivation to increase the prominence of the discipline of developmental biology in our university. We engineered a novel, multi-year undergraduate developmental biology program which was "student-oriented," ensuring that students were continually exposed to the underlying principles and philosophy of this discipline throughout their undergraduate career. Among its key features are introductory lectures in core courses in the first year, which emphasize the relevance of developmental biology to tissue engineering, reproductive medicine, therapeutic approaches in medicine, agriculture and aquaculture. State-of-the-art animated computer graphics and images of high visual impact are also used. In addition, students are streamed into the developmental biology track in the second year, using courses like human embryology and courses shared with cell biology, which include practicals based on modern experimental approaches. Finally, fully dedicated third-year courses in developmental biology are undertaken in conjunction with stand-alone practical courses where students experiencefirst-hand work in a research laboratory. Our philosophy is a "cradle-to-grave" approach to the education of undergraduates so as to prepare highly motivated, enthusiastic and well-educated developmental biologists for entry into graduate programs and ultimately post-doctoral research.

Feature relevance assessment for the semantic interpretation of 3D point cloud data

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M. Weinmann

2013-10-01

Full Text Available The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

The LAILAPS search engine: a feature model for relevance ranking in life science databases.

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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.

Feature-selective Attention in Frontoparietal Cortex: Multivoxel Codes Adjust to Prioritize Task-relevant Information.

Science.gov (United States)

Jackson, Jade; Rich, Anina N; Williams, Mark A; Woolgar, Alexandra

2017-02-01

Human cognition is characterized by astounding flexibility, enabling us to select appropriate information according to the objectives of our current task. A circuit of frontal and parietal brain regions, often referred to as the frontoparietal attention network or multiple-demand (MD) regions, are believed to play a fundamental role in this flexibility. There is evidence that these regions dynamically adjust their responses to selectively process information that is currently relevant for behavior, as proposed by the "adaptive coding hypothesis" [Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820-829, 2001]. Could this provide a neural mechanism for feature-selective attention, the process by which we preferentially process one feature of a stimulus over another? We used multivariate pattern analysis of fMRI data during a perceptually challenging categorization task to investigate whether the representation of visual object features in the MD regions flexibly adjusts according to task relevance. Participants were trained to categorize visually similar novel objects along two orthogonal stimulus dimensions (length/orientation) and performed short alternating blocks in which only one of these dimensions was relevant. We found that multivoxel patterns of activation in the MD regions encoded the task-relevant distinctions more strongly than the task-irrelevant distinctions: The MD regions discriminated between stimuli of different lengths when length was relevant and between the same objects according to orientation when orientation was relevant. The data suggest a flexible neural system that adjusts its representation of visual objects to preferentially encode stimulus features that are currently relevant for behavior, providing a neural mechanism for feature-selective attention.

Intraductal papillary mucinous neoplasms of the pancreas: reporting clinically relevant features.

Science.gov (United States)

Del Chiaro, Marco; Verbeke, Caroline

2017-05-01

Intraductal papillary mucinous neoplasms (IPMNs) of the pancreas can exhibit a wide spectrum of macroscopic and microscopic appearances. This not only causes occasional difficulties for the reporting pathologist in distinguishing these tumours from other lesions, but is also relevant clinically. As evidence accumulates, it becomes clear that multiple macroscopic and histological features of these neoplasms are relevant to the risk for malignant transformation and, consequently, of prime importance for clinical patient management. The need for detailed reporting is therefore increasing. This review discusses the panoply of gross and microscopic features of IPMN as well as the recommendations from recent consensus meetings regarding the pathology reporting on this tumour entity. © 2016 John Wiley & Sons Ltd.

Hands-on-Entropy, Energy Balance with Biological Relevance

Science.gov (United States)

Reeves, Mark

2015-03-01

Entropy changes underlie the physics that dominates biological interactions. Indeed, introductory biology courses often begin with an exploration of the qualities of water that are important to living systems. However, one idea that is not explicitly addressed in most introductory physics or biology textbooks is important contribution of the entropy in driving fundamental biological processes towards equilibrium. From diffusion to cell-membrane formation, to electrostatic binding in protein folding, to the functioning of nerve cells, entropic effects often act to counterbalance deterministic forces such as electrostatic attraction and in so doing, allow for effective molecular signaling. A small group of biology, biophysics and computer science faculty have worked together for the past five years to develop curricular modules (based on SCALEUP pedagogy). This has enabled students to create models of stochastic and deterministic processes. Our students are first-year engineering and science students in the calculus-based physics course and they are not expected to know biology beyond the high-school level. In our class, they learn to reduce complex biological processes and structures in order model them mathematically to account for both deterministic and probabilistic processes. The students test these models in simulations and in laboratory experiments that are biologically relevant such as diffusion, ionic transport, and ligand-receptor binding. Moreover, the students confront random forces and traditional forces in problems, simulations, and in laboratory exploration throughout the year-long course as they move from traditional kinematics through thermodynamics to electrostatic interactions. This talk will present a number of these exercises, with particular focus on the hands-on experiments done by the students, and will give examples of the tangible material that our students work with throughout the two-semester sequence of their course on introductory

Linking structural features of protein complexes and biological function.

Science.gov (United States)

Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

2015-09-01

Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. © 2015 The Protein Society.

Comparison of the perceived relevance of oral biology reported by students and interns of a Pakistani dental college.

Science.gov (United States)

Farooq, I; Ali, S

2014-11-01

The purpose of this study was to analyse and compare the perceived relevance of oral biology with dentistry as reported by dental students and interns and to investigate the most popular teaching approach and learning resource. A questionnaire aiming to ask about the relevance of oral biology to dentistry, most popular teaching method and learning resource was utilised in this study. Study groups encompassed second-year dental students who had completed their course and dental interns. The data were obtained and analysed statistically. The overall response rate for both groups was 60%. Both groups reported high relevance of oral biology to dentistry. Perception of dental interns regarding the relevance of oral biology to dentistry was higher than that of students. Both groups identified student presentations as the most important teaching method. Amongst the most important learning resources, textbooks were considered most imperative by interns, whereas lecture handouts received the highest importance score by students. Dental students and interns considered oral biology to be relevant to dentistry, although greater relevance was reported by interns. Year-wise advancement in dental education and training improves the perception of the students about the relevance of oral biology to dentistry. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The complexity of DNA damage: relevance to biological consequences

International Nuclear Information System (INIS)

Ward, J.F.

1994-01-01

Ionizing radiation causes both singly and multiply damaged sites in DNA when the range of radical migration is limited by the presence of hydroxyl radical scavengers (e.g. within cells). Multiply damaged sites are considered to be more biologically relevant because of the challenges they present to cellular repair mechanisms. These sites occur in the form of DNA double-strand breaks (dsb) but also as other multiple damages that can be converted to dsb during attempted repair. The presence of a dsb can lead to loss of base sequence information and/or can permit the two ends of a break to separate and rejoin with the wrong partner. (Multiply damaged sites may also be the biologically relevant type of damage caused by other agents, such as UVA, B and/or C light, and some antitumour antibiotics). The quantitative data available from radiation studies of DNA are shown to support the proposed mechanisms for the production of complex damage in cellular DNA, i.e. via scavengable and non-scavengable mechanisms. The yields of complex damages can in turn be used to support the conclusion that cellular mutations are a consequence of the presence of these damages within a gene. (Author)

About the composition of self-relevance: Conjunctions not features are bound to the self.

Science.gov (United States)

Schäfer, Sarah; Frings, Christian; Wentura, Dirk

2016-06-01

Sui and colleagues (Journal of Experimental Psychology: Human Perception and Performance, 38, 1105-1117, 2012) introduced a matching paradigm to investigate prioritized processing of instructed self-relevance. They arbitrarily assigned simple geometric shapes to the participant and two other persons. Subsequently, the task was to judge whether label-shape pairings matched or not. The authors found a remarkable self-prioritization effect, that is, for matching self-related trials verification was very fast and accurate in comparison to the non-matching conditions. We analyzed whether single features or feature conjunctions are tagged to the self. In particular, we assigned colored shapes to the labels and included partial-matching trials (i.e., trials in which only one feature matched the label, whereas the other feature did not match the label). If single features are tagged to the self, partial matches would result in interference, whereas they should elicit the same data pattern as non-matching trials if only feature conjunctions are tagged to the self. Our data suggest the latter; only feature conjunctions are tagged to the self and are processed in a prioritized manner. This result emphasizes the functionality of self-relevance as a selection mechanism.

A biologically relevant method for considering patterns of oceanic retention in the Southern Ocean

Science.gov (United States)

Mori, Mao; Corney, Stuart P.; Melbourne-Thomas, Jessica; Klocker, Andreas; Sumner, Michael; Constable, Andrew

2017-12-01

Many marine species have planktonic forms - either during a larval stage or throughout their lifecycle - that move passively or are strongly influenced by ocean currents. Understanding these patterns of movement is important for informing marine ecosystem management and for understanding ecological processes generally. Retention of biological particles in a particular area due to ocean currents has received less attention than transport pathways, particularly for the Southern Ocean. We present a method for modelling retention time, based on the half-life for particles in a particular region, that is relevant for biological processes. This method uses geostrophic velocities at the ocean surface, derived from 23 years of satellite altimetry data (1993-2016), to simulate the advection of passive particles during the Southern Hemisphere summer season (from December to March). We assess spatial patterns in the retention time of passive particles and evaluate the processes affecting these patterns for the Indian sector of the Southern Ocean. Our results indicate that the distribution of retention time is related to bathymetric features and the resulting ocean dynamics. Our analysis also reveals a moderate level of consistency between spatial patterns of retention time and observations of Antarctic krill (Euphausia superba) distribution.

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli

OpenAIRE

Sakaki, Michiko; Niki, N.; Mather, M.

2012-01-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for bio...

Sparse Bayesian classification and feature selection for biological expression data with high correlations.

Directory of Open Access Journals (Sweden)

Xian Yang

Full Text Available Classification models built on biological expression data are increasingly used to predict distinct disease subtypes. Selected features that separate sample groups can be the candidates of biomarkers, helping us to discover biological functions/pathways. However, three challenges are associated with building a robust classification and feature selection model: 1 the number of significant biomarkers is much smaller than that of measured features for which the search will be exhaustive; 2 current biological expression data are big in both sample size and feature size which will worsen the scalability of any search algorithms; and 3 expression profiles of certain features are typically highly correlated which may prevent to distinguish the predominant features. Unfortunately, most of the existing algorithms are partially addressing part of these challenges but not as a whole. In this paper, we propose a unified framework to address the above challenges. The classification and feature selection problem is first formulated as a nonconvex optimisation problem. Then the problem is relaxed and solved iteratively by a sequence of convex optimisation procedures which can be distributed computed and therefore allows the efficient implementation on advanced infrastructures. To illustrate the competence of our method over others, we first analyse a randomly generated simulation dataset under various conditions. We then analyse a real gene expression dataset on embryonal tumour. Further downstream analysis, such as functional annotation and pathway analysis, are performed on the selected features which elucidate several biological findings.

On the relevance of spectral features for instrument classification

DEFF Research Database (Denmark)

Nielsen, Andreas Brinch; Sigurdsson, Sigurdur; Hansen, Lars Kai

2007-01-01

Automatic knowledge extraction from music signals is a key component for most music organization and music information retrieval systems. In this paper, we consider the problem of instrument modelling and instrument classification from the rough audio data. Existing systems for automatic instrument...... classification operate normally on a relatively large number of features, from which those related to the spectrum of the audio signal are particularly relevant. In this paper, we confront two different models about the spectral characterization of musical instruments. The first assumes a constant envelope...

Relevance feature selection of modal frequency-ambient condition pattern recognition in structural health assessment for reinforced concrete buildings

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He-Qing Mu

2016-08-01

Full Text Available Modal frequency is an important indicator for structural health assessment. Previous studies have shown that this indicator is substantially affected by the fluctuation of ambient conditions, such as temperature and humidity. Therefore, recognizing the pattern between modal frequency and ambient conditions is necessary for reliable long-term structural health assessment. In this article, a novel machine-learning algorithm is proposed to automatically select relevance features in modal frequency-ambient condition pattern recognition based on structural dynamic response and ambient condition measurement. In contrast to the traditional feature selection approaches by examining a large number of combinations of extracted features, the proposed algorithm conducts continuous relevance feature selection by introducing a sophisticated hyperparameterization on the weight parameter vector controlling the relevancy of different features in the prediction model. The proposed algorithm is then utilized for structural health assessment for a reinforced concrete building based on 1-year daily measurements. It turns out that the optimal model class including the relevance features for each vibrational mode is capable to capture the pattern between the corresponding modal frequency and the ambient conditions.

Correlativity study on MRI morphologic features, pathology, and molecular biology of breast cancer

International Nuclear Information System (INIS)

Chen Rong; Gong Shuigen; Zhang Weiguo; Chen Jinhua; He Shuangwu; Liu Baohua; Li Zengpeng

2004-01-01

Objective: To investigate the correlation among MRI morphologic features, pathology, and molecular biology of breast cancer. Methods: MR scanning was performed in 78 patients with breast cancer before operation and MRI morphologic features of breast cancer were analyzed. The mastectomy specimens of the breast neoplasm were stained with immunohistochemistry, and the expression of estrogen receptor (ER), progesterone receptor (PR), C-erbB-2, p53, and the distribution of microvessel density (MVD) was measured. The pathologic results were compared with MRI features. Results: Among the 80 breast cancers, ER positive expression was positively correlated with the spiculate margin of breast cancer (P 0.05). Among the 41 breast cancers with dynamic MR scans, there was positive correlation between the spatial distribution of contrast agent and MVD (P<0.01). Conclusion: There exists some correlation among MRI morphologic features, pathology, and molecular biology factors in breast cancer to certain extent. The biologic behavior and prognosis of the breast cancer can be assessed according to MRI features

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions.

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Pannese, Alessia; Grandjean, Didier; Frühholz, Sascha

2016-12-01

Discriminating between auditory signals of different affective value is critical to successful social interaction. It is commonly held that acoustic decoding of such signals occurs in the auditory system, whereas affective decoding occurs in the amygdala. However, given that the amygdala receives direct subcortical projections that bypass the auditory cortex, it is possible that some acoustic decoding occurs in the amygdala as well, when the acoustic features are relevant for affective discrimination. We tested this hypothesis by combining functional neuroimaging with the neurophysiological phenomena of repetition suppression (RS) and repetition enhancement (RE) in human listeners. Our results show that both amygdala and auditory cortex responded differentially to physical voice features, suggesting that the amygdala and auditory cortex decode the affective quality of the voice not only by processing the emotional content from previously processed acoustic features, but also by processing the acoustic features themselves, when these are relevant to the identification of the voice's affective value. Specifically, we found that the auditory cortex is sensitive to spectral high-frequency voice cues when discriminating vocal anger from vocal fear and joy, whereas the amygdala is sensitive to vocal pitch when discriminating between negative vocal emotions (i.e., anger and fear). Vocal pitch is an instantaneously recognized voice feature, which is potentially transferred to the amygdala by direct subcortical projections. These results together provide evidence that, besides the auditory cortex, the amygdala too processes acoustic information, when this is relevant to the discrimination of auditory emotions. Copyright © 2016 Elsevier Ltd. All rights reserved.

A study of ruthenium complexes of some biologically relevant a-N ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Chemical Sciences; Volume 112; Issue 3. A study of ruthenium complexes of some biologically relevant ∙ -N-heterocyclic ... Author Affiliations. P Sengupta1 S Ghosh1. Department of Inorganic Chemistry, Indian Association for the Cultivation of Science, Jadavpur, Calcutta 700 032, India ...

Acoustic fine structure may encode biologically relevant information for zebra finches.

Science.gov (United States)

Prior, Nora H; Smith, Edward; Lawson, Shelby; Ball, Gregory F; Dooling, Robert J

2018-04-18

The ability to discriminate changes in the fine structure of complex sounds is well developed in birds. However, the precise limit of this discrimination ability and how it is used in the context of natural communication remains unclear. Here we describe natural variability in acoustic fine structure of male and female zebra finch calls. Results from psychoacoustic experiments demonstrate that zebra finches are able to discriminate extremely small differences in fine structure, which are on the order of the variation in acoustic fine structure that is present in their vocal signals. Results from signal analysis methods also suggest that acoustic fine structure may carry information that distinguishes between biologically relevant categories including sex, call type and individual identity. Combined, our results are consistent with the hypothesis that zebra finches can encode biologically relevant information within the fine structure of their calls. This study provides a foundation for our understanding of how acoustic fine structure may be involved in animal communication.

Dilution thermodynamics of the biologically relevant cation mixtures

International Nuclear Information System (INIS)

Kaczyński, Marek; Borowik, Tomasz; Przybyło, Magda; Langner, Marek

2014-01-01

Graphical abstract: - Highlights: • Dilution energetics of Ca 2+ can be altered by the aqueous phase ionic composition. • Dissipated heat upon Ca 2+ dilution is drastically reduced in the K + presence. • Reduction of the enthalpy change upon Ca 2+ dilution is K + concentration dependent. • The cooperativity of Ca 2+ hydration might be of great biological relevance providing a thermodynamic argument for the specific ionic composition of the intracellular environment. - Abstract: The ionic composition of intracellular space is rigorously controlled by a variety of processes consuming large quantities of energy. Since the energetic efficiency is an important evolutional criterion, therefore the ion fluxes within the cell should be optimized with respect to the accompanying energy consumption. In the paper we present the experimental evidence that the dilution enthalpies of the biologically relevant ions; i.e. calcium and magnesium depend on the presence of monovalent cations; i.e. sodium and potassium. The heat flow generated during the dilution of ionic mixtures was measured with the isothermal titration calorimetry. When calcium was diluted together with potassium the dilution enthalpy was drastically reduced as the function of the potassium concentration present in the solution. No such effect was observed when the potassium ions were substituted with sodium ones. When the dilution of magnesium was investigated the dependence of the dilution enthalpy on the accompanying monovalent cation was much weaker. In order to interpret experimental evidences the ionic cluster formation is postulated. The specific organization of such cluster should depend on ions charges, sizes and organization of the hydration layers

Simulation on scattering features of biological tissue based on generated refractive-index model

International Nuclear Information System (INIS)

Wang Baoyong; Ding Zhihua

2011-01-01

Important information on morphology of biological tissue can be deduced from elastic scattering spectra, and their analyses are based on the known refractive-index model of tissue. In this paper, a new numerical refractive-index model is put forward, and its scattering properties are intensively studied. Spectral decomposition [1] is a widely used method to generate random medium in geology, but it is never used in biology. Biological tissue is different from geology in the sense of random medium. Autocorrelation function describe almost all of features in geology, but biological tissue is not as random as geology, its structure is regular in the sense of fractal geometry [2] , and fractal dimension can be used to describe its regularity under random. Firstly scattering theories of this fractal media are reviewed. Secondly the detailed generation process of refractive-index is presented. Finally the scattering features are simulated in FDTD (Finite Difference Time Domain) Solutions software. From the simulation results, we find that autocorrelation length and fractal dimension controls scattering feature of biological tissue.

Feature selection for splice site prediction: A new method using EDA-based feature ranking

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Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

Clinical relevance and biology of circulating tumor cells

Science.gov (United States)

2011-01-01

Most breast cancer patients die due to metastases, and the early onset of this multistep process is usually missed by current tumor staging modalities. Therefore, ultrasensitive techniques have been developed to enable the enrichment, detection, isolation and characterization of disseminated tumor cells in bone marrow and circulating tumor cells in the peripheral blood of cancer patients. There is increasing evidence that the presence of these cells is associated with an unfavorable prognosis related to metastatic progression in the bone and other organs. This review focuses on investigations regarding the biology and clinical relevance of circulating tumor cells in breast cancer. PMID:22114869

Discriminative topological features reveal biological network mechanisms

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Levovitz Chaya

2004-11-01

Full Text Available Abstract Background Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and sociological origin. In most cases the success of a model has been evaluated by how well it reproduces a few key features of the real-world data, such as degree distributions, mean geodesic lengths, and clustering coefficients. Often pairs of models can reproduce these features with indistinguishable fidelity despite being generated by vastly different mechanisms. In such cases, these few target features are insufficient to distinguish which of the different models best describes real world networks of interest; moreover, it is not clear a priori that any of the presently-existing algorithms for network generation offers a predictive description of the networks inspiring them. Results We present a method to assess systematically which of a set of proposed network generation algorithms gives the most accurate description of a given biological network. To derive discriminative classifiers, we construct a mapping from the set of all graphs to a high-dimensional (in principle infinite-dimensional "word space". This map defines an input space for classification schemes which allow us to state unambiguously which models are most descriptive of a given network of interest. Our training sets include networks generated from 17 models either drawn from the literature or introduced in this work. We show that different duplication-mutation schemes best describe the E. coli genetic network, the S. cerevisiae protein interaction network, and the C. elegans neuronal network, out of a set of network models including a linear preferential attachment model and a small-world model. Conclusions Our method is a first step towards systematizing network models and assessing their predictability, and we anticipate its usefulness for a number of communities.

Study about the relevance and the disclosure of biological assets of listed companies in BM&FBOVESPA

Directory of Open Access Journals (Sweden)

Luciana Holtz

2013-08-01

Full Text Available The main objective this article is to verify that the information content of biological assets disclosed in the financial statements are relevant and, the secondary objective perform content analysis of the notes verifying the compliance of information supplied by entities with CPC 29. The study sample was composed of publicly traded stock companies listed on the BM & FBOVESPA with data for the year 2010 and 2011. The empirical tests were conducted applying relevance models, using observations of 347 active companies characterizing a study model pooled ordinary least squares – POLS, including companies that have reported biological assets into account specific .The companies that had values of biological assets posted have had analyzed explanatory notes referring to this account. The results provide empirical evidence that the information content of biological assets disclosed by companies is not relevant to the sample. In relation the content analysis of the notes was checked a partial compliance of the standard, there is a disparity in the information disclosure practices by the companies analyzed, as well as an omission of items required by the standard. Can be inferred that loss of the relevance has occurred, in part, by the poor quality of the notes, which may make it difficult for outside users in interpreting the information disclosed.

Effective automated feature construction and selection for classification of biological sequences.

Directory of Open Access Journals (Sweden)

Uday Kamath

Full Text Available Many open problems in bioinformatics involve elucidating underlying functional signals in biological sequences. DNA sequences, in particular, are characterized by rich architectures in which functional signals are increasingly found to combine local and distal interactions at the nucleotide level. Problems of interest include detection of regulatory regions, splice sites, exons, hypersensitive sites, and more. These problems naturally lend themselves to formulation as classification problems in machine learning. When classification is based on features extracted from the sequences under investigation, success is critically dependent on the chosen set of features.We present an algorithmic framework (EFFECT for automated detection of functional signals in biological sequences. We focus here on classification problems involving DNA sequences which state-of-the-art work in machine learning shows to be challenging and involve complex combinations of local and distal features. EFFECT uses a two-stage process to first construct a set of candidate sequence-based features and then select a most effective subset for the classification task at hand. Both stages make heavy use of evolutionary algorithms to efficiently guide the search towards informative features capable of discriminating between sequences that contain a particular functional signal and those that do not.To demonstrate its generality, EFFECT is applied to three separate problems of importance in DNA research: the recognition of hypersensitive sites, splice sites, and ALU sites. Comparisons with state-of-the-art algorithms show that the framework is both general and powerful. In addition, a detailed analysis of the constructed features shows that they contain valuable biological information about DNA architecture, allowing biologists and other researchers to directly inspect the features and potentially use the insights obtained to assist wet-laboratory studies on retainment or modification

Using novel descriptor accounting for ligand-receptor interactions to define and visually explore biologically relevant chemical space.

Science.gov (United States)

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

Synthetic biology analysed tools for discussion and evaluation

CERN Document Server

2016-01-01

Synthetic biology is a dynamic, young, ambitious, attractive, and heterogeneous scientific discipline. It is constantly developing and changing, which makes societal evaluation of this emerging new science a challenging task, prone to misunderstandings. Synthetic biology is difficult to capture, and confusion arises not only regarding which part of synthetic biology the discussion is about, but also with respect to the underlying concepts in use. This book offers a useful toolbox to approach this complex and fragmented field. It provides a biological access to the discussion using a 'layer' model that describes the connectivity of synthetic or semisynthetic organisms and cells to the realm of natural organisms derived by evolution. Instead of directly reviewing the field as a whole, firstly our book addresses the characteristic features of synthetic biology that are relevant to the societal discussion. Some of these features apply only to parts of synthetic biology, whereas others are relevant to synthetic bi...

The Integrin Receptor in Biologically Relevant Bilayers

DEFF Research Database (Denmark)

Kalli, Antreas C.; Róg, Tomasz; Vattulainen, Ilpo

2017-01-01

/talin complex was inserted in biologically relevant bilayers that resemble the cell plasma membrane containing zwitterionic and charged phospholipids, cholesterol and sphingolipids to study the dynamics of the integrin receptor and its effect on bilayer structure and dynamics. The results of this study...... demonstrate the dynamic nature of the integrin receptor and suggest that the presence of the integrin receptor alters the lipid organization between the two leaflets of the bilayer. In particular, our results suggest elevated density of cholesterol and of phosphatidylserine lipids around the integrin....../talin complex and a slowing down of lipids in an annulus of ~30 Å around the protein due to interactions between the lipids and the integrin/talin F2–F3 complex. This may in part regulate the interactions of integrins with other related proteins or integrin clustering thus facilitating signal transduction...

Instructional Quality Features in Videotaped Biology Lessons: Content-Independent Description of Characteristics

Science.gov (United States)

Dorfner, Tobias; Förtsch, Christian; Boone, William; Neuhaus, Birgit J.

2017-09-01

A number of studies on single instructional quality features have been reported for mathematics and science instruction. For summarizing single instructional quality features, researchers have created a model of three basic dimensions (classroom management, supportive climate, and cognitive activation) of instructional quality mainly through observing mathematics instruction. Considering this model as valid for all subjects and as usable for describing instruction, we used it in this study which aimed to analyze characteristics of instructional quality in biology lessons of high-achieving and low-achieving classes, independently of content. Therefore, we used the data of three different previous video studies of biology instruction conducted in Germany. From each video study, we selected three high-achieving and three low-achieving classes (N = 18 teachers; 35 videos) for our multiple-case study, in which conspicuous characteristics of instructional quality features were qualitatively identified and qualitatively analyzed. The amount of these characteristics was counted in a quantitative way in all the videos. The characteristics we found could be categorized using the model of three basic dimensions of instructional quality despite some subject-specific differences for biology instruction. Our results revealed that many more characteristics were observable in high-achieving classes than in low-achieving classes. Thus, we believe that this model could be used to describe biology instruction independently of the content. We also make the claims about the qualities for biology instruction—working with concentration in a content-structured environment, getting challenged in higher order thinking, and getting praised for performance—that could have positive influence on students' achievement.

Developmental Testing of Liquid and Gaseous/Vaporous Decontamination on Bacterial Spores and Other Biological Warfare Agents on Military Relevant Surfaces

Science.gov (United States)

2016-02-11

Vaporous Decontamination on Bacterial Spores and Other Biological Warfare Agents on Military-Relevant Surfaces 5a. CONTRACT NUMBER 5b. GRANT... DECONTAMINATION ON BACTERIAL SPORES AND OTHER BIOLOGICAL WARFARE AGENTS ON MILITARY-RELEVANT SURFACES Page Paragraph 1. SCOPE...surfaces before and after decontamination . The protocol in this TOP is based on the developed test methodologies from Edgewood Chemical Biological

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli.

Science.gov (United States)

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-03-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for biologically emotional images was enhanced even with limited cognitive resources, but (3) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images' subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in the visual cortex and greater functional connectivity between the amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in the medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between the amygdala and MPFC than did biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity.

MememxGATE: Unearthing Latent Content Features for Improved Search and Relevancy Ranking Across Scientific Literature

Science.gov (United States)

Wilson, B. D.; McGibbney, L. J.; Mattmann, C. A.; Ramirez, P.; Joyce, M.; Whitehall, K. D.

2015-12-01

Quantifying scientific relevancy is of increasing importance to NASA and the research community. Scientific relevancy may be defined by mapping the impacts of a particular NASA mission, instrument, and/or retrieved variables to disciplines such as climate predictions, natural hazards detection and mitigation processes, education, and scientific discoveries. Related to relevancy, is the ability to expose data with similar attributes. This in turn depends upon the ability for us to extract latent, implicit document features from scientific data and resources and make them explicit, accessible and useable for search activities amongst others. This paper presents MemexGATE; a server side application, command line interface and computing environment for running large scale metadata extraction, general architecture text engineering, document classification and indexing tasks over document resources such as social media streams, scientific literature archives, legal documentation, etc. This work builds on existing experiences using MemexGATE (funded, developed and validated through the DARPA Memex Progrjam PI Mattmann) for extracting and leveraging latent content features from document resources within the Materials Research domain. We extend the software functionality capability to the domain of scientific literature with emphasis on the expansion of gazetteer lists, named entity rules, natural language construct labeling (e.g. synonym, antonym, hyponym, etc.) efforts to enable extraction of latent content features from data hosted by wide variety of scientific literature vendors (AGU Meeting Abstract Database, Springer, Wiley Online, Elsevier, etc.) hosting earth science literature. Such literature makes both implicit and explicit references to NASA datasets and relationships between such concepts stored across EOSDIS DAAC's hence we envisage that a significant part of this effort will also include development and understanding of relevancy signals which can ultimately

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

Science.gov (United States)

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.

Biphasic dose responses in biology, toxicology and medicine: Accounting for their generalizability and quantitative features

International Nuclear Information System (INIS)

Calabrese, Edward J.

2013-01-01

The most common quantitative feature of the hormetic-biphasic dose response is its modest stimulatory response which at maximum is only 30–60% greater than control values, an observation that is consistently independent of biological model, level of organization (i.e., cell, organ or individual), endpoint measured, chemical/physical agent studied, or mechanism. This quantitative feature suggests an underlying “upstream” mechanism common across biological systems, therefore basic and general. Hormetic dose response relationships represent an estimate of the peak performance of integrative biological processes that are allometrically based. Hormetic responses reflect both direct stimulatory or overcompensation responses to damage induced by relatively low doses of chemical or physical agents. The integration of the hormetic dose response within an allometric framework provides, for the first time, an explanation for both the generality and the quantitative features of the hormetic dose response. -- Highlights: •The hormetic stimulation is at maximum 30–60% greater than control responses. •Hormesis is a measure of biological performance and plasticity. •The hormetic response is evolutionary based and highly generalizable. -- This paper provides a biologically based explanation for the generalizability/quantitative features of the hormetic dose response, representing a fundamental contribution to the field

Biological features produced by additive manufacturing processes using vat photopolymerization method

DEFF Research Database (Denmark)

Davoudinejad, Ali; Mendez Ribo, Macarena; Pedersen, David Bue

2017-01-01

of micro biological features by Additive Manufacturing (AM) processes. The study characterizes the additive manufacturing processes for polymeric micro part productions using the vat photopolymerization method. A specifically designed vat photopolymerization AM machine suitable for precision printing...

A DSS framework for maintaining relevant features of the Small Business B2C Websites

OpenAIRE

Khatun, Madhury; Miah, Shah Jahan

2016-01-01

Managers are heavily engaged in strategic decision-making for businesses, particularly in a changing environment. One of the most important decisions for online small businesses, as part of their strategic planning, is selecting relevant features on their websites, both to attract and interact with consumers. However, only a few Australian small businesses use strategic tools for selecting their website features. As a result, businesses lose potential domestic sales in the business-to-consume...

A model of biological neuron with terminal chaos and quantum-like features

International Nuclear Information System (INIS)

Conte, Elio; Pierri, GianPaolo; Federici, Antonio; Mendolicchio, Leonardo; Zbilut, Joseph P.

2006-01-01

A model of biological neuron is proposed combining terminal dynamics with quantum-like mechanical features, assuming the spin to be an important entity in neurodynamics, and, in particular, in synaptic transmission

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Science.gov (United States)

Irshad, Humayun; Jalali, Sepehr; Roux, Ludovic; Racoceanu, Daniel; Hwee, Lim Joo; Naour, Gilles Le; Capron, Frédérique

2013-01-01

According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. The aim is to investigate the various texture features and Hierarchical Model and X (HMAX) biologically inspired approach for mitosis detection using machine-learning techniques. We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT) features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM), and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for an International Conference on Pattern Recognition (ICPR) 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.

Molecular biological features of male germ cell differentiation

Science.gov (United States)

HIROSE, MIKA; TOKUHIRO, KEIZO; TAINAKA, HITOSHI; MIYAGAWA, YASUSHI; TSUJIMURA, AKIRA; OKUYAMA, AKIHIKO; NISHIMUNE, YOSHITAKE

2007-01-01

Somatic cell differentiation is required throughout the life of a multicellular organism to maintain homeostasis. In contrast, germ cells have only one specific function; to preserve the species by conveying the parental genes to the next generation. Recent studies of the development and molecular biology of the male germ cell have identified many genes, or isoforms, that are specifically expressed in the male germ cell. In the present review, we consider the unique features of male germ cell differentiation. (Reprod Med Biol 2007; 6: 1–9) PMID:29699260

Biological adaptations for functional features of language in the face of cultural evolution.

Science.gov (United States)

Christiansen, Morten H; Reali, Florencia; Chater, Nick

2011-04-01

Although there may be no true language universals, it is nonetheless possible to discern several family resemblance patterns across the languages of the world. Recent work on the cultural evolution of language indicates the source of these patterns is unlikely to be an innate universal grammar evolved through biological adaptations for arbitrary linguistic features. Instead, it has been suggested that the patterns of resemblance emerge because language has been shaped by the brain, with individual languages representing different but partially overlapping solutions to the same set of nonlinguistic constraints. Here, we use computational simulations to investigate whether biological adaptation for functional features of language, deriving from cognitive and communicative constraints, may nonetheless be possible alongside rapid cultural evolution. Specifically, we focus on the Baldwin effect as an evolutionary mechanism by which previously learned linguistic features might become innate through natural selection across many generations of language users. The results indicate that cultural evolution of language does not necessarily prevent functional features of language from becoming genetically fixed, thus potentially providing a particularly informative source of constraints on cross-linguistic resemblance patterns.

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

Directory of Open Access Journals (Sweden)

Humayun Irshad

2013-01-01

Full Text Available Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to investigate the various texture features and Hierarchical Model and X (HMAX biologically inspired approach for mitosis detection using machine-learning techniques. Materials and Methods: We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM, and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. Results: The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS dataset provided for an International Conference on Pattern Recognition (ICPR 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Conclusions: Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and

Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

Science.gov (United States)

Liu, Guo-Ping; Yan, Jian-Jun; Wang, Yi-Qin; Fu, Jing-Jing; Xu, Zhao-Xia; Guo, Rui; Qian, Peng

2012-01-01

Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs). Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:22719781

Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

Directory of Open Access Journals (Sweden)

Guo-Ping Liu

2012-01-01

Full Text Available Background. In Traditional Chinese Medicine (TCM, most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs. Methods. We employed a multilabel learning using the relevant feature for each label (REAL algorithm to construct a syndrome diagnostic model for chronic gastritis (CG in TCM. REAL combines feature selection methods to select the significant symptoms (signs of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL, whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.

CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources.

Science.gov (United States)

Bleda, Marta; Tarraga, Joaquin; de Maria, Alejandro; Salavert, Francisco; Garcia-Alonso, Luz; Celma, Matilde; Martin, Ainoha; Dopazo, Joaquin; Medina, Ignacio

2012-07-01

During the past years, the advances in high-throughput technologies have produced an unprecedented growth in the number and size of repositories and databases storing relevant biological data. Today, there is more biological information than ever but, unfortunately, the current status of many of these repositories is far from being optimal. Some of the most common problems are that the information is spread out in many small databases; frequently there are different standards among repositories and some databases are no longer supported or they contain too specific and unconnected information. In addition, data size is increasingly becoming an obstacle when accessing or storing biological data. All these issues make very difficult to extract and integrate information from different sources, to analyze experiments or to access and query this information in a programmatic way. CellBase provides a solution to the growing necessity of integration by easing the access to biological data. CellBase implements a set of RESTful web services that query a centralized database containing the most relevant biological data sources. The database is hosted in our servers and is regularly updated. CellBase documentation can be found at http://docs.bioinfo.cipf.es/projects/cellbase.

Task relevance modulates the cortical representation of feature conjunctions in the target template.

Science.gov (United States)

Reeder, Reshanne R; Hanke, Michael; Pollmann, Stefan

2017-07-03

Little is known about the cortical regions involved in representing task-related content in preparation for visual task performance. Here we used representational similarity analysis (RSA) to investigate the BOLD response pattern similarity between task relevant and task irrelevant feature dimensions during conjunction viewing and target template maintenance prior to visual search. Subjects were cued to search for a spatial frequency (SF) or orientation of a Gabor grating and we measured BOLD signal during cue and delay periods before the onset of a search display. RSA of delay period activity revealed that widespread regions in frontal, posterior parietal, and occipitotemporal cortices showed general representational differences between task relevant and task irrelevant dimensions (e.g., orientation vs. SF). In contrast, RSA of cue period activity revealed sensory-related representational differences between cue images (regardless of task) at the occipital pole and additionally in the frontal pole. Our data show that task and sensory information are represented differently during viewing and during target template maintenance, and that task relevance modulates the representation of visual information across the cortex.

Clinical and Biological Features of Interval Colorectal Cancer

Directory of Open Access Journals (Sweden)

Yu Mi Lee

2017-05-01

Full Text Available Interval colorectal cancer (I-CRC is defined as a CRC diagnosed within 60 months after a negative colonoscopy, taking into account that 5 years is the “mean sojourn time.” It is important to prevent the development of interval cancer. The development of interval colon cancer is associated with female sex, old age, family history of CRC, comorbidities, diverticulosis, and the skill of the endoscopist. During carcinogenesis, sessile serrated adenomas/polyps (SSA/Ps share many genomic and colonic site characteristics with I-CRCs. The clinical and biological features of I-CRC should be elucidated to prevent the development of interval colon cancer.

Modelling low energy electron and positron tracks in biologically relevant media

International Nuclear Information System (INIS)

Blanco, F.; Munoz, A.; Almeida, D.; Ferreira da Silva, F.; Limao-Vieira, P.; Fuss, M.C.; Sanz, A.G.; Garcia, G.

2013-01-01

This colloquium describes an approach to incorporate into radiation damage models the effect of low and intermediate energy (0-100 eV) electrons and positrons, slowing down in biologically relevant materials (water and representative biomolecules). The core of the modelling procedure is a C++ computing programme named 'Low Energy Particle Track Simulation (LEPTS)', which is compatible with available general purpose Monte Carlo packages. Input parameters are carefully selected from theoretical and experimental cross section data and energy loss distribution functions. Data sources used for this purpose are reviewed showing examples of electron and positron cross section and energy loss data for interactions with different media of increasing complexity: atoms, molecules, clusters and condense matter. Finally, we show how such a model can be used to develop an effective dosimetric tool at the molecular level (i.e. nanodosimetry). Recent experimental developments to study the fragmentation induced in biologically material by charge transfer from neutrals and negative ions are also included. (authors)

Streptococcus pyogenes biofilms – formation, biology,and clinical relevance

Directory of Open Access Journals (Sweden)

Tomas eFiedler

2015-02-01

Full Text Available Streptococcus pyogenes (group A streptococci, GAS is an exclusive human bacterial pathogen. The virulence potential of this species is tremendous. Interactions with humans range from asymptomatic carriage over mild and superficial infections of skin and mucosal membranes up to systemic purulent toxic-invasive disease manifestations. Particularly the latter are a severe threat for predisposed patients and lead to significant death tolls worldwide. This places GAS among the most important Gram-positive bacterial pathogens. Many recent reviews have highlighted the GAS repertoire of virulence factors, regulators and regulatory circuits/networks that enable GAS to colonize the host and to deal with all levels of the host immune defense. This covers in vitro and in vivo studies, including animal infection studies based on mice and more relevant, macaque monkeys. It is now appreciated that GAS, like many other bacterial species, do not necessarily exclusively live in a planktonic lifestyle. GAS is capable of microcolony and biofilm formation on host cells and tissues. We are now beginning to understand that this feature significantly contributes to GAS pathogenesis. In this review we will discuss the current knowledge on GAS biofilm formation, the biofilm-phenotype associated virulence factors, regulatory aspects of biofilm formation, the clinical relevance, and finally contemporary treatment regimens and future treatment options.

Distinguishing Biologically Relevant Hexoses by Water Adduction to the Lithium-Cationized Molecule.

Science.gov (United States)

Campbell, Matthew T; Chen, Dazhe; Wallbillich, Nicholas J; Glish, Gary L

2017-10-03

A method to distinguish the four most common biologically relevant underivatized hexoses, d-glucose, d-galactose, d-mannose, and d-fructose, using only mass spectrometry with no prior separation/derivatization step has been developed. Electrospray of a solution containing hexose and a lithium salt generates [Hexose+Li] + . The lithium-cationized hexoses adduct water in a quadrupole ion trap. The rate of this water adduction reaction can be used to distinguish the four hexoses. Additionally, for each hexose, multiple lithiation sites are possible, allowing for multiple structures of [Hexose+Li] + . Electrospray produces at least one structure that reacts with water and at least one that does not. The ratio of unreactive lithium-cationized hexose to total lithium-cationized hexose is unique for the four hexoses studied, providing a second method for distinguishing the isomers. Use of the water adduction reaction rate or the unreactive ratio provides two separate methods for confidently (p ≤ 0.02) distinguishing the most common biologically relevant hexoses using only femtomoles of hexose. Additionally, binary mixtures of glucose and fructose were studied. A calibration curve was created by measuring the reaction rate of various samples with different ratios of fructose and glucose. The calibration curve was used to accurately measure the percentage of fructose in three samples of high fructose corn syrup (<4% error).

High-temperature Ionization-induced Synthesis of Biologically Relevant Molecules in the Protosolar Nebula

Science.gov (United States)

Bekaert, David V.; Derenne, Sylvie; Tissandier, Laurent; Marrocchi, Yves; Charnoz, Sebastien; Anquetil, Christelle; Marty, Bernard

2018-06-01

Biologically relevant molecules (hereafter biomolecules) have been commonly observed in extraterrestrial samples, but the mechanisms accounting for their synthesis in space are not well understood. While electron-driven production of organic solids from gas mixtures reminiscent of the photosphere of the protosolar nebula (PSN; i.e., dominated by CO–N2–H2) successfully reproduced key specific features of the chondritic insoluble organic matter (e.g., elementary and isotopic signatures of chondritic noble gases), the molecular diversity of organic materials has never been investigated. Here, we report that a large range of biomolecules detected in meteorites and comets can be synthesized under conditions typical of the irradiated gas phase of the PSN at temperatures = 800 K. Our results suggest that organic materials—including biomolecules—produced within the photosphere would have been widely dispersed in the protoplanetary disk through turbulent diffusion, providing a mechanism for the distribution of organic meteoritic precursors prior to any thermal/photoprocessing and subsequent modification by secondary parent body processes. Using a numerical model of dust transport in a turbulent disk, we propose that organic materials produced in the photosphere of the disk would likely be associated with small dust particles, which are coupled to the motion of gas within the disk and therefore preferentially lofted into the upper layers of the disk where organosynthesis occurs.

Biology relevant to space radiation

International Nuclear Information System (INIS)

Fry, R.J.M.

1996-01-01

The biological effects of the radiations to which mankind on earth are exposed are becoming known with an increasing degree of detail. This knowledge is the basis of the estimates of risk that, in turn, fosters a comprehensive and evolving radiation protection system. The substantial body of information has been, and is being, applied to questions about the biological effects of radiation is space and the associated risk estimates. The purpose of this paper is not to recount all the biological effect of radiation but to concentrate on those that may occur as a result from exposure to the radiations encountered in space. In general, the biological effects of radiation in space are the same as those on earth. However, the evidence that the effects on certain tissues by the heaviest-charged particles can be interpreted on the basis of our knowledge about other high-LET radiation is equivocal. This specific question will be discussed in greater detail later. It is important to point out the that there are only limited data about the effects on humans of two components of the radiations in space, namely protons and heavy ions. Thus predictions of effects on space crews are based on experimental systems exposed on earth at rates and fluences that are higher than those in space and one the effects of gamma or x rays with estimates of the equivalent doses using quality factors

Single cell biology beyond the era of antibodies: relevance, challenges, and promises in biomedical research.

Science.gov (United States)

Abraham, Parvin; Maliekal, Tessy Thomas

2017-04-01

Research of the past two decades has proved the relevance of single cell biology in basic research and translational medicine. Successful detection and isolation of specific subsets is the key to understand their functional heterogeneity. Antibodies are conventionally used for this purpose, but their relevance in certain contexts is limited. In this review, we discuss some of these contexts, posing bottle neck for different fields of biology including biomedical research. With the advancement of chemistry, several methods have been introduced to overcome these problems. Even though microfluidics and microraft array are newer techniques exploited for single cell biology, fluorescence-activated cell sorting (FACS) remains the gold standard technique for isolation of cells for many biomedical applications, like stem cell therapy. Here, we present a comprehensive and comparative account of some of the probes that are useful in FACS. Further, we illustrate how these techniques could be applied in biomedical research. It is postulated that intracellular molecular markers like nucleostemin (GNL3), alkaline phosphatase (ALPL) and HIRA can be used for improving the outcome of cardiac as well as bone regeneration. Another field that could utilize intracellular markers is diagnostics, and we propose the use of specific peptide nucleic acid probes (PNPs) against certain miRNAs for cancer surgical margin prediction. The newer techniques for single cell biology, based on intracellular molecules, will immensely enhance the repertoire of possible markers for the isolation of cell types useful in biomedical research.

Relevant Features of Science: Values in Conservation Biology

Science.gov (United States)

van Dijk, Esther M.

2013-01-01

The development of an understanding of the nature of science is generally assumed to be an important aspect of science communication with respect to the enhancement of scientific literacy. At present, a general characterization of the nature of science is still lacking and probably such a characterization will not be achievable. The overall aim of…

Healthy full-term infants' brain responses to emotionally and linguistically relevant sounds using a multi-feature mismatch negativity (MMN) paradigm.

Science.gov (United States)

Kostilainen, Kaisamari; Wikström, Valtteri; Pakarinen, Satu; Videman, Mari; Karlsson, Linnea; Keskinen, Maria; Scheinin, Noora M; Karlsson, Hasse; Huotilainen, Minna

2018-03-23

We evaluated the feasibility of a multi-feature mismatch negativity (MMN) paradigm in studying auditory processing of healthy newborns. The aim was to examine the automatic change-detection and processing of semantic and emotional information in speech in newborns. Brain responses of 202 healthy newborns were recorded with a multi-feature paradigm including a Finnish bi-syllabic pseudo-word/ta-ta/as a standard stimulus, six linguistically relevant deviant stimuli and three emotionally relevant stimuli (happy, sad, angry). Clear responses to emotional sounds were found already at the early latency window 100-200 ms, whereas responses to linguistically relevant minor changes and emotional stimuli at the later latency window 300-500 ms did not reach significance. Moreover, significant interaction between gender and emotional stimuli was found in the early latency window. Further studies on using multi-feature paradigms with linguistic and emotional stimuli in newborns are needed, especially those containing of follow-ups, enabling the assessment of the predictive value of early variations between subjects. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Seven-day human biological rhythms: An expedition in search of their origin, synchronization, functional advantage, adaptive value and clinical relevance.

Science.gov (United States)

Reinberg, Alain E; Dejardin, Laurence; Smolensky, Michael H; Touitou, Yvan

2017-01-01

This fact-finding expedition explores the perspectives and knowledge of the origin and functional relevance of the 7 d domain of the biological time structure, with special reference to human beings. These biological rhythms are displayed at various levels of organization in diverse species - from the unicellular sea algae of Acetabularia and Goniaulax to plants, insects, fish, birds and mammals, including man - under natural as well as artificial, i.e. constant, environmental conditions. Nonetheless, very little is known about their derivation, functional advantage, adaptive value, synchronization and potential clinical relevance. About 7 d cosmic cycles are seemingly too weak, and the 6 d work/1 d rest week commanded from G-d through the Laws of Mosses to the Hebrews is too recent an event to be the origin in humans. Moreover, human and insect studies conducted under controlled constant conditions devoid of environmental, social and other time cues report the persistence of 7 d rhythms, but with a slightly different (free-running) period (τ), indicating their source is endogenous. Yet, a series of human and laboratory rodent studies reveal certain mainly non-cyclic exogenous events can trigger 7 d rhythm-like phenomena. However, it is unknown whether such triggers unmask, amplify and/or synchronize previous non-overtly expressed oscillations. Circadian (~24 h), circa-monthly (~30 d) and circannual (~1 y) rhythms are viewed as genetically based features of life forms that during evolution conferred significant functional advantage to individual organisms and survival value to species. No such advantages are apparent for endogenous 7 d rhythms, raising several questions: What is the significance of the 7 d activity/rest cycle, i.e. week, storied in the Book of Genesis and adopted by the Hebrews and thereafter the residents of nearby Mediterranean countries and ultimately the world? Why do humans require 1 d off per 7 d span? Do 7 d rhythms bestow functional

Clinical, biological, histological features and treatment of oral mucositis induced by radiation therapy: a literature review

International Nuclear Information System (INIS)

Bonan, Paulo Rogerio Ferreti; Lopes, Marcio Ajudarte; Almeida, Oslei Paes de; Alves, Fabio de Abreu

2005-01-01

The oral mucositis is a main side effect of radiotherapy on head and neck, initiating two weeks after the beginning of the treatment. It is characterized by sensation of local burning to intense pain, leading in several cases, to the interruption of the treatment. The purpose of this work is to review the main published studies that discuss the clinical, biological and histopathological features of oral mucositis induced by radiation therapy and to describe the main approaches recommended to prevent or to treat it. Although the clinical features of mucositis are intensively described in the literature, few studies address the histopathological alterations in oral mucositis and only recently, its biological processes have been investigated. The biological mechanisms involved in the radiation tissue damage have been only recently discussed and there is no consensus among treatment modalities. Yet, the progressive knowledge in the histopathology and biological characteristics of oral mucositis probably will lead to more effective in prevention and control strategies. (author)

Inferring feature relevances from metric learning

DEFF Research Database (Denmark)

Schulz, Alexander; Mokbel, Bassam; Biehl, Michael

2015-01-01

Powerful metric learning algorithms have been proposed in the last years which do not only greatly enhance the accuracy of distance-based classifiers and nearest neighbor database retrieval, but which also enable the interpretability of these operations by assigning explicit relevance weights...

BIOLOGICAL FEATURES OF TARAN (RUTILUS HECKELII OF THE DNIEPER-BUG ESTUARY SYSTEM

Directory of Open Access Journals (Sweden)

K. Geina

2016-03-01

Full Text Available Purpose. To analyze morphological variability and basic biological features of the modern stock of taran of the Dnieper-Bug estuary system in the conditions of the transformed Dnieper flow. Methodology. Morphological variability was determined based on the comparison of morphological features of roach Rutilus rutilus (Linnaeus, 1758 of the Kakhovka reservoir and semi-migratory taran Rutilus rutilus heckelii (Nordmann, 1840 of the Dnieper-Bug estuary system. As a main criterion of the evaluation of the taran stock biological state, we used age, sex structure, growth characteristics, fecundity and condition factor. Fish sampling was carried out at stationary monitoring-observation stations of the Institute of Fisheries NAAS of Ukraine. Field and cameral processing of the collected materials were performed based on conventional methods and guidelines. Findings. Morphological variability analysis demonstrated significant differences between Dnieper and Bug taran. The highest differences were observed for antroventral distance (td=11.19. Significant differences were also observed for antenanal and ventroanal distances td=4.05-4.14. No significant differences were found for meristic features. There were also significant differences between Dnieper-Bug taran and Kakhovka reservoir roach, which had formed a resident form after regulating the Dnieper River flow. Kakhovka reservoir roach is more deep-bodied with Н=32.79%, t-test value was 5.65. Pelvic fins were more shifted to the caudal fin (td=5.28 that resulted in significant difference (p<0.05 in ventroanal distance (td=4.26. Taran also had somewhat smaller length of the anal fin base (td=4.73 but its height was higher – td=5.78. The main peculiarity of the current biological state of taran stock is the domination of young age groups. The small number of fish in the boundary groups of the age series right wing with relative stability of growth features indicate on intensive pressure on the

Longitudinal MRI assessment: the identification of relevant features in the development of Posterior Fossa Syndrome in children

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Spiteri, M.; Lewis, E.; Windridge, D.; Avula, S.

2015-03-01

Up to 25% of children who undergo brain tumour resection surgery in the posterior fossa develop posterior fossa syndrome (PFS). This syndrome is characterised by mutism and disturbance in speech. Our hypothesis is that there is a correlation between PFS and the occurrence of hypertrophic olivary degeneration (HOD) in lobes within the posterior fossa, known as the inferior olivary nuclei (ION). HOD is exhibited as an increase in size and intensity of the ION on an MR image. Intra-operative MRI (IoMRI) is used during surgical procedures at the Alder Hey Children's Hospital, Liver- pool, England, in the treatment of Posterior Fossa tumours and allows visualisation of the brain during surgery. The final MR scan on the IoMRI allows early assessment of the ION immediately after the surgical procedure. The longitudinal MRI data of 28 patients was analysed in a collaborative study with Alder Hey Children's Hospital, in order to identify the most relevant imaging features that relate to the development of PFS, specifically related to HOD. A semi-automated segmentation process was carried out to delineate the ION on each MRI. Feature selection techniques were used to identify the most relevant features amongst the MRI data, demographics and clinical data provided by the hospital. A support vector machine (SVM) was used to analyse the discriminative ability of the selected features. The results indicate the presence of HOD as the most efficient feature that correlates with the development of PFS, followed by the change in intensity and size of the ION and whether HOD occurred bilaterally or unilaterally.

Physical, chemical, and biological properties of radiocerium relevant to radiation protection guidelines

International Nuclear Information System (INIS)

Anon.

1978-01-01

Present knowledge of the relevant physical, chemical, and biological properties of radiocerium as a basis for establishing radiation protection guidelines is summarized. The first section of the report reviews the chemical and physical properties of radiocerium relative to the biological behavior of internally-deposited cerium and other lanthanides. The second section of the report gives the sources of radiocerium in the environment and the pathways to man. The third section of the report describes the metabolic fate of cerium in several mammalian species as a basis for predicting its metabolic fate in man. The fourth section of the report considers the biomedical effects of radiocerium in light of extensive animal experimentation. The last two sections of the report describe the history of radiation protection guidelines for radiocerium and summarize data required for evaluating the adequacy of current radiation protection guidelines. Each section begins with a summary of the most important findings that follow

Teleology then and now: the question of Kant's relevance for contemporary controversies over function in biology.

Science.gov (United States)

Zammito, John

2006-12-01

'Naturalism' is the aspiration of contemporary philosophy of biology, and Kant simply cannot be refashioned into a naturalist. Instead, epistemological 'deflation' was the decisive feature of Kant's treatment of the 'biomedical' science in his day, so it is not surprising that this might attract some philosophers of science to him today. A certain sense of impasse in the contemporary 'function talk' seems to motivate renewed interest in Kant. Kant--drawing on his eighteenth-century predecessors-provided a discerning and powerful characterization of what biologists had to explain in organic form. His difference from the rest is that he opined that it was impossible to explain it. Its 'inscrutability' was intrinsic. The third Critique essentially proposed the reduction of biology to a kind of pre-scientific descriptivism, doomed never to attain authentic scientificity, to have its 'Newton of the blade of grass'. By contrast, for Locke, and a fortiori for Buffon and his followers, 'intrinsic purposiveness' was a fact of the matter about concrete biological phenomena; the features of internal self-regulation were hypotheses arising out of actual research practice. The difference comes most vividly to light once we recognize Kant's distinction of the concept of organism from the concept of life. If biology must conceptualize self-organization as actual in the world, Kant's regulative/constitutive distinction is pointless in practice and the (naturalist) philosophy of biology has urgent work to undertake for which Kant turns out not to be very helpful.

Crossmodal integration enhances neural representation of task-relevant features in audiovisual face perception.

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Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Liu, Yongjian; Liang, Changhong; Sun, Pei

2015-02-01

Previous studies have shown that audiovisual integration improves identification performance and enhances neural activity in heteromodal brain areas, for example, the posterior superior temporal sulcus/middle temporal gyrus (pSTS/MTG). Furthermore, it has also been demonstrated that attention plays an important role in crossmodal integration. In this study, we considered crossmodal integration in audiovisual facial perception and explored its effect on the neural representation of features. The audiovisual stimuli in the experiment consisted of facial movie clips that could be classified into 2 gender categories (male vs. female) or 2 emotion categories (crying vs. laughing). The visual/auditory-only stimuli were created from these movie clips by removing the auditory/visual contents. The subjects needed to make a judgment about the gender/emotion category for each movie clip in the audiovisual, visual-only, or auditory-only stimulus condition as functional magnetic resonance imaging (fMRI) signals were recorded. The neural representation of the gender/emotion feature was assessed using the decoding accuracy and the brain pattern-related reproducibility indices, obtained by a multivariate pattern analysis method from the fMRI data. In comparison to the visual-only and auditory-only stimulus conditions, we found that audiovisual integration enhanced the neural representation of task-relevant features and that feature-selective attention might play a role of modulation in the audiovisual integration. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The asymmetric hetero-Diels-Alder reaction in the syntheses of biologically relevant compounds.

Science.gov (United States)

Eschenbrenner-Lux, Vincent; Kumar, Kamal; Waldmann, Herbert

2014-10-13

The hetero-Diels-Alder reaction is one of the most powerful transformations in the chemistry toolbox for the synthesis of aza- and oxa-heterocycles embodying multiple stereogenic centers. However, as compared to other cycloadditions, in particular the dipolar cycloadditions and the Diels-Alder reaction, the hetero-Diels-Alder reaction has been much less explored and exploited in organic synthesis. Nevertheless, this powerful transformation has opened up efficient and creative routes to biologically relevant small molecules and different natural products which contain six-membered oxygen or nitrogen ring systems. Recent developments in this field, in particular in the establishment of enantioselectively catalyzed hetero-Diels-Alder cycloadditions steered by a plethora of different catalysts and the application of the resulting small molecules in chemical biology and medicinal chemistry research, are highlighted in this Minireview. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Food words distract the hungry: Evidence of involuntary semantic processing of task-irrelevant but biologically-relevant unexpected auditory words.

Science.gov (United States)

Parmentier, Fabrice B R; Pacheco-Unguetti, Antonia P; Valero, Sara

2018-01-01

Rare changes in a stream of otherwise repeated task-irrelevant sounds break through selective attention and disrupt performance in an unrelated visual task by triggering shifts of attention to and from the deviant sound (deviance distraction). Evidence indicates that the involuntary orientation of attention to unexpected sounds is followed by their semantic processing. However, past demonstrations relied on tasks in which the meaning of the deviant sounds overlapped with features of the primary task. Here we examine whether such processing is observed when no such overlap is present but sounds carry some relevance to the participants' biological need to eat when hungry. We report the results of an experiment in which hungry and satiated participants partook in a cross-modal oddball task in which they categorized visual digits (odd/even) while ignoring task-irrelevant sounds. On most trials the irrelevant sound was a sinewave tone (standard sound). On the remaining trials, deviant sounds consisted of spoken words related to food (food deviants) or control words (control deviants). Questionnaire data confirmed state (but not trait) differences between the two groups with respect to food craving, as well as a greater desire to eat the food corresponding to the food-related words in the hungry relative to the satiated participants. The results of the oddball task revealed that food deviants produced greater distraction (longer response times) than control deviants in hungry participants while the reverse effect was observed in satiated participants. This effect was observed in the first block of trials but disappeared thereafter, reflecting semantic saturation. Our results suggest that (1) the semantic content of deviant sounds is involuntarily processed even when sharing no feature with the primary task; and that (2) distraction by deviant sounds can be modulated by the participants' biological needs.

Biological effects of environmentally relevant concentrations of the pharmaceutical Triclosan in the marine mussel Perna perna (Linnaeus, 1758)

Energy Technology Data Exchange (ETDEWEB)

Sanzi Cortez, Fernando, E-mail: lecotox@unisanta.br [Instituto de Pesquisas Energeticas e Nucleares IPEN-CNEN/SP, 05508-000 Sao Paulo, SP (Brazil); Laboratorio de Ecotoxicologia, Universidade Santa Cecilia, 11045-907 Santos, SP (Brazil); Dias Seabra Pereira, Camilo [Laboratorio de Ecotoxicologia, Universidade Santa Cecilia, 11045-907 Santos, SP (Brazil); Instituto do Mar, Universidade Federal de Sao Paulo, 11030-400 Santos, SP (Brazil); Ramos Santos, Aldo Ramos [Laboratorio de Ecotoxicologia, Universidade Santa Cecilia, 11045-907 Santos, SP (Brazil); Cesar, Augusto; Choueri, Rodrigo Brasil [Laboratorio de Ecotoxicologia, Universidade Santa Cecilia, 11045-907 Santos, SP (Brazil); Instituto do Mar, Universidade Federal de Sao Paulo, 11030-400 Santos, SP (Brazil); Martini, Gisela de Assis [Laboratorio de Ecotoxicologia, Universidade Santa Cecilia, 11045-907 Santos, SP (Brazil); Bohrer-Morel, Maria Beatriz [Instituto de Pesquisas Energeticas e Nucleares IPEN-CNEN/SP, 05508-000 Sao Paulo, SP (Brazil)

2012-09-15

Triclosan (5-Chloro-2-(2,4-dichlorophenoxy) phenol) is an antibacterial compound widely employed in pharmaceuticals and personal care products. Although this emerging compound has been detected in aquatic environments, scarce information is found on the effects of Triclosan to marine organisms. The aim of this study was to evaluate the toxicity of a concentration range of Triclosan through fertilization assay (reproductive success), embryo-larval development assay (early life stage) and physiological stress (Neutral Red Retention Time assay - NRRT) (adult stage) in the marine sentinel organism Perna perna. The mean inhibition concentrations for fertilization (IC{sub 50} = 0.490 mg L{sup -1}) and embryo-larval development (IC{sub 50} = 0.135 mg L{sup -1}) tests were above environmental relevant concentrations (ng L{sup -1}) given by previous studies. Differently, significant reduction on NRRT results was found at 12 ng L{sup -1}, demonstrating the current risk of the continuous introduction of Triclosan into aquatic environments, and the need of ecotoxicological studies oriented by the mechanism of action of the compound. - Highlights: Black-Right-Pointing-Pointer Triclosan causes biological adverse effects at environmental relevant concentrations. Black-Right-Pointing-Pointer Mechanisms of action oriented assays were more sensitive to detect biological damages. Black-Right-Pointing-Pointer Currently there is environmental risks concerned Triclosan in aquatic ecosystems. - Triclosan causes biological adverse effects at environmentally relevant concentrations.

Biological effects of environmentally relevant concentrations of the pharmaceutical Triclosan in the marine mussel Perna perna (Linnaeus, 1758)

International Nuclear Information System (INIS)

Sanzi Cortez, Fernando; Dias Seabra Pereira, Camilo; Ramos Santos, Aldo Ramos; Cesar, Augusto; Choueri, Rodrigo Brasil; Martini, Gisela de Assis; Bohrer-Morel, Maria Beatriz

2012-01-01

Triclosan (5-Chloro-2-(2,4-dichlorophenoxy) phenol) is an antibacterial compound widely employed in pharmaceuticals and personal care products. Although this emerging compound has been detected in aquatic environments, scarce information is found on the effects of Triclosan to marine organisms. The aim of this study was to evaluate the toxicity of a concentration range of Triclosan through fertilization assay (reproductive success), embryo-larval development assay (early life stage) and physiological stress (Neutral Red Retention Time assay - NRRT) (adult stage) in the marine sentinel organism Perna perna. The mean inhibition concentrations for fertilization (IC 50 = 0.490 mg L −1 ) and embryo-larval development (IC 50 = 0.135 mg L −1 ) tests were above environmental relevant concentrations (ng L −1 ) given by previous studies. Differently, significant reduction on NRRT results was found at 12 ng L −1 , demonstrating the current risk of the continuous introduction of Triclosan into aquatic environments, and the need of ecotoxicological studies oriented by the mechanism of action of the compound. - Highlights: ► Triclosan causes biological adverse effects at environmental relevant concentrations. ► Mechanisms of action oriented assays were more sensitive to detect biological damages. ► Currently there is environmental risks concerned Triclosan in aquatic ecosystems. - Triclosan causes biological adverse effects at environmentally relevant concentrations.

A biologically inspired scale-space for illumination invariant feature detection

International Nuclear Information System (INIS)

Vonikakis, Vasillios; Chrysostomou, Dimitrios; Kouskouridas, Rigas; Gasteratos, Antonios

2013-01-01

This paper presents a new illumination invariant operator, combining the nonlinear characteristics of biological center-surround cells with the classic difference of Gaussians operator. It specifically targets the underexposed image regions, exhibiting increased sensitivity to low contrast, while not affecting performance in the correctly exposed ones. The proposed operator can be used to create a scale-space, which in turn can be a part of a SIFT-based detector module. The main advantage of this illumination invariant scale-space is that, using just one global threshold, keypoints can be detected in both dark and bright image regions. In order to evaluate the degree of illumination invariance that the proposed, as well as other, existing, operators exhibit, a new benchmark dataset is introduced. It features a greater variety of imaging conditions, compared to existing databases, containing real scenes under various degrees and combinations of uniform and non-uniform illumination. Experimental results show that the proposed detector extracts a greater number of features, with a high level of repeatability, compared to other approaches, for both uniform and non-uniform illumination. This, along with its simple implementation, renders the proposed feature detector particularly appropriate for outdoor vision systems, working in environments under uncontrolled illumination conditions. (paper)

Applications of Microfluidics in Quantitative Biology.

Science.gov (United States)

Bai, Yang; Gao, Meng; Wen, Lingling; He, Caiyun; Chen, Yuan; Liu, Chenli; Fu, Xiongfei; Huang, Shuqiang

2018-05-01

Quantitative biology is dedicated to taking advantage of quantitative reasoning and advanced engineering technologies to make biology more predictable. Microfluidics, as an emerging technique, provides new approaches to precisely control fluidic conditions on small scales and collect data in high-throughput and quantitative manners. In this review, the authors present the relevant applications of microfluidics to quantitative biology based on two major categories (channel-based microfluidics and droplet-based microfluidics), and their typical features. We also envision some other microfluidic techniques that may not be employed in quantitative biology right now, but have great potential in the near future. © 2017 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. Biotechnology Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Investigation of some biologically relevant redox reactions using electrochemical mass spectrometry interfaced by desorption electrospray ionization.

Science.gov (United States)

Lu, Mei; Wolff, Chloe; Cui, Weidong; Chen, Hao

2012-04-01

Recently we have shown that, as a versatile ionization technique, desorption electrospray ionization (DESI) can serve as a useful interface to combine electrochemistry (EC) with mass spectrometry (MS). In this study, the EC/DESI-MS method has been further applied to investigate some aqueous phase redox reactions of biological significance, including the reduction of peptide disulfide bonds and nitroaromatics as well as the oxidation of phenothiazines. It was found that knotted/enclosed disulfide bonds in the peptides apamin and endothelin could be electrochemically cleaved. Subsequent tandem MS analysis of the resulting reduced peptide ions using collision-induced dissociation (CID) and electron-capture dissociation (ECD) gave rise to extensive fragment ions, providing a fast protocol for sequencing peptides with complicated disulfide bond linkages. Flunitrazepam and clonazepam, a class of nitroaromatic drugs, are known to undergo reduction into amines which was proposed to involve nitroso and N-hydroxyl intermediates. Now in this study, these corresponding intermediate ions were successfully intercepted and their structures were confirmed by CID. This provides mass spectrometric evidence for the mechanism of the nitro to amine conversion process during nitroreduction, an important redox reaction involved in carcinogenesis. In addition, the well-known oxidation reaction of chlorpromazine was also examined. The putative transient one-electron transfer product, the chlorpromazine radical cation (m/z 318), was captured by MS, for the first time, and its structure was also verified by CID. In addition to these observations, some features of the DESI-interfaced electrochemical mass spectrometry were discussed, such as simple instrumentation and the lack of background signal. These results further demonstrate the feasibility of EC/DESI-MS for the study of the biology-relevant redox chemistry and would find applications in proteomics and drug development research.

Relevance of echo-structure and texture features

DEFF Research Database (Denmark)

Karemore, Gopal; Mullick, Jhinuk Basu; KV, Dr. Rajagopal

2010-01-01

Aim: Echostructure is an essential parameter for the evaluation of circumscribed lesions and can be described as a texture feature on ultrasound images. Present study evaluates the possibility of distinguishing between benign and malignant breast tumors using various texture features. Materials...... and Methods: 58 cases of breast tumor (29 each from benign and malignant) were documented under standardized conditions using a linear array machine and 7.5 MHz transducer. In each sonographic image, ROI of tumor was marked and then subjected to the evaluation of tumor status using five parameters of second...... performance ROC= 0.78(pbenign and malignant tumors. It also reveals that when evaluating images of a breast tumor...

Making Biology Relevant to Undergraduates

Science.gov (United States)

Musante, Susan

2012-01-01

This article features Science Education for New Civic Engagements and Responsibilities (SENCER; www.sencer.net) Summer Institute. The SENCER program, which began formally in 2001, was the vision of David Burns; Karen Oates, currently Peterson Family Dean of Arts and Sciences at Worcester Polytechnic Institute; and Ric Wiebl, currently director of…

6,7-dimethoxy-coumarin as a probe of hydration dynamics in biologically relevant systems

Science.gov (United States)

Ghose, Avisek; Amaro, Mariana; Kovaricek, Petr; Hof, Martin; Sykora, Jan

2018-04-01

Coumarin derivatives are well known fluorescence reporters for investigating biological systems due to their strong micro-environment sensitivity. Despite having wide range of environment sensitive fluorescence probes, the potential of 6,7-dimethoxy-coumarin has not been studied extensively so far. With a perspective of its use in protein studies, namely using the unnatural amino acid technology or as a substrate for hydrolase enzymes, we study acetyloxymethyl-6,7-dimethoxycoumarin (Ac-DMC). We investigate the photophysics and hydration dynamics of this dye in aerosol-OT (AOT) reverse micelles at various water contents using the time dependent fluorescence shift (TDFS) method. The TDFS response in AOT reverse micelles from water/surfactant ratio of 0 to 20 confirms its sensitivity towards the hydration and mobility of its microenvironment. Moreover, we show that the fluorophore can be efficiently quenched by halide ions. Hence, we conclude that the 6,7-dimethoxy-methylcoumarin fluorophore is useful for studying hydration parameters in biologically relevant systems.

Biology relevant to space radiation

International Nuclear Information System (INIS)

Fry, R.J.M.

1997-01-01

There are only very limited data on the health effects to humans from the two major components of the radiations in space, namely protons and heavy ions. As a result, predictions of the accompanying effects must be based either on (1) data generated through studies of experimental systems exposed on earth at rates and fluences higher than those in space, or (2) extrapolations from studies of gamma and x rays. Better information is needed about the doses, dose rates, and the energy and LET spectra of the radiations at the organ level that are anticipated to be encountered during extended space missions. In particular, there is a need for better estimates of the relationship between radiation quality and biological effects. In the case of deterministic effects, it is the threshold that is important. The possibility of the occurrence of a large solar particle event (SPE) requires that such effects be considered during extended space missions. Analyses suggest, however, that it is feasible to provide sufficient shielding so as to reduce such effects to acceptable levels, particularly if the dose rates can be limited. If these analyses prove correct, the primary biological risks will be the stochastic effects (latent cancer induction). The contribution of one large SPE to the risk of stochastic effects while undesirable will not be large in comparison to the potential total dose on a mission of long duration

Inactivation of the antibacterial and cytotoxic properties of silver ions by biologically relevant compounds.

Directory of Open Access Journals (Sweden)

Geraldine Mulley

Full Text Available There has been a recent surge in the use of silver as an antimicrobial agent in a wide range of domestic and clinical products, intended to prevent or treat bacterial infections and reduce bacterial colonization of surfaces. It has been reported that the antibacterial and cytotoxic properties of silver are affected by the assay conditions, particularly the type of growth media used in vitro. The toxicity of Ag+ to bacterial cells is comparable to that of human cells. We demonstrate that biologically relevant compounds such as glutathione, cysteine and human blood components significantly reduce the toxicity of silver ions to clinically relevant pathogenic bacteria and primary human dermal fibroblasts (skin cells. Bacteria are able to grow normally in the presence of silver nitrate at >20-fold the minimum inhibitory concentration (MIC if Ag+ and thiols are added in a 1:1 ratio because the reaction of Ag+ with extracellular thiols prevents silver ions from interacting with cells. Extracellular thiols and human serum also significantly reduce the antimicrobial activity of silver wound dressings Aquacel-Ag (Convatec and Acticoat (Smith & Nephew to Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli in vitro. These results have important implications for the deployment of silver as an antimicrobial agent in environments exposed to biological tissue or secretions. Significant amounts of money and effort have been directed at the development of silver-coated medical devices (e.g. dressings, catheters, implants. We believe our findings are essential for the effective design and testing of antimicrobial silver coatings.

Wet meadow ecosystems and the longevity of biologically-mediated geomorphic features

Science.gov (United States)

Nash, C.; Grant, G.; O'Connor, J. E.

2016-12-01

Upland meadows represent a ubiquitous feature of montane landscapes in the U.S. West and beyond. Characterized by flat valley floors flanked by higher-gradient hillslopes, these meadows are important features, both for the diverse ecosystems they support but also because they represent depositional features in what is primarily an erosional environment. As such, they serve as long-term chronometers of both geological and ecological processes in a portion of the landscape where such records are rare, and provide a useful microcosm for exploring many of the questions motivating critical zone science. Specifically, meadows can offer insights into questions regarding the longevity of theses biologically-mediated landscapes, and the geomorphic thresholds associated with transitions between metastable landscape states. Though categorically depositional, wet meadows have been shown to rapidly shift into erosional landscapes characterized by deep arroyos, declining water tables, and sparse, semi-arid ecosystems. Numerous hypotheses have been proposed explaining this shift: intensive ungulate usage, removal of beaver, climatic shifts, and intrinsic geomorphic evolution. Even less is known about the mechanisms controlling the construction of these meadow features. Evidence seems to suggest these channels oscillate between two metastable conditions: deeply incised, single-threaded channels and sheet-flow dominated valley-spanning wetlands. We present new evidence exploring the subsurface architecture of wet meadows and the bidirectional process cascades potentially responsible for their temporal evolution. Using a combination of near surface geophysical techniques and detailed stratigraphic descriptions of incised and un-incised meadows throughout the Silvies River Basin, OR, we examine mechanisms responsible both for the construction of these features and their apparently rapid transition from depositional to erosional. Our investigation focuses specifically on potential

Carcinogenesis-relevant biological events in the pathophysiology of the efferocytosis phenomenon

Directory of Open Access Journals (Sweden)

Gargi Sachin Sarode

2017-12-01

Full Text Available The effective removal of cells undergoing programmed cell death, which is referred to as efferocytosis, prevents the leakage of intracellular contents into the surrounding tissue, which could lead to tissue damage and inflammation. Efferocytosis involves a coordinated orchestration of multiple steps that lead to a swift, coherent and immunologically silent removal of dying cells. The release of wound healing cytokines, which resolve inflammation and enhance tissue repair, is an important feature of efferocytosis. However, in addition to the healing cytokines released during efferocytosis, the immunosuppressive action of cytokines promotes the tumor microenvironment, enhances the motility of cancer cells and promotes the evasion of antitumor immunity. The aim of the present review was to comprehensively discuss the efferocytosis phenomenon, the important players associated with this process and their role in cancer-related biological events.

Clinical and biological features of multiple myeloma involving the gastrointestinal system.

Science.gov (United States)

Talamo, Giampaolo; Cavallo, Federica; Zangari, Maurizio; Barlogie, Bart; Lee, Choon-Kee; Pineda-Roman, Mauricio; Kiwan, Elias; Krishna, Somashekar; Tricot, Guido

2006-07-01

We report 24 cases of multiple myeloma (MM) with involvement of the gastrointestinal (GI) system. We found a strong association with high A lactate dehydrogenase levels, plasmablastic morphology, and A unfavorable karyotype. GI involvement at the time of initial diagnosis was much rarer than later in the course of the disease. The A median survival after diagnosis of GI involvement was 7 months. Among 13 patients treated with stem cell transplantation, the response rate was 92%, and median progression-free survival was 4 months. We conclude that MM involving the GI system is associated with adverse biological features and with short-lasting remissions, even after A high-dose chemotherapy.

An algorithm for finding biologically significant features in microarray data based on a priori manifold learning.

Directory of Open Access Journals (Sweden)

Zena M Hira

Full Text Available Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap.

Gregory Bateson's relevance to current molecular biology

DEFF Research Database (Denmark)

Bruni, Luis Emilio

2008-01-01

in a developmental pathway. Being a central figure in the development of cybernetic theory he collaborated with a range of researchers from the life sciences who were innovating their own disciplines by introducing cybernetic concepts in their particular fields and disciplines. In the light of this, it should...... not come as a surprise today to realize how the general ideas that he was postulating for the study of communication systems in biology fit so well with the astonishing findings of current molecular biology, for example in the field of cellular signal transduction networks. I guess this is the case due...

Floral features, pollination biology and breeding system of Chloraea membranacea Lindl. (Orchidaceae: Chloraeinae).

Science.gov (United States)

Sanguinetti, Agustin; Buzatto, Cristiano Roberto; Pedron, Marcelo; Davies, Kevin L; Ferreira, Pedro Maria de Abreu; Maldonado, Sara; Singer, Rodrigo B

2012-12-01

The pollination biology of very few Chloraeinae orchids has been studied to date, and most of these studies have focused on breeding systems and fruiting success. Chloraea membranacea Lindl. is one of the few non-Andean species in this group, and the aim of the present contribution is to elucidate the pollination biology, functional floral morphology and breeding system in native populations of this species from Argentina (Buenos Aires) and Brazil (Rio Grande do Sul State). Floral features were examined using light microscopy, and scanning and transmission electron microscopy. The breeding system was studied by means of controlled pollinations applied to plants, either bagged in the field or cultivated in a glasshouse. Pollination observations were made on natural populations, and pollinator behaviour was recorded by means of photography and video. Both Argentinean and Brazilian plants were very consistent regarding all studied features. Flowers are nectarless but scented and anatomical analysis indicates that the dark, clavate projections on the adaxial labellar surface are osmophores (scent-producing glands). The plants are self-compatible but pollinator-dependent. The fruit-set obtained through cross-pollination and manual self-pollination was almost identical. The main pollinators are male and female Halictidae bees that withdraw the pollinarium when leaving the flower. Remarkably, the bees tend to visit more than one flower per inflorescence, thus promoting self-pollination (geitonogamy). Fruiting success in Brazilian plants reached 60·78 % in 2010 and 46 % in 2011. Some pollinarium-laden female bees were observed transferring pollen from the carried pollinarium to their hind legs. The use of pollen by pollinators is a rare record for Orchidaceae in general. Chloraea membrancea is pollinated by deceit. Together, self-compatibility, pollinarium texture, pollinator abundance and behaviour may account for the observed high fruiting success. It is suggested that

Feature Selection via Chaotic Antlion Optimization.

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Hossam M Zawbaa

Full Text Available Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting while minimizing the number of features used.We propose an optimization approach for the feature selection problem that considers a "chaotic" version of the antlion optimizer method, a nature-inspired algorithm that mimics the hunting mechanism of antlions in nature. The balance between exploration of the search space and exploitation of the best solutions is a challenge in multi-objective optimization. The exploration/exploitation rate is controlled by the parameter I that limits the random walk range of the ants/prey. This variable is increased iteratively in a quasi-linear manner to decrease the exploration rate as the optimization progresses. The quasi-linear decrease in the variable I may lead to immature convergence in some cases and trapping in local minima in other cases. The chaotic system proposed here attempts to improve the tradeoff between exploration and exploitation. The methodology is evaluated using different chaotic maps on a number of feature selection datasets. To ensure generality, we used ten biological datasets, but we also used other types of data from various sources. The results are compared with the particle swarm optimizer and with genetic algorithm variants for feature selection using a set of quality metrics.

Carbon-13 NMR spectroscopy of biological systems

CERN Document Server

Beckmann, Nicolau

1995-01-01

This book is intended to provide an in-depth understanding of 13C NMR as a tool in biological research. 13C NMR has provided unique information concerning complex biological systems, from proteins and nucleic acids to animals and humans. The subjects addressed include multidimensional heteronuclear techniques for structural studies of molecules in the liquid and solid states, the investigation of interactions in model membranes, the elucidation of metabolic pathwaysin vitro and in vivo on animals, and noninvasive metabolic studies performed on humans. The book is a unique mix of NMR methods and biological applications which makes it a convenient reference for those interested in research in this interdisciplinary area of physics, chemistry, biology, and medicine.Key Features* An interdisciplinary text with emphasis on both 13C NMR methodology and the relevant biological and biomedical issues* State-of-the-art 13C NMR techniques are described; Whenever possible, their advantages over other approaches are empha...

A rapid Q-PCR titration protocol for adenovirus and helper-dependent adenovirus vectors that produces biologically relevant results

Science.gov (United States)

Gallaher, Sean D.; Berk, Arnold J.

2013-01-01

Adenoviruses are employed in the study of cellular processes and as expression vectors used in gene therapy. The success and reproducibility of these studies is dependent in part on having accurate and meaningful titers of replication competent and helper-dependent adenovirus stocks, which is problematic due to the use of varied and divergent titration protocols. Physical titration methods, which quantify the total number of viral particles, are used by many, but are poor at estimating activity. Biological titration methods, such as plaque assays, are more biologically relevant, but are time consuming and not applicable to helper-dependent gene therapy vectors. To address this, a protocol was developed called “infectious genome titration” in which viral DNA is isolated from the nuclei of cells ~3 h post-infection, and then quantified by Q-PCR. This approach ensures that only biologically active virions are counted as part of the titer determination. This approach is rapid, robust, sensitive, reproducible, and applicable to all forms of adenovirus. Unlike other Q-PCR-based methods, titers determined by this protocol are well correlated with biological activity. PMID:23624118

Assessing the relevance of ecotoxicological studies for regulatory decision making.

Science.gov (United States)

Rudén, Christina; Adams, Julie; Ågerstrand, Marlene; Brock, Theo Cm; Poulsen, Veronique; Schlekat, Christian E; Wheeler, James R; Henry, Tala R

2017-07-01

Regulatory policies in many parts of the world recognize either the utility of or the mandate that all available studies be considered in environmental or ecological hazard and risk assessment (ERA) of chemicals, including studies from the peer-reviewed literature. Consequently, a vast array of different studies and data types need to be considered. The first steps in the evaluation process involve determining whether the study is relevant to the ERA and sufficiently reliable. Relevance evaluation is typically performed using existing guidance but involves application of "expert judgment" by risk assessors. In the present paper, we review published guidance for relevance evaluation and, on the basis of the practical experience within the group of authors, we identify additional aspects and further develop already proposed aspects that should be considered when conducting a relevance assessment for ecotoxicological studies. From a regulatory point of view, the overarching key aspect of relevance concerns the ability to directly or indirectly use the study in ERA with the purpose of addressing specific protection goals and ultimately regulatory decision making. Because ERA schemes are based on the appropriate linking of exposure and effect estimates, important features of ecotoxicological studies relate to exposure relevance and biological relevance. Exposure relevance addresses the representativeness of the test substance, environmental exposure media, and exposure regime. Biological relevance deals with the environmental significance of the test organism and the endpoints selected, the ecological realism of the test conditions simulated in the study, as well as a mechanistic link of treatment-related effects for endpoints to the protection goal identified in the ERA. In addition, uncertainties associated with relevance should be considered in the assessment. A systematic and transparent assessment of relevance is needed for regulatory decision making. The relevance

Stability of silver nanoparticles: agglomeration and oxidation in biological relevant conditions

Science.gov (United States)

Valenti, Laura E.; Giacomelli, Carla E.

2017-05-01

Silver nanoparticles (Ag-NP) are the most used nanomaterial in consumer products due to the intrinsic antimicrobial capacity of silver. However, Ag-NP may be also harmful to algae, aquatic species, mammalian cells, and higher plants because both Ag+ and nanoparticles are responsible of cell damages. The oxidative dissolution of Ag-NP would proceed to completion under oxic conditions, but the rate and extent of the dissolution depend on several factors. This work correlates the effect of the capping agent (albumin and citrate) with the stability of Ag-NP towards agglomeration in simulated body fluid (SBF) and oxidation in the presence of ROS species (H2O2). Capping provides colloidal stability only through electrostatic means, whereas albumin acts as bulky ligands giving steric and electrostatic repulsion, inhibiting the agglomeration in SBF. However, citrate capping protects Ag-NP from dissolution to a major extent than albumin does because of its reducing power. Moreover, citrate in solution minimizes the oxidation of albumin-coated Ag-NP even after long incubation times. H2O2-induced dissolution proceeds to completion with Ag-NP incubated in SBF, while incubation in citrate leads to an incomplete oxidation. In short, albumin is an excellent capping agent to minimize Ag-NP agglomeration whereas citrate provides a mild-reductive medium that prevents dissolution in biological relevant media as well as in the presence of ROS species. These results provide insight into how the surface properties and media composition affect the release of Ag+ from Ag-NP, related to the cell toxicity and relevant to the storage and lifetime of silver-containing nanomaterials.

Stability of silver nanoparticles: agglomeration and oxidation in biological relevant conditions

Energy Technology Data Exchange (ETDEWEB)

Valenti, Laura E.; Giacomelli, Carla E., E-mail: giacomel@fcq.unc.edu.ar [Universidad Nacional de Córdoba, Ciudad Universitaria, Instituto de Investigaciones en Físico Química de Córdoba (INFIQC) CONICET-UNC, Departamento de Fisicoquímica, Facultad de Ciencias Químicas (Argentina)

2017-05-15

Silver nanoparticles (Ag-NP) are the most used nanomaterial in consumer products due to the intrinsic antimicrobial capacity of silver. However, Ag-NP may be also harmful to algae, aquatic species, mammalian cells, and higher plants because both Ag{sup +} and nanoparticles are responsible of cell damages. The oxidative dissolution of Ag-NP would proceed to completion under oxic conditions, but the rate and extent of the dissolution depend on several factors. This work correlates the effect of the capping agent (albumin and citrate) with the stability of Ag-NP towards agglomeration in simulated body fluid (SBF) and oxidation in the presence of ROS species (H{sub 2}O{sub 2}). Capping provides colloidal stability only through electrostatic means, whereas albumin acts as bulky ligands giving steric and electrostatic repulsion, inhibiting the agglomeration in SBF. However, citrate capping protects Ag-NP from dissolution to a major extent than albumin does because of its reducing power. Moreover, citrate in solution minimizes the oxidation of albumin-coated Ag-NP even after long incubation times. H{sub 2}O{sub 2}-induced dissolution proceeds to completion with Ag-NP incubated in SBF, while incubation in citrate leads to an incomplete oxidation. In short, albumin is an excellent capping agent to minimize Ag-NP agglomeration whereas citrate provides a mild-reductive medium that prevents dissolution in biological relevant media as well as in the presence of ROS species. These results provide insight into how the surface properties and media composition affect the release of Ag{sup +} from Ag-NP, related to the cell toxicity and relevant to the storage and lifetime of silver-containing nanomaterials.

Economical and Morpho-Biological Features of Whiner Wheat New Generation Varieties (Triticum durum

Directory of Open Access Journals (Sweden)

Л. І. Улич

2010-10-01

Full Text Available The article describes summary of the researches, characteristics of morphological and agro-biological characteristics and features, a note is made of a significant progress in the selection of productivity and adaptability of registered Durum Winter Wheat Varieties of new crops rotation. Significant developments of  plants architectonic are marked, especially in height, characteristics of economical value, and in terms of considerable achievements in breeding of this kind of wheat. A stress in made on the need to enhance Durum Winter Wheat breeding to develop more frostresistant and drought-overheat resistant varieties.

MIBG avidity correlates with clinical features, tumor biology, and outcomes in neuroblastoma: A report from the Children's Oncology Group.

Science.gov (United States)

DuBois, Steven G; Mody, Rajen; Naranjo, Arlene; Van Ryn, Collin; Russ, Douglas; Oldridge, Derek; Kreissman, Susan; Baker, David L; Parisi, Marguerite; Shulkin, Barry L; Bai, Harrison; Diskin, Sharon J; Batra, Vandana; Maris, John M; Park, Julie R; Matthay, Katherine K; Yanik, Gregory

2017-11-01

Prior studies suggest that neuroblastomas that do not accumulate metaiodobenzylguanidine (MIBG) on diagnostic imaging (MIBG non-avid) may have more favorable features compared with MIBG avid tumors. We compared clinical features, biologic features, and clinical outcomes between patients with MIBG nonavid and MIBG avid neuroblastoma. Patients had metastatic high- or intermediate-risk neuroblastoma and were treated on Children's Oncology Group protocols A3973 or A3961. Comparisons of clinical and biologic features according to MIBG avidity were made with chi-squared or Fisher exact tests. Event-free (EFS) and overall (OS) survival compared using log-rank tests and modeled using Cox models. Thirty of 343 patients (8.7%) had MIBG nonavid disease. Patients with nonavid tumors were less likely to have adrenal primary tumors (34.5 vs. 57.2%; P = 0.019), bone metastases (36.7 vs. 61.7%; P = 0.008), or positive urine catecholamines (66.7 vs. 91.0%; P neuroblastoma have lower rates of adrenal primary tumors, bone metastasis, and catecholamine secretion. Despite being more likely to have MYCN-amplified tumors, these patients have superior outcomes compared with patients with MIBG avid disease. © 2017 Wiley Periodicals, Inc.

Some nonlinear challenges in biology

International Nuclear Information System (INIS)

Mosconi, Francesco; Julou, Thomas; Desprat, Nicolas; Sinha, Deepak Kumar; Allemand, Jean-François; Croquette, Vincent; Bensimon, David

2008-01-01

Driven by a deluge of data, biology is undergoing a transition to a more quantitative science. Making sense of the data, building new models, asking the right questions and designing smart experiments to answer them are becoming ever more relevant. In this endeavour, nonlinear approaches can play a fundamental role. The biochemical reactions that underlie life are very often nonlinear. The functional features exhibited by biological systems at all levels (from the activity of an enzyme to the organization of a colony of ants, via the development of an organism or a functional module like the one responsible for chemotaxis in bacteria) are dynamically robust. They are often unaffected by order of magnitude variations in the dynamical parameters, in the number or concentrations of actors (molecules, cells, organisms) or external inputs (food, temperature, pH, etc). This type of structural robustness is also a common feature of nonlinear systems, exemplified by the fundamental role played by dynamical fixed points and attractors and by the use of generic equations (logistic map, Fisher–Kolmogorov equation, the Stefan problem, etc.) in the study of a plethora of nonlinear phenomena. However, biological systems differ from these examples in two important ways: the intrinsic stochasticity arising from the often very small number of actors and the role played by evolution. On an evolutionary time scale, nothing in biology is frozen. The systems observed today have evolved from solutions adopted in the past and they will have to adapt in response to future conditions. The evolvability of biological system uniquely characterizes them and is central to biology. As the great biologist T Dobzhansky once wrote: 'nothing in biology makes sense except in the light of evolution'. (open problem)

Association of MYCN copy number with clinical features, tumor biology, and outcomes in neuroblastoma: A report from the Children's Oncology Group.

Science.gov (United States)

Campbell, Kevin; Gastier-Foster, Julie M; Mann, Meegan; Naranjo, Arlene H; Van Ryn, Collin; Bagatell, Rochelle; Matthay, Katherine K; London, Wendy B; Irwin, Meredith S; Shimada, Hiroyuki; Granger, M Meaghan; Hogarty, Michael D; Park, Julie R; DuBois, Steven G

2017-11-01

High-level MYCN amplification (MNA) is associated with poor outcome and unfavorable clinical and biological features in patients with neuroblastoma. To the authors' knowledge, less is known regarding these associations in patients with low-level MYCN copy number increases. In this retrospective study, the authors classified patients has having tumors with MYCN wild-type tumors, MYCN gain (2-4-fold increase in MYCN signal compared with the reference probe), or MNA (>4-fold increase). Tests of trend were used to investigate ordered associations between MYCN copy number category and features of interest. Log-rank tests and Cox models compared event-free survival and overall survival by subgroup. Among 4672 patients, 3694 (79.1%) had MYCN wild-type tumors, 133 (2.8%) had MYCN gain, and 845 (18.1%) had MNA. For each clinical/biological feature, the percentage of patients with an unfavorable feature was lowest in the MYCN wild-type category, intermediate in the MYCN gain category, and highest in the MNA category (PNeuroblastoma Staging System) and patients with non-high-risk disease with MYCN gain had a significantly increased risk for death, a finding confirmed on multivariable testing. Increasing MYCN copy number is associated with an increasingly higher rate of unfavorable clinical/biological features, with 11q aberration being an exception. Patients with MYCN gain appear to have inferior outcomes, especially in otherwise more favorable groups. Cancer 2017;123:4224-4235. © 2017 American Cancer Society. © 2017 American Cancer Society.

Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

Science.gov (United States)

Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

2013-02-01

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Copyright © 2012 Wiley Periodicals, Inc.

Numerical Analysis for Relevant Features in Intrusion Detection (NARFid)

Science.gov (United States)

2009-03-01

Error and Average Correlation Coefficient. Mucciardi and Gose [63] discuss seven methods for selecting features. These methods seek to overcome the...POEmaxPOEmin). (2.37) With each iteration of selecting the next feature, ACC is also normalized in the same fashion. As stated by Mucciardi and Gose ...lan’s discussion [70] as described in Section 2.3.1. Mucciardi and Gose [63] provide the POEACC parameters that perform well in their experiments. As

Elements determination of clinical relevance in biological tissues Dmdmdx/J dystrophic mice strains investigated by NAA

International Nuclear Information System (INIS)

Metairon, Sabrina

2012-01-01

In this work the determination of chemistry elements in biological tissues (whole blood, bones and organs) of dystrophic mice, used as animal model of Duchenne Muscular Dystrophy (DMD), was performed using analytical nuclear technique. The aim of this work was to determine reference values of elements of clinical (Ca, Cl, K, Mg, Na) and nutritional (Br and S) relevance in whole blood, tibia, quadriceps and hearts from Dmdmdx/J (10 males and 10 females) dystrophic mice and C57BL/6J (10 males) control group mice, using Neutron Activation Analysis technique (NAA). To show in more details the alterations that this disease may cause in these biological tissues, correlations matrixes of the DMD mdx /J mouse strain were generated and compared with C57BL/6J control group. For this study 119 samples of biological tissue were irradiated in the IEA-R1 nuclear reactor at IPEN (Sao Paulo, Brazil). The concentrations of these elements in biological tissues of Dmd mdx /J and C57B/6J mice are the first indicative interval for reference values. Moreover, the alteration in some correlation coefficients data among the elements in the health status and in the diseased status indicates a connection between these elements in whole blood, tibia, quadriceps and heart. These results may help the researchers to evaluate the efficiency of new treatments and to compare the advantages of different treatment approaches before performing tests in patients with muscular dystrophy. (author)

Development of the Biology Card Sorting Task to Measure Conceptual Expertise in Biology

Science.gov (United States)

Smith, Julia I.; Combs, Elijah D.; Nagami, Paul H.; Alto, Valerie M.; Goh, Henry G.; Gourdet, Muryam A. A.; Hough, Christina M.; Nickell, Ashley E.; Peer, Adrian G.; Coley, John D.; Tanner, Kimberly D.

2013-01-01

There are widespread aspirations to focus undergraduate biology education on teaching students to think conceptually like biologists; however, there is a dearth of assessment tools designed to measure progress from novice to expert biological conceptual thinking. We present the development of a novel assessment tool, the Biology Card Sorting Task, designed to probe how individuals organize their conceptual knowledge of biology. While modeled on tasks from cognitive psychology, this task is unique in its design to test two hypothesized conceptual frameworks for the organization of biological knowledge: 1) a surface feature organization focused on organism type and 2) a deep feature organization focused on fundamental biological concepts. In this initial investigation of the Biology Card Sorting Task, each of six analytical measures showed statistically significant differences when used to compare the card sorting results of putative biological experts (biology faculty) and novices (non–biology major undergraduates). Consistently, biology faculty appeared to sort based on hypothesized deep features, while non–biology majors appeared to sort based on either surface features or nonhypothesized organizational frameworks. Results suggest that this novel task is robust in distinguishing populations of biology experts and biology novices and may be an adaptable tool for tracking emerging biology conceptual expertise. PMID:24297290

Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

CERN Document Server

Pisharady, Pramod Kumar; Poh, Loh Ai

2014-01-01

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

Extracellular membrane vesicles in blood products-biology and clinical relevance

Directory of Open Access Journals (Sweden)

Emilija Krstova Krajnc

2016-01-01

Full Text Available Extracellular membrane vesicles are fragments shed from plasma membranes off all cell types that are undergoing apoptosis or are being subjected to various types of stimulation or stress.  Even in the process of programmed cell death (apoptosis, cell fall apart of varying size vesicles. They expose phosphatidylserine (PS on the outer leaflet of their membrane, and bear surface membrane antigens reflecting their cellular origin. Extracellular membrane vesicles have been isolated from many types of biological fluids, including serum, cerebrospinal fluid, urine, saliva, tears and conditioned culture medium. Flow cytometry is one of the many different methodological approaches that have been used to analyze EMVs. The method attempts to characterize the EMVs cellular origin, size, population, number, and structure. EMVs are present and accumulate in blood products (erythrocytes, platelets as well as in fresh frozen plasma during storage. The aim of this review is to highlight the importance of extracellular vesicles as a cell-to-cell communication system and the role in the pathogenesis of different diseases. Special emphasis will be given to the implication of extracellular membrane vesicles in blood products and their clinical relevance. Although our understanding of the role of  EMVs in disease is far from comprehensive, they display promise as biomarkers for different diseases in the future and also as a marker of quality and safety in the quality control of blood products.

Understanding psychiatric disorder by capturing ecologically relevant features of learning and decision-making.

Science.gov (United States)

Scholl, Jacqueline; Klein-Flügge, Miriam

2017-09-28

Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms. Here we propose that using computational models with tasks that capture ecologically relevant learning and decision-making processes may provide a critical advantage for capturing the mechanisms underlying symptoms of disorders in psychiatry. As a result, it may help develop mechanistic approaches towards diagnosis and treatment. We begin this review by mapping out the basic concepts and models of learning and decision-making. We then move on to consider specific challenges that emerge in realistic environments and describe how they can be captured by tasks. These include changes of context, uncertainty, reflexive/emotional biases, cost-benefit decision-making, and balancing exploration and exploitation. Where appropriate we highlight future or current links to psychiatry. We particularly draw examples from research on clinical depression, a disorder that greatly compromises motivated behaviours in real-life, but where simpler paradigms have yielded mixed results. Finally, we highlight several paradigms that could be used to help provide new insights into the mechanisms of psychiatric disorders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Online feature selection with streaming features.

Science.gov (United States)

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

2013-05-01

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

The clinical implications and biologic relevance of neurofilament expression in gastroenteropancreatic neuroendocrine neoplasms.

Science.gov (United States)

Schimmack, Simon; Lawrence, Ben; Svejda, Bernhard; Alaimo, Daniele; Schmitz-Winnenthal, Hubertus; Fischer, Lars; Büchler, Markus W; Kidd, Mark; Modlin, Irvin

2012-05-15

Although gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) exhibit widely divergent behavior, limited biologic information (apart from Ki-67) is available to characterize malignancy. Therefore, the identification of alternative biomarkers is a key unmet need. Given the role of internexin alpha (INA) in neuronal development, the authors assessed its function in neuroendocrine cell systems and the clinical implications of its expression as a GEP-NEN biomarker. Functional assays were undertaken to investigate the mechanistic role of INA in the pancreatic BON cell line. Expression levels of INA were investigated in 50 pancreatic NENs (43 primaries, 7 metastases), 43 small intestinal NENs (25 primaries, 18 metastases), normal pancreas (n = 10), small intestinal mucosa (n = 16), normal enterochromaffin (EC) cells (n = 9), mouse xenografts (n = 4) and NEN cell lines (n = 6) using quantitative polymerase chain reaction, Western blot, and immunostaining analyses. In BON cells, decreased levels of INA messenger RNA and protein were associated with the inhibition of both proliferation and mitogen-activated protein kinase (MAPK) signaling. INA was not expressed in normal neuroendocrine cells but was overexpressed (from 2-fold to 42-fold) in NEN cell lines and murine xenografts. In pancreatic NENs, INA was overexpressed compared with pancreatic adenocarcinomas and normal pancreas (27-fold [P = .0001], and 9-fold [P = .02], respectively). INA transcripts were correlated positively with Ki-67 (correlation coefficient [r] = 0.5; P biologic information relevant to delineation of both pancreatic NEN tumor phenotypes and clinical behavior. Copyright © 2011 American Cancer Society.

Understanding Protein-Protein Interactions Using Local Structural Features

DEFF Research Database (Denmark)

Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

Science.gov (United States)

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

Dose addition models based on biologically-relevant reductions in fetal testosterone accurately predict postnatal reproductive tract alterations by a phthalate mixture in rats

Science.gov (United States)

Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the curren...

Mapping genomic features to functional traits through microbial whole genome sequences.

Science.gov (United States)

Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott

2014-01-01

Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

Clinicopathological variables of sporadic schwannomas of peripheral nerve in 291 patients and expression of biologically relevant markers.

Science.gov (United States)

Young, Eric D; Ingram, Davis; Metcalf-Doetsch, William; Khan, Dilshad; Al Sannaa, Ghadah; Le Loarer, Francois; Lazar, Alexander J F; Slopis, John; Torres, Keila E; Lev, Dina; Pollock, Raphael E; McCutcheon, Ian E

2017-09-08

OBJECTIVE While sporadic peripheral schwannomas (SPSs) are generally well treated with surgery, their biology is not well understood. Consequently, treatment options are limited. The aim of this study was to provide a comprehensive description of SPS. The authors describe clinicopathological features and treatment outcomes of patients harboring these tumors, and they assess expression of biomarkers using a clinically annotated tissue microarray. Together, these data give new insight into the biology and management of SPS. METHODS Patients presenting with a primary SPS between 1993 and 2011 (n = 291) were selected from an institutional registry to construct a clinical database. All patients underwent follow-up, and short- and long-term outcomes were assessed. Expression of relevant biomarkers was assessed using a new tissue microarray (n = 121). RESULTS SPSs were generally large (mean 5.5 cm) and frequently painful at presentation (55%). Most patients were treated with surgery (80%), the majority of whom experienced complete resolution (52%) or improvement (18%) of their symptoms. Tumors that were completely resected (85%) did not recur. Some patients experienced short-term (16%) and long-term (4%) complications postoperatively. Schwannomas expressed higher levels of platelet-derived growth factor receptor-β (2.1) than malignant peripheral nerve sheath tumors (MPNSTs) (1.5, p = 0.004) and neurofibromas (1.33, p = 0.007). Expression of human epidermal growth factor receptor-2 was greater in SPSs (0.91) than in MPNSTs (0.33, p = 0.002) and neurofibromas (0.33, p = 0.026). Epidermal growth factor receptor was expressed in far fewer SPS cells (10%) than in MPNSTs (58%, p SPSs more frequently expressed cytoplasmic survivin (66% of tumor cells) than normal nerve (46% of cells), but SPS expressed nuclear survivin in fewer tumor cells than in MPNSTs (24% and 50%, respectively; p = 0.018). CONCLUSIONS Complete resection is curative for SPS. Left untreated, however, these

Feature generation and representations for protein-protein interaction classification.

Science.gov (United States)

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification

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Nurhan Gursel Ozmen

2018-01-01

Full Text Available Classification of electroencephalogram (EEG signal is important in mental decoding for brain-computer interfaces (BCI. We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on different mental tasks using single-channel EEG. This biologically inspired method extracts the most discriminative spectral features from power spectral densities (PSDs of the EEG signals. We applied our method on a dataset of six subjects who performed five different imagination tasks: (i resting state, (ii mental arithmetic, (iii imagination of left hand movement, (iv imagination of right hand movement, and (v imagination of letter “A.” Pairwise and multiclass classifications were performed in single EEG channel using Linear Discriminant Analysis and Support Vector Machines. Our method produced results (mean classification accuracy of 83.06% for binary classification and 91.85% for multiclassification that are on par with the state-of-the-art methods, using single-channel EEG with low computational cost. Among all task pairs, mental arithmetic versus letter imagination yielded the best result (mean classification accuracy of 90.29%, indicating that this task pair could be the most suitable pair for a binary class BCI. This study contributes to the development of single-channel BCI, as well as finding the best task pair for user defined applications.

Biological Assets in Companies in Brazil: Pursuant To CPC 29 and Association with Business Features

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Vinicius Martins Macedo

2015-12-01

Full Text Available The adoption of international accounting standards in Brazil has brought about changes in the form of recognition, measurement and disclosure of economic facts of companies. In order to harmonize the accounting standards with the international standard-setting bodies Brazilian approved CPC 29, which establishes the accounting treatment and disclosure of biological assets and agricultural products. The objective of this study was to verify the Brazilian companies with biological assets the level of compliance with the CPC 29 and its association with business features. The study adopted the descriptive approach and examined the consolidated Financial Statements for the year 2013 of Brazilian public companies. In total 19 companies were analyzed showed that biological assets in 2013. The survey results show that the average compliance of companies with CPC 29 is 74.68%. Regarding the statistical analysis, it was observed that the level of compliance of companies have associations with business characteristics such as sector, governance, size, profitability and representativeness of the asset and the company's size has significant interaction with the level of accordingly. Compared to previous studies it was found that there was a significant increase in company compliance level with CPC 29 over time

A meta-analysis of the abscopal effect in preclinical models: Is the biologically effective dose a relevant physical trigger?

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Raffaella Marconi

Full Text Available Preclinical in vivo studies using small animals are considered crucial in translational cancer research and clinical implementation of novel treatments. This is of paramount relevance in radiobiology, especially for any technological developments permitted to deliver high doses in single or oligo-fractionated regimens, such as stereotactic ablative radiotherapy (SABR. In this context, clinical success in cancer treatment needs to be guaranteed, sparing normal tissue and preventing the potential spread of disease or local recurrence. In this work we introduce a new dose-response relationship based on relevant publications concerning preclinical models with regard to delivered dose, fractionation schedule and occurrence of biological effects on non-irradiated tissue, abscopal effects.We reviewed relevant publications on murine models and the abscopal effect in radiation cancer research following PRISMA methodology. In particular, through a log-likelihood method, we evaluated whether the occurrence of abscopal effects may be related to the biologically effective dose (BED. To this aim, studies accomplished with different tumor histotypes were considered in our analysis including breast, colon, lung, fibrosarcoma, pancreas, melanoma and head and neck cancer. For all the tumors, the α / β ratio was assumed to be 10 Gy, as generally adopted for neoplastic cells.Our results support the hypothesis that the occurrence rate of abscopal effects in preclinical models increases with BED. In particular, the probability of revealing abscopal effects is 50% when a BED of 60 Gy is generated.Our study provides evidence that SABR treatments associated with high BEDs could be considered an effective strategy in triggering the abscopal effect, thus shedding light on the promising outcomes revealed in clinical practice.

The endocannabinoid system and its relevance for nutrition

DEFF Research Database (Denmark)

Maccarrone, Mauro; Gasperi, Valeria; Catani, Maria Valeria

2010-01-01

Endocannabinoids bind to cannabinoid, vanilloid, and peroxisome proliferator-activated receptors. The biological actions of these polyunsaturated lipids are controlled by key agents responsible for their synthesis, transport and degradation, which together form an endocannabinoid system (ECS......). In the past few years, evidence has been accumulated for a role of the ECS in regulating food intake and energy balance, both centrally and peripherally. In addition, up-regulation of the ECS in the gastrointestinal tract has a potential impact on inflammatory bowel diseases. In this review, the main features...... of the ECS are summarized in order to put in better focus our current knowledge of the nutritional relevance of endocannabinoid signaling and of its role in obesity, cardiovascular pathologies, and gastrointestinal diseases. The central and peripheral pathways that underlie these effects are discussed...

Messina: a novel analysis tool to identify biologically relevant molecules in disease.

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Mark Pinese

Full Text Available BACKGROUND: Morphologically similar cancers display heterogeneous patterns of molecular aberrations and follow substantially different clinical courses. This diversity has become the basis for the definition of molecular phenotypes, with significant implications for therapy. Microarray or proteomic expression profiling is conventionally employed to identify disease-associated genes, however, traditional approaches for the analysis of profiling experiments may miss molecular aberrations which define biologically relevant subtypes. METHODOLOGY/PRINCIPAL FINDINGS: Here we present Messina, a method that can identify those genes that only sometimes show aberrant expression in cancer. We demonstrate with simulated data that Messina is highly sensitive and specific when used to identify genes which are aberrantly expressed in only a proportion of cancers, and compare Messina to contemporary analysis techniques. We illustrate Messina by using it to detect the aberrant expression of a gene that may play an important role in pancreatic cancer. CONCLUSIONS/SIGNIFICANCE: Messina allows the detection of genes with profiles typical of markers of molecular subtype, and complements existing methods to assist the identification of such markers. Messina is applicable to any global expression profiling data, and to allow its easy application has been packaged into a freely-available stand-alone software package.

TaBoo SeArch Algorithm with a Modified Inverse Histogram for Reproducing Biologically Relevant Rare Events of Proteins.

Science.gov (United States)

Harada, Ryuhei; Takano, Yu; Shigeta, Yasuteru

2016-05-10

The TaBoo SeArch (TBSA) algorithm [ Harada et al. J. Comput. Chem. 2015 , 36 , 763 - 772 and Harada et al. Chem. Phys. Lett. 2015 , 630 , 68 - 75 ] was recently proposed as an enhanced conformational sampling method for reproducing biologically relevant rare events of a given protein. In TBSA, an inverse histogram of the original distribution, mapped onto a set of reaction coordinates, is constructed from trajectories obtained by multiple short-time molecular dynamics (MD) simulations. Rarely occurring states of a given protein are statistically selected as new initial states based on the inverse histogram, and resampling is performed by restarting the MD simulations from the new initial states to promote the conformational transition. In this process, the definition of the inverse histogram, which characterizes the rarely occurring states, is crucial for the efficiency of TBSA. In this study, we propose a simple modification of the inverse histogram to further accelerate the convergence of TBSA. As demonstrations of the modified TBSA, we applied it to (a) hydrogen bonding rearrangements of Met-enkephalin, (b) large-amplitude domain motions of Glutamine-Binding Protein, and (c) folding processes of the B domain of Staphylococcus aureus Protein A. All demonstrations numerically proved that the modified TBSA reproduced these biologically relevant rare events with nanosecond-order simulation times, although a set of microsecond-order, canonical MD simulations failed to reproduce the rare events, indicating the high efficiency of the modified TBSA.

Culturally Relevant Cyberbullying Prevention

OpenAIRE

Phillips, Gregory John

2017-01-01

In this action research study, I, along with a student intervention committee of 14 members, developed a cyberbullying intervention for a large urban high school on the west coast. This high school contained a predominantly African American student population. I aimed to discover culturally relevant cyberbullying prevention strategies for African American students. The intervention committee selected video safety messages featuring African American actors as the most culturally relevant cyber...

Is the fluid mosaic (and the accompanying raft hypothesis a suitable model to describe fundamental features of biological membranes? What may be missing?

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Luis Alberto Bagatolli

2013-11-01

Full Text Available The structure, dynamics, and stability of lipid bilayers are controlled by thermodynamic forces, leading to overall tensionless membranes with a distinct lateral organization and a conspicuous lateral pressure profile. Bilayers are also subject to built-in curvature-stress instabilities that may be released locally or globally in terms of morphological changes leading to the formation of non-lamellar and curved structures. A key controller of the bilayer’s propensity to form curved structures is the average molecular shape of the different lipid molecules. Via the curvature stress, molecular shape mediates a coupling to membrane-protein function and provides a set of physical mechanisms for formation of lipid domains and laterally differentiated regions in the plane of the membrane. Unfortunately, these relevant physical features of membranes are often ignored in the most popular models for biological membranes. Results from a number of experimental and theoretical studies emphasize the significance of these fundamental physical properties and call for a refinement of the fluid mosaic model (and the accompanying raft hypothesis.

Morphological characters of the thickbody skate Amblyraja frerichsi (Krefft 1968) (Rajiformes: Rajidae), with notes on its biology.

Science.gov (United States)

Bustamante, Carlos; Lamilla, Julio; Concha, Francisco; Ebert, David A; Bennett, Michael B

2012-01-01

Detailed descriptions of morphological features, morphometrics, neurocranium anatomy, clasper structure and egg case descriptions are provided for the thickbody skate Amblyraja frerichsi; a rare, deep-water species from Chile, Argentina and Falkland Islands. The species diagnosis is complemented from new observations and aspects such as colour, size and distribution are described. Geographic and bathymetric distributional ranges are discussed as relevant features of this taxońs biology. Additionally, the conservation status is assessed including bycatch records from Chilean fisheries.

The clinical features of alcohol use disorders in biological and step-fathers that predict risk for alcohol use disorders in offspring.

Science.gov (United States)

Kendler, Kenneth S; Ohlsson, Henrik; Edwards, Alexis; Sundquist, Jan; Sundquist, Kristina

2017-12-01

Given that Alcohol Use Disorder (AUD) is clinically heterogeneous, can we, in a large epidemiological sample using public registries, identify clinical features of AUD cases in biological and step-fathers that index, respectively, genetic and familial-environmental risk for AUD in their offspring? From all father-offspring pairs where the father had AUD and the offspring was born 1960-1990, we identified not-lived-with (NLW) biological fathers (n = 38,376) and step-father pairs (n = 9,711). The relationship between clinical and historical features of the father's AUD and risk for AUD in offspring was assessed by linear hazard regression. Age at first registration for AUD and recurrence of AUD registration were significantly stronger predictors of risk for AUD in the offspring of NLW fathers than in step-fathers. By contrast, number of AUD registrations in NLW fathers and step-fathers were equally predictive of risk for AUD in offspring. However, while the number of step-father AUD registrations that occurred when he was living them with significantly predicted risk for AUD in his step-children, the number of registrations that occurred when not residing with his step-children was unassociated with their AUD risk. In an epidemiological sample, we could meaningfully differentiate between features of AUD in fathers that indexed genetic risk which was transmitted to biological offspring (early age at onset and recurrence) versus indexed environmental risk (registrations while rearing) which increased risk in step-children. © 2017 Wiley Periodicals, Inc.

Structural features that predict real-value fluctuations of globular proteins.

Science.gov (United States)

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Morphological characters of the thickbody skate Amblyraja frerichsi (Krefft 1968 (Rajiformes: Rajidae, with notes on its biology.

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Carlos Bustamante

Full Text Available Detailed descriptions of morphological features, morphometrics, neurocranium anatomy, clasper structure and egg case descriptions are provided for the thickbody skate Amblyraja frerichsi; a rare, deep-water species from Chile, Argentina and Falkland Islands. The species diagnosis is complemented from new observations and aspects such as colour, size and distribution are described. Geographic and bathymetric distributional ranges are discussed as relevant features of this taxońs biology. Additionally, the conservation status is assessed including bycatch records from Chilean fisheries.

Morphological Characters of the Thickbody Skate Amblyraja frerichsi (Krefft 1968) (Rajiformes: Rajidae), with Notes on Its Biology

Science.gov (United States)

Bustamante, Carlos; Lamilla, Julio; Concha, Francisco; Ebert, David A.; Bennett, Michael B.

2012-01-01

Detailed descriptions of morphological features, morphometrics, neurocranium anatomy, clasper structure and egg case descriptions are provided for the thickbody skate Amblyraja frerichsi; a rare, deep-water species from Chile, Argentina and Falkland Islands. The species diagnosis is complemented from new observations and aspects such as colour, size and distribution are described. Geographic and bathymetric distributional ranges are discussed as relevant features of this taxońs biology. Additionally, the conservation status is assessed including bycatch records from Chilean fisheries. PMID:22768186

Comprehension of complex biological processes by analytical methods: how far can we go using mass spectrometry?

International Nuclear Information System (INIS)

Gerner, C.

2013-01-01

Comprehensive understanding of complex biological processes is the basis for many biomedical issues of great relevance for modern society including risk assessment, drug development, quality control of industrial products and many more. Screening methods provide means for investigating biological samples without research hypothesis. However, the first boom of analytical screening efforts has passed and we again need to ask whether and how to apply screening methods. Mass spectrometry is a modern tool with unrivalled analytical capacities. This applies to all relevant characteristics of analytical methods such as specificity, sensitivity, accuracy, multiplicity and diversity of applications. Indeed, mass spectrometry qualifies to deal with complexity. Chronic inflammation is a common feature of almost all relevant diseases challenging our modern society; these diseases are apparently highly diverse and include arteriosclerosis, cancer, back pain, neurodegenerative diseases, depression and other. The complexity of mechanisms regulating chronic inflammation is the reason for the practical challenge to deal with it. The presentation shall give an overview of capabilities and limitations of the application of this analytical tool to solve critical questions with great relevance for our society. (author)

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

Science.gov (United States)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Gastric tumours in hereditary cancer syndromes: clinical features, molecular biology and strategies for prevention.

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Sereno, María; Aguayo, Cristina; Guillén Ponce, Carmen; Gómez-Raposo, César; Zambrana, Francisco; Gómez-López, Miriam; Casado, Enrique

2011-09-01

Gastric cancer is the major cause of cancer-related deaths worldwide. The majority of them are classified as sporadic, whereas the remaining 10% exhibit familial clustering. Hereditary diffuse gastric cancer (HDGC) syndrome is the most important condition that leads to hereditary gastric cancer. However, other hereditary cancer syndromes, such as hereditary non-polyposis colorectal cancer, familial adenomatous polyposis, Peutz-Jeghers syndrome, Li-Fraumeni syndrome and hereditary breast and ovarian cancer, entail a higher risk compared to the general population for developing this kind of neoplasia. In this review, we describe briefly the most important aspects related to clinical features, molecular biology and strategies for prevention in hereditary gastric associated to different cancer syndromes.

Monochloramine Cometabolism by Nitrifying Biofilm Relevant ...

Science.gov (United States)

Recently, biological monochloramine removal (i.e., cometabolism) by a pure culture ammonia–oxidizing bacteria, Nitrosomonas europaea, and a nitrifying mixed–culture have been shown to increase monochloramine demand. Although important, these previous suspended culture batch kinetic experiments were not representative of drinking water distribution systems where bacteria grow predominantly as biofilm attached to pipe walls or sediments and physiological differences may exist between suspension and biofilm growth. Therefore, the current research was an important next step in extending the previous results to investigate monochloramine cometabolism by biofilm grown in annular reactors under drinking water relevant conditions. Estimated monochloramine cometabolism kinetics were similar to those of ammonia metabolism, and monochloramine cometabolism was a significant loss mechanism (25–40% of the observed monochloramine loss). These results demonstrated that monochloramine cometabolism occurred in drinking water relevant nitrifying biofilm; thus, cometabolism may be a significant contribution to monochloramine loss during nitrification episodes in distribution systems. Investigate whether or not nitrifying biofilm can biologically transform monochloramine under drinking water relevant conditions.

Oculomotor selection underlies feature retention in visual working memory.

Science.gov (United States)

Hanning, Nina M; Jonikaitis, Donatas; Deubel, Heiner; Szinte, Martin

2016-02-01

Oculomotor selection, spatial task relevance, and visual working memory (WM) are described as three processes highly intertwined and sustained by similar cortical structures. However, because task-relevant locations always constitute potential saccade targets, no study so far has been able to distinguish between oculomotor selection and spatial task relevance. We designed an experiment that allowed us to dissociate in humans the contribution of task relevance, oculomotor selection, and oculomotor execution to the retention of feature representations in WM. We report that task relevance and oculomotor selection lead to dissociable effects on feature WM maintenance. In a first task, in which an object's location was encoded as a saccade target, its feature representations were successfully maintained in WM, whereas they declined at nonsaccade target locations. Likewise, we observed a similar WM benefit at the target of saccades that were prepared but never executed. In a second task, when an object's location was marked as task relevant but constituted a nonsaccade target (a location to avoid), feature representations maintained at that location did not benefit. Combined, our results demonstrate that oculomotor selection is consistently associated with WM, whereas task relevance is not. This provides evidence for an overlapping circuitry serving saccade target selection and feature-based WM that can be dissociated from processes encoding task-relevant locations. Copyright © 2016 the American Physiological Society.

MetaFIND: A feature analysis tool for metabolomics data

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Cunningham Pádraig

2008-11-01

Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

Handwritten-word spotting using biologically inspired features

NARCIS (Netherlands)

van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language, and collection. We propose a biologically inspired

Relevance in the science classroom: A multidimensional analysis

Science.gov (United States)

Hartwell, Matthew F.

While perceived relevance is considered a fundamental component of adaptive learning, the experience of relevance and its conceptual definition have not been well described. The mixed-methods research presented in this dissertation aimed to clarify the conceptual meaning of relevance by focusing on its phenomenological experience from the students' perspective. Following a critical literature review, I propose an identity-based model of perceived relevance that includes three components: a contextual target, an identity target, and a connection type, or lens. An empirical investigation of this model that consisted of two general phases was implemented in four 9th grade-biology classrooms. Participants in Phase 1 (N = 118) completed a series of four open-ended writing activities focused on eliciting perceived personal connections to academic content. Exploratory qualitative content analysis of a 25% random sample of the student responses was used to identify the main meaning-units of the proposed model as well as different dimensions of student relevance perceptions. These meaning-units and dimensions provided the basis for the construction of a conceptual mapping sentence capturing students' perceived relevance, which was then applied in a confirmatory analysis to all other student responses. Participants in Phase 2 (N = 139) completed a closed survey designed based on the mapping sentence to assess their perceived relevance of a biology unit. The survey also included scales assessing other domain-level motivational processes. Exploratory factor analysis and non-metric multidimensional scaling indicated a coherent conceptual structure, which included a primary interpretive relevance dimension. Comparison of the conceptual structure across various groups (randomly-split sample, gender, academic level, domain-general motivational profiles) provided support for its ubiquity and insight into variation in the experience of perceived relevance among students of different

Self-Relevance Constructions of Biology Concepts: Meaning-Making and Identity-Formation

Science.gov (United States)

Davidson, Yonaton Sahar

2018-01-01

Recent research supports the benefit of students' construction of relevance through writing about the connection of content to their life. However, most such research defines relevance narrowly as utility value--perceived instrumentality of the content to the student's career goals. Furthermore, the scope of phenomenological and conceptual…

Feature Extraction

CERN Document Server

CERN. Geneva

2015-01-01

Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

Science.gov (United States)

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those

Computational biology

DEFF Research Database (Denmark)

Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

2011-01-01

Computation via biological devices has been the subject of close scrutiny since von Neumann’s early work some 60 years ago. In spite of the many relevant works in this field, the notion of programming biological devices seems to be, at best, ill-defined. While many devices are claimed or proved t...

The PLOS ONE Synthetic Biology Collection: Six Years and Counting

Science.gov (United States)

Peccoud, Jean; Isalan, Mark

2012-01-01

Since it was launched in 2006, PLOS ONE has published over fifty articles illustrating the many facets of the emerging field of synthetic biology. This article reviews these publications by organizing them into broad categories focused on DNA synthesis and assembly techniques, the development of libraries of biological parts, the use of synthetic biology in protein engineering applications, and the engineering of gene regulatory networks and metabolic pathways. Finally, we review articles that describe enabling technologies such as software and modeling, along with new instrumentation. In order to increase the visibility of this body of work, the papers have been assembled into the PLOS ONE Synthetic Biology Collection (www.ploscollections.org/synbio). Many of the innovative features of the PLOS ONE web site will help make this collection a resource that will support a lively dialogue between readers and authors of PLOS ONE synthetic biology papers. The content of the collection will be updated periodically by including relevant articles as they are published by the journal. Thus, we hope that this collection will continue to meet the publishing needs of the synthetic biology community. PMID:22916228

Assessing therapeutic relevance of biologically interesting, ampholytic substances based on their physicochemical and spectral characteristics with chemometric tools

Science.gov (United States)

Judycka, U.; Jagiello, K.; Bober, L.; Błażejowski, J.; Puzyn, T.

2018-06-01

Chemometric tools were applied to investigate the biological behaviour of ampholytic substances in relation to their physicochemical and spectral properties. Results of the Principal Component Analysis suggest that size of molecules and their electronic and spectral characteristics are the key properties required to predict therapeutic relevance of the compounds examined. These properties were used for developing the structure-activity classification model. The classification model allows assessing the therapeutic behaviour of ampholytic substances on the basis of solely values of descriptors that can be obtained computationally. Thus, the prediction is possible without necessity of carrying out time-consuming and expensive laboratory tests, which is its main advantage.

Malaria in pregnancy: the relevance of animal models for vaccine development.

Science.gov (United States)

Doritchamou, Justin; Teo, Andrew; Fried, Michal; Duffy, Patrick E

2017-10-06

Malaria during pregnancy due to Plasmodium falciparum or P. vivax is a major public health problem in endemic areas, with P. falciparum causing the greatest burden of disease. Increasing resistance of parasites and mosquitoes to existing tools, such as preventive antimalarial treatments and insecticide-treated bed nets respectively, is eroding the partial protection that they offer to pregnant women. Thus, development of effective vaccines against malaria during pregnancy is an urgent priority. Relevant animal models that recapitulate key features of the pathophysiology and immunology of malaria in pregnant women could be used to accelerate vaccine development. This review summarizes available rodent and nonhuman primate models of malaria in pregnancy, and discusses their suitability for studies of biologics intended to prevent or treat malaria in this vulnerable population.

Classification Using Markov Blanket for Feature Selection

DEFF Research Database (Denmark)

Zeng, Yifeng; Luo, Jian

2009-01-01

Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

Feature Selection with the Boruta Package

OpenAIRE

Kursa, Miron B.; Rudnicki, Witold R.

2010-01-01

This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

Dealing with immunogenicity of biologicals: assessment and clinical relevance

NARCIS (Netherlands)

Wolbink, Gerrit J.; Aarden, Lucien A.; Dijkmans, B. A. C.

2009-01-01

PURPOSE OF REVIEW: In the last decade, biologicals revolutionized rheumatology. An increasing number of patients benefit from biotherapeuticals. However, some patients do not respond to treatment and others lose their response after a certain time. Immunogenicity is one of the factors linked to

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

Science.gov (United States)

Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

2016-01-01

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

LANGUAGE EXPERIENCE SHAPES PROCESSING OF PITCH RELEVANT INFORMATION IN THE HUMAN BRAINSTEM AND AUDITORY CORTEX: ELECTROPHYSIOLOGICAL EVIDENCE.

Science.gov (United States)

Krishnan, Ananthanarayan; Gandour, Jackson T

2014-12-01

Pitch is a robust perceptual attribute that plays an important role in speech, language, and music. As such, it provides an analytic window to evaluate how neural activity relevant to pitch undergo transformation from early sensory to later cognitive stages of processing in a well coordinated hierarchical network that is subject to experience-dependent plasticity. We review recent evidence of language experience-dependent effects in pitch processing based on comparisons of native vs. nonnative speakers of a tonal language from electrophysiological recordings in the auditory brainstem and auditory cortex. We present evidence that shows enhanced representation of linguistically-relevant pitch dimensions or features at both the brainstem and cortical levels with a stimulus-dependent preferential activation of the right hemisphere in native speakers of a tone language. We argue that neural representation of pitch-relevant information in the brainstem and early sensory level processing in the auditory cortex is shaped by the perceptual salience of domain-specific features. While both stages of processing are shaped by language experience, neural representations are transformed and fundamentally different at each biological level of abstraction. The representation of pitch relevant information in the brainstem is more fine-grained spectrotemporally as it reflects sustained neural phase-locking to pitch relevant periodicities contained in the stimulus. In contrast, the cortical pitch relevant neural activity reflects primarily a series of transient temporal neural events synchronized to certain temporal attributes of the pitch contour. We argue that experience-dependent enhancement of pitch representation for Chinese listeners most likely reflects an interaction between higher-level cognitive processes and early sensory-level processing to improve representations of behaviorally-relevant features that contribute optimally to perception. It is our view that long

Methods of small parameter in mathematical biology

CERN Document Server

Banasiak, Jacek

2014-01-01

This monograph presents new tools for modeling multiscale biological processes. Natural processes are usually driven by mechanisms widely differing from each other in the time or space scale at which they operate and thus should be described by appropriate multiscale models. However, looking at all such scales simultaneously is often infeasible, costly, and provides information that is redundant for a particular application. Hence, there has been a growing interest in providing a more focused description of multiscale processes by aggregating variables in a way that is relevant and preserves the salient features of the dynamics. The aim of this book is to present a systematic way of deriving the so-called limit equations for such aggregated variables and ensuring that the coefficients of these equations encapsulate the relevant information from the discarded levels of description. Since any approximation is only valid if an estimate of the incurred error is available, the tools described allow for proving tha...

Feature Selection with the Boruta Package

Directory of Open Access Journals (Sweden)

Miron B. Kursa

2010-10-01

Full Text Available This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

SysBioCube: A Data Warehouse and Integrative Data Analysis Platform Facilitating Systems Biology Studies of Disorders of Military Relevance.

Science.gov (United States)

Chowbina, Sudhir; Hammamieh, Rasha; Kumar, Raina; Chakraborty, Nabarun; Yang, Ruoting; Mudunuri, Uma; Jett, Marti; Palma, Joseph M; Stephens, Robert

2013-01-01

SysBioCube is an integrated data warehouse and analysis platform for experimental data relating to diseases of military relevance developed for the US Army Medical Research and Materiel Command Systems Biology Enterprise (SBE). It brings together, under a single database environment, pathophysio-, psychological, molecular and biochemical data from mouse models of post-traumatic stress disorder and (pre-) clinical data from human PTSD patients.. SysBioCube will organize, centralize and normalize this data and provide an access portal for subsequent analysis to the SBE. It provides new or expanded browsing, querying and visualization to provide better understanding of the systems biology of PTSD, all brought about through the integrated environment. We employ Oracle database technology to store the data using an integrated hierarchical database schema design. The web interface provides researchers with systematic information and option to interrogate the profiles of pan-omics component across different data types, experimental designs and other covariates.

Perspectives on the relevance of the circadian time structure to workplace threshold limit values and employee biological monitoring.

Science.gov (United States)

Smolensky, Michael H; Reinberg, Alain E; Sackett-Lundeen, Linda

2017-01-01

The circadian time structure (CTS) and its disruption by rotating and nightshift schedules relative to work performance, accident risk, and health/wellbeing have long been areas of occupational medicine research. Yet, there has been little exploration of the relevance of the CTS to setting short-term, time-weighted, and ceiling threshold limit values (TLVs); conducting employee biological monitoring (BM); and establishing normative reference biological exposure indices (BEIs). Numerous publications during the past six decades document the CTS substantially affects the disposition - absorption, distribution, metabolism, and elimination - and effects of medications. Additionally, laboratory animal and human studies verify the tolerance to chemical, biological (contagious), and physical agents can differ extensively according to the circadian time of exposure. Because of slow and usually incomplete CTS adjustment by rotating and permanent nightshift workers, occupational chemical and other contaminant encounters occur during a different circadian stage than for dayshift workers. Thus, the intended protection of some TLVs when working the nightshift compared to dayshift might be insufficient, especially in high-risk settings. The CTS is germane to employee BM in that large-amplitude predictable-in-time 24h variation can occur in the concentration of urine, blood, and saliva of monitored chemical contaminants and their metabolites plus biomarkers indicative of adverse xenobiotic exposure. The concept of biological time-qualified (for rhythms) reference values, currently of interest to clinical laboratory pathology practice, is seemingly applicable to industrial medicine as circadian time and workshift-specific BEIs to improve surveillance of night workers, in particular. Furthermore, BM as serial assessments performed frequently both during and off work, exemplified by employee self-measurement of lung function using a small portable peak expiratory flow meter, can

Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine

Directory of Open Access Journals (Sweden)

Yang Zhang

2015-11-01

Full Text Available Prognostics is necessary to ensure the reliability and safety of lithium-ion batteries for hybrid electric vehicles or satellites. This process can be achieved by capacity estimation, which is a direct fading indicator for assessing the state of health of a battery. However, the capacity of a lithium-ion battery onboard is difficult to monitor. This paper presents a data-driven approach for online capacity estimation. First, six novel features are extracted from cyclic charge/discharge cycles and used as indirect health indicators. An adaptive multi-kernel relevance machine (MKRVM based on accelerated particle swarm optimization algorithm is used to determine the optimal parameters of MKRVM and characterize the relationship between extracted features and battery capacity. The overall estimation process comprises offline and online stages. A supervised learning step in the offline stage is established for model verification to ensure the generalizability of MKRVM for online application. Cross-validation is further conducted to validate the performance of the proposed model. Experiment and comparison results show the effectiveness, accuracy, efficiency, and robustness of the proposed approach for online capacity estimation of lithium-ion batteries.

Detection of base damage in DNA in human blood exposed to ionizing radiation at biologically relevant doses

International Nuclear Information System (INIS)

Loon, A.A.W.M. van; Lohman, P.H.M.; Groenendijk, R.H.; Schans, G.P. van der; Baan, R.A.

1991-01-01

The alkaline elution technique for the detection of DNA damage has been adapted to allow application on unlabelled blood cells. Both the induction and subsequent repair have been studied of two classes of DNA damage, viz. single-strand breaks and base damage recognized by the γ-endonuclease activity in a cell-free extract of Micrococcus luteus bacteria. The high sensitivity of the assay permitted the measurement of induction and repair of base damage after in vitro exposure of full blood under aerobic conditions to biologically relevant doses of γ-rays (1.5-4.5 Gy). After a radiation dose of 3 Gy about 50% of the base damage was removed within 1.5 h of repair. Base damage could still be detected at 24h after exposure to 15 Gy. (author)

Action video game players' visual search advantage extends to biologically relevant stimuli.

Science.gov (United States)

Chisholm, Joseph D; Kingstone, Alan

2015-07-01

Research investigating the effects of action video game experience on cognition has demonstrated a host of performance improvements on a variety of basic tasks. Given the prevailing evidence that these benefits result from efficient control of attentional processes, there has been growing interest in using action video games as a general tool to enhance everyday attentional control. However, to date, there is little evidence indicating that the benefits of action video game playing scale up to complex settings with socially meaningful stimuli - one of the fundamental components of our natural environment. The present experiment compared action video game player (AVGP) and non-video game player (NVGP) performance on an oculomotor capture task that presented participants with face stimuli. In addition, the expression of a distractor face was manipulated to assess if action video game experience modulated the effect of emotion. Results indicate that AVGPs experience less oculomotor capture than NVGPs; an effect that was not influenced by the emotional content depicted by distractor faces. It is noteworthy that this AVGP advantage emerged despite participants being unaware that the investigation had to do with video game playing, and participants being equivalent in their motivation and treatment of the task as a game. The results align with the notion that action video game experience is associated with superior attentional and oculomotor control, and provides evidence that these benefits can generalize to more complex and biologically relevant stimuli. Copyright © 2015 Elsevier B.V. All rights reserved.

Kernel-Based Relevance Analysis with Enhanced Interpretability for Detection of Brain Activity Patterns

Directory of Open Access Journals (Sweden)

Andres M. Alvarez-Meza

2017-10-01

Full Text Available We introduce Enhanced Kernel-based Relevance Analysis (EKRA that aims to support the automatic identification of brain activity patterns using electroencephalographic recordings. EKRA is a data-driven strategy that incorporates two kernel functions to take advantage of the available joint information, associating neural responses to a given stimulus condition. Regarding this, a Centered Kernel Alignment functional is adjusted to learning the linear projection that best discriminates the input feature set, optimizing the required free parameters automatically. Our approach is carried out in two scenarios: (i feature selection by computing a relevance vector from extracted neural features to facilitating the physiological interpretation of a given brain activity task, and (ii enhanced feature selection to perform an additional transformation of relevant features aiming to improve the overall identification accuracy. Accordingly, we provide an alternative feature relevance analysis strategy that allows improving the system performance while favoring the data interpretability. For the validation purpose, EKRA is tested in two well-known tasks of brain activity: motor imagery discrimination and epileptic seizure detection. The obtained results show that the EKRA approach estimates a relevant representation space extracted from the provided supervised information, emphasizing the salient input features. As a result, our proposal outperforms the state-of-the-art methods regarding brain activity discrimination accuracy with the benefit of enhanced physiological interpretation about the task at hand.

Radiation biology. Chapter 20

Energy Technology Data Exchange (ETDEWEB)

Wondergem, J. [International Atomic Energy Agency, Vienna (Austria)

2014-09-15

Radiation biology (radiobiology) is the study of the action of ionizing radiations on living matter. This chapter gives an overview of the biological effects of ionizing radiation and discusses the physical, chemical and biological variables that affect dose response at the cellular, tissue and whole body levels at doses and dose rates relevant to diagnostic radiology.

On Feature Relevance in Image-Based Prediction Models: An Empirical Study

DEFF Research Database (Denmark)

Konukoglu, E.; Ganz, Melanie; Van Leemput, Koen

2013-01-01

Determining disease-related variations of the anatomy and function is an important step in better understanding diseases and developing early diagnostic systems. In particular, image-based multivariate prediction models and the “relevant features” they produce are attracting attention from the co...

Cosmetics as a Feature of the Extended Human Phenotype: Modulation of the Perception of Biologically Important Facial Signals

Science.gov (United States)

Etcoff, Nancy L.; Stock, Shannon; Haley, Lauren E.; Vickery, Sarah A.; House, David M.

2011-01-01

Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important signals at first

Cosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals.

Directory of Open Access Journals (Sweden)

Nancy L Etcoff

Full Text Available Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural, to moderate (professional, to dramatic (glamorous. Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important

Cosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals.

Science.gov (United States)

Etcoff, Nancy L; Stock, Shannon; Haley, Lauren E; Vickery, Sarah A; House, David M

2011-01-01

Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important signals at first

The Improved Relevance Voxel Machine

DEFF Research Database (Denmark)

Ganz, Melanie; Sabuncu, Mert; Van Leemput, Koen

The concept of sparse Bayesian learning has received much attention in the machine learning literature as a means of achieving parsimonious representations of features used in regression and classification. It is an important family of algorithms for sparse signal recovery and compressed sensing....... Hence in its current form it is reminiscent of a greedy forward feature selection algorithm. In this report, we aim to solve the problems of the original RVoxM algorithm in the spirit of [7] (FastRVM).We call the new algorithm Improved Relevance Voxel Machine (IRVoxM). Our contributions...... and enables basis selection from overcomplete dictionaries. One of the trailblazers of Bayesian learning is MacKay who already worked on the topic in his PhD thesis in 1992 [1]. Later on Tipping and Bishop developed the concept of sparse Bayesian learning [2, 3] and Tipping published the Relevance Vector...

Analysis of Evolutionarily Independent Protein-RNA Complexes Yields a Criterion to Evaluate the Relevance of Prebiotic Scenarios.

Science.gov (United States)

Blanco, Celia; Bayas, Marco; Yan, Fu; Chen, Irene A

2018-02-19

A central difficulty facing study of the origin of life on Earth is evaluating the relevance of different proposed prebiotic scenarios. Perhaps the most established feature of the origin of life was the progression through an RNA World, a prebiotic stage dominated by functional RNA. We use the appearance of proteins in the RNA World to understand the prebiotic milieu and develop a criterion to evaluate proposed synthetic scenarios. Current consensus suggests that the earliest amino acids of the genetic code were anionic or small hydrophobic or polar amino acids. However, the ability to interact with the RNA World would have been a crucial feature of early proteins. To determine which amino acids would be important for the RNA World, we analyze non-biological protein-aptamer complexes in which the RNA or DNA is the result of in vitro evolution. This approach avoids confounding effects of biological context and evolutionary history. We use bioinformatic analysis and molecular dynamics simulations to characterize these complexes. We find that positively charged and aromatic amino acids are over-represented whereas small hydrophobic amino acids are under-represented. Binding enthalpy is found to be primarily electrostatic, with positively charged amino acids contributing cooperatively to binding enthalpy. Arginine dominates all modes of interaction at the interface. These results suggest that proposed prebiotic syntheses must be compatible with cationic amino acids, particularly arginine or a biophysically similar amino acid, in order to be relevant to the invention of protein by the RNA World. Copyright © 2018 Elsevier Ltd. All rights reserved.

Macrotrabecular-massive hepatocellular carcinoma: A distinctive histological subtype with clinical relevance.

Science.gov (United States)

Ziol, Marianne; Poté, Nicolas; Amaddeo, Giuliana; Laurent, Alexis; Nault, Jean-Charles; Oberti, Frédéric; Costentin, Charlotte; Michalak, Sophie; Bouattour, Mohamed; Francoz, Claire; Pageaux, Georges Philippe; Ramos, Jeanne; Decaens, Thomas; Luciani, Alain; Guiu, Boris; Vilgrain, Valérie; Aubé, Christophe; Derman, Jonathan; Charpy, Cécile; Zucman-Rossi, Jessica; Barget, Nathalie; Seror, Olivier; Ganne-Carrié, Nathalie; Paradis, Valérie; Calderaro, Julien

2017-12-27

We recently identified a novel histological subtype of hepatocellular carcinoma, designated as "macrotrabecular-massive" (MTM-HCC) and associated with specific molecular features. In order to assess the clinical relevance of this novel variant, we aimed to investigate its prognostic value in two large series of patients with HCC treated either by surgical resection or radiofrequency ablation (RFA). We retrospectively included 237 HCC surgical samples and 284 HCC liver biopsies from patients treated by surgical resection and RFA, respectively. Histological slides were reviewed by pathologists specialized in liver disease, and the MTM-HCC subtype was defined by the presence of a predominant (>50%) macrotrabecular architecture (more than 6 cells thick). The main clinical and biological features were recorded at baseline. Clinical endpoints were early and overall recurrence. The MTM-HCC subtype was identified in 12% of the whole cohort (16% of surgically resected samples, 8.5% of liver biopsy samples). It was associated at baseline with known poor prognostic factors (tumor size, AFP level, satellite nodules and vascular invasion). Multivariate analysis showed that MTM-HCC subtype was an independent predictor of early and overall recurrence (surgical series: OR 3.03 (1.38-6.65), p=0.006 and 2.76 (1.63-4.67), pvalue was retained even after patients stratification according to common clinical, biological and pathological features of aggressiveness. No other baseline parameter was independently associated to recurrence in the RFA series. The MTM-HCC subtype, reliably observed in 12% of patients eligible for a curative treatment, represents an aggressive form of HCC that may require more specific therapeutic strategies. This article is protected by copyright. All rights reserved. © 2017 by the American Association for the Study of Liver Diseases.

Doubly sparse factor models for unifying feature transformation and feature selection

International Nuclear Information System (INIS)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato; Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko

2010-01-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Doubly sparse factor models for unifying feature transformation and feature selection

Energy Technology Data Exchange (ETDEWEB)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato [ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama (Japan); Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko, E-mail: okada@k.u-tokyo.ac.j [Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki (Japan)

2010-06-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Examining the Impact of Question Surface Features on Students’ Answers to Constructed-Response Questions on Photosynthesis

Science.gov (United States)

Weston, Michele; Haudek, Kevin C.; Prevost, Luanna; Urban-Lurain, Mark; Merrill, John

2015-01-01

One challenge in science education assessment is that students often focus on surface features of questions rather than the underlying scientific principles. We investigated how student written responses to constructed-response questions about photosynthesis vary based on two surface features of the question: the species of plant and the order of two question prompts. We asked four versions of the question with different combinations of the two plant species and order of prompts in an introductory cell biology course. We found that there was not a significant difference in the content of student responses to versions of the question stem with different species or order of prompts, using both computerized lexical analysis and expert scoring. We conducted 20 face-to-face interviews with students to further probe the effects of question wording on student responses. During the interviews, we found that students thought that the plant species was neither relevant nor confusing when answering the question. Students identified the prompts as both relevant and confusing. However, this confusion was not specific to a single version. PMID:25999312

Biologics in pediatric psoriasis - efficacy and safety.

Science.gov (United States)

Dogra, Sunil; Mahajan, Rahul

2018-01-01

Childhood psoriasis is a special situation that is a management challenge for the treating dermatologist. As is the situation with traditional systemic agents, which are commonly used in managing severe psoriasis in children, the biologics are being increasingly used in the recalcitrant disease despite limited data on long term safety. Areas covered: We performed an extensive literature search to collect evidence-based data on the use of biologics in pediatric psoriasis. The relevant literature published from 2000 to September 2017 was obtained from PubMed, using the MeSH words 'biologics', 'biologic response modifiers' and 'treatment of pediatric/childhood psoriasis'. All clinical trials, randomized double-blind or single-blind controlled trials, open-label studies, retrospective studies, reviews, case reports and letters concerning the use of biologics in pediatric psoriasis were screened. Articles covering the use of biologics in pediatric psoriasis were screened and reference lists in the selected articles were scrutinized to identify other relevant articles that had not been found in the initial search. Articles without relevant information about biologics in general (e.g. its mechanism of action, pharmacokinetics and adverse effects) and its use in psoriasis in particular were excluded. We screened 427 articles and finally selected 41 relevant articles. Expert opinion: The available literature on the use of biologics such as anti-tumor necrosis factor (TNF)-α agents, and anti-IL-12/23 agents like ustekinumab suggests that these are effective and safe in managing severe pediatric psoriasis although there is an urgent need to generate more safety data. Dermatologists must be careful about the potential adverse effects of the biologics before administering them to children with psoriasis. It is likely that with rapidly evolving scenario of biologics in psoriasis, these will prove to be very useful molecules particularly in managing severe and recalcitrant

7th Annual Systems Biology Symposium: Systems Biology and Engineering

Energy Technology Data Exchange (ETDEWEB)

Galitski, Timothy P.

2008-04-01

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering are now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."

Statistical approach for selection of biologically informative genes.

Science.gov (United States)

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

Zebrafish: A marvel of high-throughput biology for 21st century toxicology.

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Bugel, Sean M; Tanguay, Robert L; Planchart, Antonio

2014-09-07

The evolutionary conservation of genomic, biochemical and developmental features between zebrafish and humans is gradually coming into focus with the end result that the zebrafish embryo model has emerged as a powerful tool for uncovering the effects of environmental exposures on a multitude of biological processes with direct relevance to human health. In this review, we highlight advances in automation, high-throughput (HT) screening, and analysis that leverage the power of the zebrafish embryo model for unparalleled advances in our understanding of how chemicals in our environment affect our health and wellbeing.

Spatial Modeling Tools for Cell Biology

National Research Council Canada - National Science Library

Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

2006-01-01

.... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

Relevance Feedback in Content Based Image Retrieval: A Review

Directory of Open Access Journals (Sweden)

Manesh B. Kokare

2011-01-01

Full Text Available This paper provides an overview of the technical achievements in the research area of relevance feedback (RF in content-based image retrieval (CBIR. Relevance feedback is a powerful technique in CBIR systems, in order to improve the performance of CBIR effectively. It is an open research area to the researcher to reduce the semantic gap between low-level features and high level concepts. The paper covers the current state of art of the research in relevance feedback in CBIR, various relevance feedback techniques and issues in relevance feedback are discussed in detail.

Single Molecule Fluorescence: from Physical Fascination to Biological Relevance

OpenAIRE

Segers-Nolten, Gezina M.J.

2003-01-01

Confocal fluorescence microscopy is particularly well-known from the beautiful images that have been obtained with this technique from cells. Several cellular components could be nicely visualized simultaneously by staining them with different fluorophores. Not only for ensemble applications but also in single molecule research confocal fluorescence microscopy became a popular technique. In this thesis the possibilities are shown to study a complicated biological process, which is Nucleotide ...

Exposure to 3G mobile phone signals does not affect the biological features of brain tumor cells.

Science.gov (United States)

Liu, Yu-xiao; Li, Guo-qing; Fu, Xiang-ping; Xue, Jing-hui; Ji, Shou-ping; Zhang, Zhi-wen; Zhang, Yi; Li, An-ming

2015-08-08

The increase in mobile phone use has generated concerns about possible risks to human health, especially the development of brain tumors. Whether tumor patients should continue to use mobile telephones has remained unclear because of a paucity of information. Herein, we investigated whether electromagnetic fields from mobile phones could alter the biological features of human tumor cells and act as a tumor-promoting agent. Human glioblastoma cell lines, U251-MG and U87-MG, were exposed to 1950-MHz time division-synchronous code division multiple access (TD-SCDMA) at a specific absorption rate (maximum SAR = 5.0 W/kg) for 12, 24, and 48 h. Cell morphologies and ultra-structures were observed by microscopy and the rates of apoptosis and cell cycle progression were monitored by flow cytometry. Additionally, cell growth was determined using the CKK-8 assay, and the expression levels of tumor and apoptosis-related genes and proteins were analyzed by real-time PCR and western blotting, respectively. Tumor formation and invasiveness were measured using a tumorigenicity assay in vivo and migration assays in vitro. No significant differences in either biological features or tumor formation ability were observed between unexposed and exposed glioblastoma cells. Our data showed that exposure to 1950-MHz TD-SCDMA electromagnetic fields for up to 48 h did not act as a cytotoxic or tumor-promoting agent to affect the proliferation or gene expression profile of glioblastoma cells. Our findings implied that exposing brain tumor cells in vitro for up to 48 h to 1950-MHz continuous TD-SCDMA electromagnetic fields did not elicit a general cell stress response.

Insights into the biological features of the antigenic determinants recognized by four monoclonal antibodies in redia and adult stages of the liver fluke Fasciola hepatica.

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Alba, Annia; Sánchez, Jorge; Hernández, Hilda; Mosqueda, Maryani; Rodríguez, Suanel Y; Capó, Virginia; Otero, Oscar; Alfonso, Carlos; Marcet, Ricardo; Sarracent, Jorge

2016-09-01

Fasciola hepatica is a digenean trematode which infects a wide variety of domestic animals and also humans. Previous studies have demonstrated that four monoclonal antibodies (Mabs) against the total extract of F. hepatica redia (named as 1E4, 6G11, 4E5 and 4G11) also recognized the excretion - secretion antigens (ES Ag) of adult parasites, which is a biologically-relevant mixture of molecules with functional roles during infection and immune evasion on definitive hosts. In the present report we describe the partial characterization of the epitopes recognized by these Mabs by heat treatment, mercaptoethanol reduction, pronase proteolysis and sodium peryodate oxidation, which suggested their predominant protein and conformational nature. Also, a comparative study using immunodetection assays on crude extracts and on histological sections of both rediae and adults of F. hepatica were performed to explore the expression pattern of the antigenic determinants in these developmental stages. From these experiments it was found that the Mabs reacted most likely with the same proteins of approximately 64 and 105 kDa present on both rediae and adult's extracts. However, the 1E4, 6G11 and 4E5 Mabs also recognized other molecules of the total extract of F. hepatica adults, a fact that constitutes an evidence of the antigenic variation between both stages and points at a certain biological relevance of the recognized antigenic determinants. Immunolocalization studies on histological sections revealed that all Mabs reacted with the tegument of F. hepatica in both rediae and adults stages, while the epitopes recognized by 1E4, 6G11 and 4E5 antibodies were also preferentially localized in the intestinal caeca and in different organs of the reproductive system of adult specimens. The immunogenicity of these antigenic determinants, their conserved status among different stages of the life cycle of F. hepatica and their presence in both tegument and ES Ag of adult parasites

Student-oriented learning: an inquiry-based developmental biology lecture course.

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Malacinski, George M

2003-01-01

In this junior-level undergraduate course, developmental life cycles exhibited by various organisms are reviewed, with special attention--where relevant--to the human embryo. Morphological features and processes are described and recent insights into the molecular biology of gene expression are discussed. Ways are studied in which model systems, including marine invertebrates, amphibia, fruit flies and other laboratory species are employed to elucidate general principles which apply to fertilization, cleavage, gastrulation and organogenesis. Special attention is given to insights into those topics which will soon be researched with data from the Human Genome Project. The learning experience is divided into three parts: Part I is a in which the Socratic (inquiry) method is employed by the instructor (GMM) to organize a review of classical developmental phenomena; Part II represents an in which students study the details related to the surveys included in Part I as they have been reported in research journals; Part III focuses on a class project--the preparation of a spiral bound on a topic of relevance to human developmental biology (e.g.,Textbook of Embryonal Stem Cells). Student response to the use of the Socratic method increases as the course progresses and represents the most successful aspect of the course.

Flapping and flexible wings for biological and micro air vehicles

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Shyy, Wei; Berg, Mats; Ljungqvist, Daniel

1999-07-01

Micro air vehicles (MAVs) with wing spans of 15 cm or less, and flight speed of 30-60 kph are of interest for military and civilian applications. There are two prominent features of MAV flight: (i) low Reynolds number (10 4-10 5), resulting in unfavorable aerodynamic conditions to support controlled flight, and (ii) small physical dimensions, resulting in certain favorable scaling characteristics including structural strength, reduced stall speed, and low inertia. Based on observations of biological flight vehicles, it appears that wing motion and flexible airfoils are two key attributes for flight at low Reynolds number. The small size of MAVs corresponds in nature to small birds, which do not glide like large birds, but instead flap with considerable change of wing shape during a single flapping cycle. With flapping and flexible wings, birds overcome the deteriorating aerodynamic performance under steady flow conditions by employing unsteady mechanisms. In this article, we review both biological and aeronautical literatures to present salient features relevant to MAVs. We first summarize scaling laws of biological and micro air vehicles involving wing span, wing loading, vehicle mass, cruising speed, flapping frequency, and power. Next we discuss kinematics of flapping wings and aerodynamic models for analyzing lift, drag and power. Then we present issues related to low Reynolds number flows and airfoil shape selection. Recent work on flexible structures capable of adjusting the airfoil shape in response to freestream variations is also discussed.

Contingent attentional capture across multiple feature dimensions in a temporal search task.

Science.gov (United States)

Ito, Motohiro; Kawahara, Jun I

2016-01-01

The present study examined whether attention can be flexibly controlled to monitor two different feature dimensions (shape and color) in a temporal search task. Specifically, we investigated the occurrence of contingent attentional capture (i.e., interference from task-relevant distractors) and resulting set reconfiguration (i.e., enhancement of single task-relevant set). If observers can restrict searches to a specific value for each relevant feature dimension independently, the capture and reconfiguration effect should only occur when the single relevant distractor in each dimension appears. Participants identified a target letter surrounded by a non-green square or a non-square green frame. The results revealed contingent attentional capture, as target identification accuracy was lower when the distractor contained a target-defining feature than when it contained a nontarget feature. Resulting set reconfiguration was also obtained in that accuracy was superior when the current target's feature (e.g., shape) corresponded to the defining feature of the present distractor (shape) than when the current target's feature did not match the distractor's feature (color). This enhancement was not due to perceptual priming. The present study demonstrated that the principles of contingent attentional capture and resulting set reconfiguration held even when multiple target feature dimensions were monitored. Copyright © 2015 Elsevier B.V. All rights reserved.

The Role of Stochastic Models in Interpreting the Origins of Biological Chirality

Directory of Open Access Journals (Sweden)

Gábor Lente

2010-04-01

Full Text Available This review summarizes recent stochastic modeling efforts in the theoretical research aimed at interpreting the origins of biological chirality. Stochastic kinetic models, especially those based on the continuous time discrete state approach, have great potential in modeling absolute asymmetric reactions, experimental examples of which have been reported in the past decade. An overview of the relevant mathematical background is given and several examples are presented to show how the significant numerical problems characteristic of the use of stochastic models can be overcome by non-trivial, but elementary algebra. In these stochastic models, a particulate view of matter is used rather than the concentration-based view of traditional chemical kinetics using continuous functions to describe the properties system. This has the advantage of giving adequate description of single-molecule events, which were probably important in the origin of biological chirality. The presented models can interpret and predict the random distribution of enantiomeric excess among repetitive experiments, which is the most striking feature of absolute asymmetric reactions. It is argued that the use of the stochastic kinetic approach should be much more widespread in the relevant literature.

Feature Vector Construction Method for IRIS Recognition

Science.gov (United States)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

nRC: non-coding RNA Classifier based on structural features.

Science.gov (United States)

Fiannaca, Antonino; La Rosa, Massimo; La Paglia, Laura; Rizzo, Riccardo; Urso, Alfonso

2017-01-01

Non-coding RNA (ncRNA) are small non-coding sequences involved in gene expression regulation of many biological processes and diseases. The recent discovery of a large set of different ncRNAs with biologically relevant roles has opened the way to develop methods able to discriminate between the different ncRNA classes. Moreover, the lack of knowledge about the complete mechanisms in regulative processes, together with the development of high-throughput technologies, has required the help of bioinformatics tools in addressing biologists and clinicians with a deeper comprehension of the functional roles of ncRNAs. In this work, we introduce a new ncRNA classification tool, nRC (non-coding RNA Classifier). Our approach is based on features extraction from the ncRNA secondary structure together with a supervised classification algorithm implementing a deep learning architecture based on convolutional neural networks. We tested our approach for the classification of 13 different ncRNA classes. We obtained classification scores, using the most common statistical measures. In particular, we reach an accuracy and sensitivity score of about 74%. The proposed method outperforms other similar classification methods based on secondary structure features and machine learning algorithms, including the RNAcon tool that, to date, is the reference classifier. nRC tool is freely available as a docker image at https://hub.docker.com/r/tblab/nrc/. The source code of nRC tool is also available at https://github.com/IcarPA-TBlab/nrc.

Transcriptomic and genomic features of invasive lobular breast cancer.

Science.gov (United States)

Desmedt, Christine; Zoppoli, Gabriele; Sotiriou, Christos; Salgado, Roberto

2017-06-01

Accounting for 10-15% of all breast neoplasms, invasive lobular breast cancer (ILC) is the second most common histological subtype of breast cancer after invasive ductal breast cancer (IDC). Understanding ILC biology, which differs from IDC in terms of clinical presentation, treatment response, relapse timing and patterns, is essential in order to adopt novel, disease-specific management strategies. While the contribution of the histological subtypes to tumour biology has been poorly investigated and acknowledged in the past, recently several major, independent efforts have led to the assembly and molecular characterization of well-annotated ILC case sets. In this review, we provide a critical overview of the literature exploring ILC, through comprehensive and multiomic methods. The first part specifically focuses on ILC transcriptomic features by reviewing the intrinsic molecular subtypes, the application of gene expression scores for the prediction of recurrence, and the identification of gene expression subtypes. The second part describes the main research efforts that lead to the identification of the genomic landscape of ILC, with a special focus to findings that differentiate ILC from IDC and carry potential clinical relevance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Information on black-footed ferret biology collected within the framework of ferret conservation

Science.gov (United States)

Biggins, Dean E.

2012-01-01

Once feared to be extinct, black-footed ferrets (Mustela nigripes) were rediscovered near Meeteetse, Wyoming, in 1981, resulting in renewed conservation and research efforts for this highly endangered species. A need for information directly useful to recovery has motivated much monitoring of ferrets since that time, but field activities have enabled collection of data relevant to broader biological themes. This special feature is placed in a context of similar books and proceedings devoted to ferret biology and conservation. Articles include general observations on ferrets, modeling of potential impacts of ferrets on prairie dogs (Cynomys spp.), discussions on relationships of ferrets to prairie dog habitats at several spatial scales (from individual burrows to patches of burrow systems) and a general treatise on the status of black-footed ferret recovery.

Functions in Biological Kind Classification

Science.gov (United States)

Lombrozo, Tania; Rehder, Bob

2012-01-01

Biological traits that serve functions, such as a zebra's coloration (for camouflage) or a kangaroo's tail (for balance), seem to have a special role in conceptual representations for biological kinds. In five experiments, we investigate whether and why functional features are privileged in biological kind classification. Experiment 1…

Comprehensive Transcriptome Analysis of Sex-Biased Expressed Genes Reveals Discrete Biological and Physiological Features of Male and Female Schistosoma japonicum.

Directory of Open Access Journals (Sweden)

Pengfei Cai

2016-04-01

Full Text Available Schistosomiasis is a chronic and debilitating disease caused by blood flukes (digenetic trematodes of the genus Schistosoma. Schistosomes are sexually dimorphic and exhibit dramatic morphological changes during a complex lifecycle which requires subtle gene regulatory mechanisms to fulfil these complex biological processes. In the current study, a 41,982 features custom DNA microarray, which represents the most comprehensive probe coverage for any schistosome transcriptome study, was designed based on public domain and local databases to explore differential gene expression in S. japonicum. We found that approximately 1/10 of the total annotated genes in the S. japonicum genome are differentially expressed between adult males and females. In general, genes associated with the cytoskeleton, and motor and neuronal activities were readily expressed in male adult worms, whereas genes involved in amino acid metabolism, nucleotide biosynthesis, gluconeogenesis, glycosylation, cell cycle processes, DNA synthesis and genome fidelity and stability were enriched in females. Further, miRNAs target sites within these gene sets were predicted, which provides a scenario whereby the miRNAs potentially regulate these sex-biased expressed genes. The study significantly expands the expressional and regulatory characteristics of gender-biased expressed genes in schistosomes with high accuracy. The data provide a better appreciation of the biological and physiological features of male and female schistosome parasites, which may lead to novel vaccine targets and the development of new therapeutic interventions.

Comprehensive Transcriptome Analysis of Sex-Biased Expressed Genes Reveals Discrete Biological and Physiological Features of Male and Female Schistosoma japonicum.

Science.gov (United States)

Cai, Pengfei; Liu, Shuai; Piao, Xianyu; Hou, Nan; Gobert, Geoffrey N; McManus, Donald P; Chen, Qijun

2016-04-01

Schistosomiasis is a chronic and debilitating disease caused by blood flukes (digenetic trematodes) of the genus Schistosoma. Schistosomes are sexually dimorphic and exhibit dramatic morphological changes during a complex lifecycle which requires subtle gene regulatory mechanisms to fulfil these complex biological processes. In the current study, a 41,982 features custom DNA microarray, which represents the most comprehensive probe coverage for any schistosome transcriptome study, was designed based on public domain and local databases to explore differential gene expression in S. japonicum. We found that approximately 1/10 of the total annotated genes in the S. japonicum genome are differentially expressed between adult males and females. In general, genes associated with the cytoskeleton, and motor and neuronal activities were readily expressed in male adult worms, whereas genes involved in amino acid metabolism, nucleotide biosynthesis, gluconeogenesis, glycosylation, cell cycle processes, DNA synthesis and genome fidelity and stability were enriched in females. Further, miRNAs target sites within these gene sets were predicted, which provides a scenario whereby the miRNAs potentially regulate these sex-biased expressed genes. The study significantly expands the expressional and regulatory characteristics of gender-biased expressed genes in schistosomes with high accuracy. The data provide a better appreciation of the biological and physiological features of male and female schistosome parasites, which may lead to novel vaccine targets and the development of new therapeutic interventions.

Predicting biological system objectives de novo from internal state measurements

Directory of Open Access Journals (Sweden)

Maranas Costas D

2008-01-01

Full Text Available Abstract Background Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth and the subsequent application of linear programming (LP to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning. Results We present a novel method called Biological Objective Solution Search (BOSS for the inference of an objective function of a biological system from its underlying network stoichiometry as well as experimentally-measured state variables. Specifically, BOSS identifies a system objective by defining a putative stoichiometric "objective reaction," adding this reaction to the existing set of stoichiometric constraints arising from known interactions within a network, and maximizing the putative objective reaction via LP, all the while minimizing the difference between the resultant in silico flux distribution and available experimental (e.g., isotopomer flux data. This new approach allows for discovery of objectives with previously unknown stoichiometry, thus extending the biological relevance from earlier methods. We verify our approach on the well-characterized central metabolic network of Saccharomyces cerevisiae. Conclusion We illustrate how BOSS offers insight into the functional organization of biochemical networks

Carcinoid of the ampulla of Vater: Morphologic features and clinical implications

Institute of Scientific and Technical Information of China (English)

George A Poultsides; Wayne AI Frederick

2006-01-01

Carcinoids involving the ampulla of Vater are rare lesions that may produce painless jaundice. The published data indicate that these tumors, in contrast to their midgut counterparts, metastasize in approximately half of cases irrespective of primary tumor size. Therefore,radical excision in the form of pancreaticoduodenectomy is recommended regardless of tumor size. As with other gastrointestinal carcinoid tumors, biological treatment with octreotide analogues can be applied to symptomatic patients. Tumor-targeted radioactive therapy is a newly emerging treatment option. We here report case of a carcinoid tumor of the ampulla of Vater presenting as painless jaundice in a 65-year old man and review the relevant literature, giving special attention to the morphologic features, clinical characteristics, and treatment modalities associated with this disease process.

The Biology of Cancer Health Disparities

Science.gov (United States)

These examples show how biology contributes to health disparities (differences in disease incidence and outcomes among distinct racial and ethnic groups, ), and how biological factors interact with other relevant factors, such as diet and the environment.

Relevant feature set estimation with a knock-out strategy and random forests

DEFF Research Database (Denmark)

Ganz, Melanie; Greve, Douglas N; Fischl, Bruce

2015-01-01

unintuitive and difficult to determine. In this article, we propose a novel MVPA method for group analysis of high-dimensional data that overcomes the drawbacks of the current techniques. Our approach explicitly aims to identify all relevant variations using a "knock-out" strategy and the Random Forest...

Ultrafast relaxation dynamics of a biologically relevant probe dansyl at the micellar surface.

Science.gov (United States)

Sarkar, Rupa; Ghosh, Manoranjan; Pal, Samir Kumar

2005-02-01

We report picosecond-resolved measurement of the fluorescence of a well-known biologically relevant probe, dansyl chromophore at the surface of a cationic micelle (cetyltrimethylammonium bromide, CTAB). The dansyl chromophore has environmentally sensitive fluorescence quantum yields and emission maxima, along with large Stokes shift. In order to study the solvation dynamics of the micellar environment, we measured the fluorescence of dansyl chromophore attached to the micellar surface. The fluorescence transients were observed to decay (with time constant approximately 350 ps) in the blue end and rise with similar timescale in the red end, indicative of solvation dynamics of the environment. The solvation correlation function is measured to decay with time constant 338 ps, which is much slower than that of ordinary bulk water. Time-resolved anisotropy of the dansyl chromophore shows a bi-exponential decay with time constants 413 ps (23%) and 1.3 ns (77%), which is considerably slower than that in free solvents revealing the rigidity of the dansyl-micelle complex. Time-resolved area-normalized emission spectroscopic (TRANES) analysis of the time dependent emission spectra of the dansyl chromophore in the micellar environment shows an isoemissive point at 21066 cm-1. This indicates the fluorescence of the chromophore contains emission from two kinds of excited states namely locally excited state (prior to charge transfer) and charge transfer state. The nature of the solvation dynamics in the micellar environments is therefore explored from the time-resolved anisotropy measurement coupled with the TRANES analysis of the fluorescence transients. The time scale of the solvation is important for the mechanism of molecular recognition.

Review for carrageenan-based pharmaceutical biomaterials: favourable physical features versus adverse biological effects.

Science.gov (United States)

Liu, Jingjing; Zhan, Xiudan; Wan, Jianbo; Wang, Yitao; Wang, Chunming

2015-05-05

Carrageenan (CRG) is a family of natural polysaccharides derived from seaweeds and has widely been used as food additives. In the past decade, owing to its attractive physicochemical properties, CRG has been developed into versatile biomaterials vehicles for drug delivery. Nevertheless, studies also emerged to reveal its adverse effects on the biological system. In this review, we critically appraise the latest literature (two thirds since 2008) on the development of CRG-based pharmaceutical vehicles and the perspective of using CRG for broader biomedical applications. We focus on how current strategies exploit the unique gelling mechanisms, strong water absorption and abundant functional groups of the three major CRG varieties. Notably, CRG-based matrices are demonstrated to increase drug loading and drug solubility, enabling release of orally administrated drugs in zero-order or in a significantly prolonged period. Other amazing features, such as pH-sensitivity and adhesive property, of CRG-based formulations are also introduced. Finally, we discuss the adverse influence of CRG on the human body and then suggest some future directions for the development of CRG-based biomaterials for broader applications in biomedicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

CHARACTERISTIC FEATURES OF MUELLER MATRIX PATTERNS FOR POLARIZATION SCATTERING MODEL OF BIOLOGICAL TISSUES

Directory of Open Access Journals (Sweden)

E DU

2014-01-01

Full Text Available We developed a model to describe polarized photon scattering in biological tissues. In this model, tissues are simplified to a mixture of scatterers and surrounding medium. There are two types of scatterers in the model: solid spheres and infinitely long solid cylinders. Variables related to the scatterers include: the densities and sizes of the spheres and cylinders, the orientation and angular distribution of cylinders. Variables related to the surrounding medium include: the refractive index, absorption coefficient and birefringence. In this paper, as a development we introduce an optical activity effect to the model. By comparing experiments and Monte Carlo simulations, we analyze the backscattering Mueller matrix patterns of several tissue-like media, and summarize the different effects coming from anisotropic scattering and optical properties. In addition, we propose a possible method to extract the optical activity values for tissues. Both the experimental and simulated results show that, by analyzing the Mueller matrix patterns, the microstructure and optical properties of the medium can be obtained. The characteristic features of Mueller matrix patterns are potentially powerful tools for studying the contrast mechanisms of polarization imaging for medical diagnosis.

Long-time data storage: relevant time scales

NARCIS (Netherlands)

Elwenspoek, Michael Curt

2011-01-01

Dynamic processes relevant for long-time storage of information about human kind are discussed, ranging from biological and geological processes to the lifecycle of stars and the expansion of the universe. Major results are that life will end ultimately and the remaining time that the earth is

How causal analysis can reveal autonomy in models of biological systems

Science.gov (United States)

Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa

2017-11-01

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Consistent robustness analysis (CRA) identifies biologically relevant properties of regulatory network models.

Science.gov (United States)

Saithong, Treenut; Painter, Kevin J; Millar, Andrew J

2010-12-16

A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

A unified framework for image retrieval using keyword and visual features.

Science.gov (United States)

Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

2005-07-01

In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

Institute for Genomics and Systems Biology

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Institute for Genomics and Systems Biology Discover. Predict. Improve. Advancing Human and , 2015 See all Research Papers Featured Video Introduction to Systems Biology Video: Introduction to Systems Biology News Jack Gilbert Heading UChicago Startup that Aims to Predict Behavior of Trillions of

The ability to cause infection in a pathogenic fungus uncovers a new biological feature of honey bee viruses.

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Li, Zhiguo; Su, Songkun; Hamilton, Michele; Yan, Limin; Chen, Yanping

2014-07-01

We demonstrated that honey bee viruses including Deformed wing virus (DWV), Black queen cell virus (BQCV) and Israeli acute paralysis virus (IAPV) could infect and replicate in the fungal pathogen Ascosphaera apis that causes honey bee chalkbrood disease, revealing a novel biological feature of honey bee viruses. The phylogenetic analysis show that viruses of fungal and honey bee origins form two clusters in the phylogenetic trees distinctly and that host range of honey bee viruses is dynamic. Further studies are warranted to investigate the impact of the viruses on the fitness of their fungal host and phenotypic effects the virus-fungus combination has on honey bee hosts. Published by Elsevier Inc.

Distinguishing the relevant features of frequent suicide attempters.

Science.gov (United States)

Lopez-Castroman, Jorge; Perez-Rodriguez, Maria de las Mercedes; Jaussent, Isabelle; Alegria, Analucia A; Artes-Rodriguez, Antonio; Freed, Peter; Guillaume, Sébastien; Jollant, Fabrice; Leiva-Murillo, Jose Miguel; Malafosse, Alain; Oquendo, Maria A; de Prado-Cumplido, Mario; Saiz-Ruiz, Jeronimo; Baca-Garcia, Enrique; Courtet, Philippe

2011-05-01

In spite of the high prevalence of suicide behaviours and the magnitude of the resultant burden, little is known about why individuals reattempt. We aim to investigate the relationships between clinical risk factors and the repetition of suicidal attempts. 1349 suicide attempters were consecutively recruited in the Emergency Room (ER) of two academic hospitals in France and Spain. Patients were extensively assessed and demographic and clinical data obtained. Data mining was used to determine the minimal number of variables that blinded the rest in relation to the number of suicide attempts. Using this set, a probabilistic graph ranking relationships with the target variable was constructed. The most common diagnoses among suicide attempters were affective disorders, followed by anxiety disorders. Risk of frequent suicide attempt was highest among middle-aged subjects, and diminished progressively with advancing age of onset at first attempt. Anxiety disorders significantly increased the risk of presenting frequent suicide attempts. Pathway analysis also indicated that frequent suicide attempts were linked to greater odds for alcohol and substance abuse disorders and more intensive treatment. Novel statistical methods found several clinical features that were associated with a history of frequent suicide attempts. The identified pathways may promote new hypothesis-driven studies of suicide attempts and preventive strategies. Copyright © 2010 Elsevier Ltd. All rights reserved.

A national-scale model of linear features improves predictions of farmland biodiversity.

Science.gov (United States)

Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

2017-12-01

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

Relevance-based control over visual attention is fast and interdependent with stimulus-driven capture

DEFF Research Database (Denmark)

Nordfang, Maria; Bundesen, Claus

2012-01-01

or distractor) was a color singleton, but the probability that the singleton was a target was just the same as the probability that a nonsingleton was a target. Participants showed significant effects of both feature contrast and task relevance. The probability of correctly reporting a singleton target...... that high local feature contrast attracts attention independently of task-relevance. Yet, recent studies have provided evidence that effects of task-irrelevant feature contrast interact with the task-relevance of the object in question (Nordfang, 2011). In a new experiment, display size was kept constant...... was significantly higher than the probability of reporting a nonsingleton target. The probability of correctly reporting a given target also was significantly higher for the displays with 2 targets and 6 distractors than for the 8-target displays, revealing selectivity based on task-relevance. This effect...

Industrial systems biology and its impact on synthetic biology of yeast cell factories

DEFF Research Database (Denmark)

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-01-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...

Temporal Feature Integration for Music Organisation

DEFF Research Database (Denmark)

Meng, Anders

2006-01-01

This Ph.D. thesis focuses on temporal feature integration for music organisation. Temporal feature integration is the process of combining all the feature vectors of a given time-frame into a single new feature vector in order to capture relevant information in the frame. Several existing methods...... for handling sequences of features are formulated in the temporal feature integration framework. Two datasets for music genre classification have been considered as valid test-beds for music organisation. Human evaluations of these, have been obtained to access the subjectivity on the datasets. Temporal...... ranking' approach is proposed for ranking the short-time features at larger time-scales according to their discriminative power in a music genre classification task. The multivariate AR (MAR) model has been proposed for temporal feature integration. It effectively models local dynamical structure...

Application to biological data

Indian Academy of Sciences (India)

Reduction of dimensionality has emerged as a routine process in modelling complex biological systems. A large number of feature selection techniques have been reported in the literature to improve model performance in terms of accuracy and speed. In the present article an unsupervised feature selection technique is ...

On making nursing undergraduate human reproductive physiology content meaningful and relevant: discussion of human pleasure in its biological context.

Science.gov (United States)

McClusky, Leon Mendel

2012-01-01

The traditional presentation of the Reproductive Physiology component in an Anatomy and Physiology course to nursing undergraduates focuses on the broad aspects of hormonal regulation of reproduction and gonadal anatomy, with the role of the higher centres of the brain omitted. An introductory discussion is proposed which could precede the lectures on the reproductive organs. The discussion gives an overview of the biological significance of human pleasure, the involvement of the neurotransmitter dopamine, and the role of pleasure in the survival of the individual and even species. Pleasure stimuli (positive and negative) and the biological significance of naturally-induced pleasurable experiences are briefly discussed in the context of reproduction and the preservation of genetic material with an aim to foster relevancy between subject material and human behaviour in any type of society. The tenderness of this aspect of the human existence is well-understood because of its invariable association with soul-revealing human expressions such as love, infatuation, sexual flirtations, all of which are underpinned by arousal, desire and/or pleasure. Assuming that increased knowledge correlates with increased confidence, the proposed approach may provide the nurse with an adequate knowledge base to overcome well-known barriers in communicating with their patients about matters of sexual health and intimacy. Copyright © 2011 Elsevier Ltd. All rights reserved.

The common extremalities in biology and physics maximum energy dissipation principle in chemistry, biology, physics and evolution

CERN Document Server

Moroz, Adam

2011-01-01

This book is the first unified systemic description of dissipative phenomena, taking place in biology, and non-dissipative (conservative) phenomena, which is more relevant to physics. Fully updated and revised, this new edition extends our understanding of nonlinear phenomena in biology and physics from the extreme / optimal perspective. The first book to provide understanding of physical phenomena from a biological perspective and biological phenomena from a physical perspective Discusses emerging fields and analysis Provides examples.

On the relevance of sharp gamma-ray features for indirect dark matter searches

International Nuclear Information System (INIS)

Bringmann, Torsten; Calore, Francesca; Weniger, Christoph

2011-06-01

Gamma rays from the annihilation of dark matter particles in the Galactic halo provide a particularly promising means of indirectly detecting dark matter. Here, we demonstrate that pronounced spectral features near the kinematic cutoff at the dark matter particles' mass, which is a generic prediction for most models, can significantly improve the sensitivity of gamma-ray telescopes to dark matter signals. We derive projected limits on such features (including the traditionally looked-for line signals) and show that these can be very efficient in constraining the nature of dark matter. (orig.)

Stress and adaptation : Toward ecologically relevant animal models

NARCIS (Netherlands)

Koolhaas, Jaap M.; Boer, Sietse F. de; Buwalda, Bauke

Animal models have contributed considerably to the current understanding of mechanisms underlying the role of stress in health and disease. Despite the progress made already, much more can be made by more carefully exploiting animals' and humans' shared biology, using ecologically relevant models.

Hyphae-specific genes HGC1, ALS3, HWP1, and ECE1 and relevant signaling pathways in Candida albicans.

Science.gov (United States)

Fan, Yan; He, Hong; Dong, Yan; Pan, Hengbiao

2013-12-01

Fungal virulence mechanisms include adhesion to epithelia, morphogenesis, production of secretory hydrolytic enzymes, and phenotype switching, all of which contribute to the process of pathogenesis. A striking feature of the biology of Candida albicans is its ability to grow in yeast, pseudohyphal, and hyphal forms. The hyphal form plays an important role in causing disease, by invading epithelial cells and causing tissue damage. In this review, we illustrate some of the main hyphae-specific genes, namely HGC1, UME6, ALS3, HWP1, and ECE1, and their relevant and reversed signal transduction pathways in reactions stimulated by environmental factors, including pH, CO2, and serum.

VISUALIZATION OF BIOLOGICAL TISSUE IMPEDANCE PARAMETERS

Directory of Open Access Journals (Sweden)

V. I. Bankov

2016-01-01

Full Text Available Objective. Investigation the opportunity for measurement of biological tissue impedance to visualize its parameters.Materials and methods. Studies were undertook on the experimental facility, consists of registrating measuring cell, constructed from flat inductors system, formed in oscillatory circuit, herewith investigated biological tissue is the part of this oscillatory circuit. An excitation of oscillatory circuit fulfilled by means of exciter inductor which forms impulse complex modulated electromagnetic field (ICM EMF. The measurement process and visualizations provided by set of certificated instruments: a digital oscillograph AKTAKOM ADS-2221MV, a digital generator АКТАКОМ AWG-4150 (both with software and a gauge RLC E7-22. Comparative dynamic studies of fixed volume and weight pig’s blood, adipose tissue, muscular tissue impedance were conducted by contact versus contactless methods. Contactless method in contrast to contact method gives opportunity to obtain the real morphological visualization of biological tissue irrespective of their nature.Results. Comparison of contact and contactless methods of impedance measurement shows that the inductance to capacitance ratio X(L / X(C was equal: 17 – for muscular tissue, 4 – for blood, 1 – for adipose tissue. It demonstrates the technical correspondence of both impedance registration methods. If propose the base relevance of X (L and X (C parameters for biological tissue impedance so contactless measurement method for sure shows insulating properties of adipose tissue and high conductivity for blood and muscular tissue in fixed volume-weight parameters. Registration of biological tissue impedance complex parameters by contactless method with the help of induced ICM EMF in fixed volume of biological tissue uncovers the most important informative volumes to characterize morphofunctional condition of biological tissue namely X (L / X (C.Conclusion. Contactless method of biological

Discrimination between biological interfaces and crystal-packing contacts

Directory of Open Access Journals (Sweden)

Yuko Tsuchiya

2008-11-01

Full Text Available Yuko Tsuchiya1, Haruki Nakamura2, Kengo Kinoshita1,31Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan; 2Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan; 3Bioinformatics Research and Development, JST, 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, JapanAbstract: A discrimination method between biologically relevant interfaces and artificial crystal-packing contacts in crystal structures was constructed. The method evaluates protein-protein interfaces in terms of complementarities for hydrophobicity, electrostatic potential and shape on the protein surfaces, and chooses the most probable biological interfaces among all possible contacts in the crystal. The method uses a discriminator named as “COMP”, which is a linear combination of the complementarities for the above three surface features and does not correlate with the contact area. The discrimination of homo-dimer interfaces from symmetry-related crystal-packing contacts based on the COMP value achieved the modest success rate. Subsequent detailed review of the discrimination results raised the success rate to about 88.8%. In addition, our discrimination method yielded some clues for understanding the interaction patterns in several examples in the PDB. Thus, the COMP discriminator can also be used as an indicator of the “biological-ness” of protein-protein interfaces.Keywords: protein-protein interaction, complementarity analysis, homo-dimer interface, crystal-packing contact, biological interfaces

TinkerCell: modular CAD tool for synthetic biology

Science.gov (United States)

Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

2009-01-01

Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API). TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at . Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled and analyzed computationally. TinkerCell can readily

TinkerCell: modular CAD tool for synthetic biology

Directory of Open Access Journals (Sweden)

Bergmann Frank T

2009-10-01

Full Text Available Abstract Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API. TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at http://www.tinkercell.com. Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled

Chemistry and the worm: Caenorhabditis elegans as a platform for integrating chemical and biological research.

Science.gov (United States)

Hulme, S Elizabeth; Whitesides, George M

2011-05-16

This Review discusses the potential usefulness of the worm Caenorhabditis elegans as a model organism for chemists interested in studying living systems. C. elegans, a 1 mm long roundworm, is a popular model organism in almost all areas of modern biology. The worm has several features that make it attractive for biology: it is small (1000 cells), transparent, and genetically tractable. Despite its simplicity, the worm exhibits complex phenotypes associated with multicellularity: the worm has differentiated cells and organs, it ages and has a well-defined lifespan, and it is capable of learning and remembering. This Review argues that the balance between simplicity and complexity in the worm will make it a useful tool in determining the relationship between molecular-scale phenomena and organism-level phenomena, such as aging, behavior, cognition, and disease. Following an introduction to worm biology, the Review provides examples of current research with C. elegans that is chemically relevant. It also describes tools-biological, chemical, and physical-that are available to researchers studying the worm. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inference problems in structural biology

DEFF Research Database (Denmark)

Olsson, Simon

The structure and dynamics of biological molecules are essential for their function. Consequently, a wealth of experimental techniques have been developed to study these features. However, while experiments yield detailed information about geometrical features of molecules, this information is of...

Biology and medicine of soccer: an update.

Science.gov (United States)

Shephard, R J

1999-10-01

Recent literature on the biology and medicine of soccer (primarily since 1990) has been accumulated by a combination of computer searching of relevant databases and review of the author's extensive files. From a total of 9681 papers, 540 were selected for closer scrutiny and 370 are discussed in the present review. These articles cover patterns of play and the resulting energy demands, the nutritional requirements of soccer, the anthropometric, physiological, biochemical and immunological characteristics of successful players, the influence of environmental stressors (heat, cold, hypoxia and time zone shifts), special features of female and junior competitors, selected issues in training, and the incidence and prevention of injuries. The information presented has important implications for the safety and success of soccer players; the challenge is now to ensure that this information is understood and acted upon by coaches and individual team members.

Interaction of dermatologically relevant nanoparticles with skin cells and skin

Directory of Open Access Journals (Sweden)

Annika Vogt

2014-12-01

Full Text Available The investigation of nanoparticle interactions with tissues is complex. High levels of standardization, ideally testing of different material types in the same biological model, and combinations of sensitive imaging and detection methods are required. Here, we present our studies on nanoparticle interactions with skin, skin cells, and biological media. Silica, titanium dioxide and silver particles were chosen as representative examples for different types of skin exposure to nanomaterials, e.g., unintended environmental exposure (silica versus intended exposure through application of sunscreen (titanium dioxide or antiseptics (silver. Because each particle type exhibits specific physicochemical properties, we were able to apply different combinations of methods to examine skin penetration and cellular uptake, including optical microscopy, electron microscopy, X-ray microscopy on cells and tissue sections, flow cytometry of isolated skin cells as well as Raman microscopy on whole tissue blocks. In order to assess the biological relevance of such findings, cell viability and free radical production were monitored on cells and in whole tissue samples. The combination of technologies and the joint discussion of results enabled us to look at nanoparticle–skin interactions and the biological relevance of our findings from different angles.

Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

Directory of Open Access Journals (Sweden)

A. Kushki

2009-02-01

Full Text Available This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.

Exemplary Programs in Secondary School Biology.

Science.gov (United States)

McComas, William F.; Penick, John E.

1989-01-01

Summarizes 10 exemplary programs which address topics on individualized biology, a modified team approach, limnology, physical anthropology, the relevance of biology to society, ecology, and health. Provides names and addresses of contact persons for further information. Units cover a broad range of abilities and activities. (RT)

Skin Cancer: Biology, Risk Factors & Treatment

Science.gov (United States)

... turn Javascript on. Feature: Skin Cancer Skin Cancer: Biology, Risk Factors & Treatment Past Issues / Summer 2013 Table ... Articles Skin Cancer Can Strike Anyone / Skin Cancer: Biology, Risk Factors & Treatment / Timely Healthcare Checkup Catches Melanoma ...

T-ray relevant frequencies for osteosarcoma classification

Science.gov (United States)

Withayachumnankul, W.; Ferguson, B.; Rainsford, T.; Findlay, D.; Mickan, S. P.; Abbott, D.

2006-01-01

We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.

Brain responses to language-relevant musical features in adolescent cochlear implant users before and after an intensive music training program

DEFF Research Database (Denmark)

Petersen, Bjørn; Weed, Ethan; Hansen, Mads

Brain responses to language-relevant musical features in adolescent cochlear implant users before and after an intensive music training program Petersen B.1,2, Weed E.1,3, Hansen M.1,4, Sørensen S.D.3 , Sandmann P.5 , Vuust P.1,2 1Center of Functionally Integrative Neuroscience, Aarhus University......, rhythm and intensity). Difference waves for the rhythm deviant were analyzed in the time window between 300 and 320 ms. Separate mixed-model ANOVAs were performed for left and right fronto-central electrodes. Paired t-tests were used to analyze the behavioral data. Here we present preliminary analyses...... of ERP responses to the rhythm deviant stimuli and results from a behavioral rhythm discrimination test. For both left and right electrode sites we found a main effect of group, driven by higher mean amplitude in the NH group. There was no main effect of training. Left hemisphere sites showed...

Demands on attention and the role of response priming in visual discrimination of feature conjunctions.

Science.gov (United States)

Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie

2004-10-01

This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Science.gov (United States)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

The relevance of nanoscale biological fragments for ice nucleation in clouds

Science.gov (United States)

O‧Sullivan, D.; Murray, B. J.; Ross, J. F.; Whale, T. F.; Price, H. C.; Atkinson, J. D.; Umo, N. S.; Webb, M. E.

2015-01-01

Most studies of the role of biological entities as atmospheric ice-nucleating particles have focused on relatively rare supermicron particles such as bacterial cells, fungal spores and pollen grains. However, it is not clear that there are sufficient numbers of these particles in the atmosphere to strongly influence clouds. Here we show that the ice-nucleating activity of a fungus from the ubiquitous genus Fusarium is related to the presence of nanometre-scale particles which are far more numerous, and therefore potentially far more important for cloud glaciation than whole intact spores or hyphae. In addition, we quantify the ice-nucleating activity of nano-ice nucleating particles (nano-INPs) washed off pollen and also show that nano-INPs are present in a soil sample. Based on these results, we suggest that there is a reservoir of biological nano-INPs present in the environment which may, for example, become aerosolised in association with fertile soil dust particles.

YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

KAUST Repository

Kleftogiannis, Dimitrios A.; Theofilatos, Konstantinos; Likothanassis, Spiros; Mavroudi, Seferina

2015-01-01

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

KAUST Repository

Kleftogiannis, Dimitrios A.

2015-01-23

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise

OpenAIRE

Ahveninen, Jyrki; Hämäläinen, Matti; Jääskeläinen, Iiro P.; Ahlfors, Seppo P.; Huang, Samantha; Lin, Fa-Hsuan; Raij, Tommi; Sams, Mikko; Vasios, Christos E.; Belliveau, John W.

2011-01-01

How can we concentrate on relevant sounds in noisy environments? A “gain model” suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A “tuning model” suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMR...

Mast cells: potential positive and negative roles in tumor biology.

Science.gov (United States)

Marichal, Thomas; Tsai, Mindy; Galli, Stephen J

2013-11-01

Mast cells are immune cells that reside in virtually all vascularized tissues. Upon activation by diverse mechanisms, mast cells can secrete a broad array of biologically active products that either are stored in the cytoplasmic granules of the cells (e.g., histamine, heparin, various proteases) or are produced de novo upon cell stimulation (e.g., prostaglandins, leukotrienes, cytokines, chemokines, and growth factors). Mast cells are best known for their effector functions during anaphylaxis and acute IgE-associated allergic reactions, but they also have been implicated in a wide variety of processes that maintain health or contribute to disease. There has been particular interest in the possible roles of mast cells in tumor biology. In vitro studies have shown that mast cells have the potential to influence many aspects of tumor biology, including tumor development, tumor-induced angiogenesis, and tissue remodeling, and the shaping of adaptive immune responses to tumors. Yet, the actual contributions of mast cells to tumor biology in vivo remain controversial. Here, we review some basic features of mast cell biology with a special emphasis on those relevant to their potential roles in tumors. We discuss how using in vivo tumor models in combination with models in which mast cell function can be modulated has implicated mast cells in the regulation of host responses to tumors. Finally, we summarize data from studies of human tumors that suggest either beneficial or detrimental roles for mast cells in tumors. ©2013 AACR.

Design control considerations for biologic-device combination products.

Science.gov (United States)

Anderson, Dave; Liu, Roger; Anand Subramony, J; Cammack, Jon

2017-03-01

Combination products are therapeutic and diagnostic medical products that combine drugs, devices, and/or biological products with one another. Historically, biologics development involved identifying efficacious doses administered to patients intravenously or perhaps by a syringe. Until fairly recently, there has been limited focus on developing an accompanying medical device, such as a prefilled syringe or auto-injector, to enable easy and more efficient delivery. For the last several years, and looking forward, where there may be little to distinguish biologics medicines with relatively similar efficacy profiles, the biotechnology market is beginning to differentiate products by patient-focused, biologic-device based combination products. As innovative as biologic-device combination products are, they can pose considerable development, regulatory, and commercialization challenges due to unique physicochemical properties and special clinical considerations (e.g., dosing volumes, frequency, co-medications, etc.) of the biologic medicine. A biologic-device combination product is a marriage between two partners with "cultural differences," so to speak. There are clear differences in the development, review, and commercialization processes of the biologic and the device. When these two cultures come together in a combination product, developers and reviewers must find ways to address the design controls and risk management processes of both the biologic and device, and knit them into a single entity with supporting product approval documentation. Moreover, digital medicine and connected health trends are pushing the boundaries of combination product development and regulations even further. Despite an admirable cooperation between industry and FDA in recent years, unique product configurations and design features have resulted in review challenges. These challenges have prompted agency reviewers to modernize consultation processes, while at the same time, promoting

Optimized maintenance concept of safety relevant valves related to ageing management features in nuclear power plants

International Nuclear Information System (INIS)

Koring, R.

2007-01-01

This paper presents the existing concept in E.ON Kernkraft and its sound application to ageing management issues by focussing on group 2 components such as safety relevant valves. It is demonstrated how the maintenance concept of safety relevant valves is supported by a valve diagnostic system accompanied by an applied procedure to assess the measured results with respect to the required functionality and ageing phenomena. Furthermore this concept has been developed to optimize the existing preventive maintenance of the safety relevant valves by implementing condition oriented aspects derived from the diagnostic results. The main issue of this maintenance concept is to demonstrate the high level of the secured function, reliability and performance of the safety relevant valves within an integrated ageing management. Additionally it offers improvements of all preventive maintenance issues as maintenance periods and the component related volume, spare parts management and costs. (author)

Impact of Thermodynamic Principles in Systems Biology

NARCIS (Netherlands)

Heijnen, J.J.

2010-01-01

It is shown that properties of biological systems which are relevant for systems biology motivated mathematical modelling are strongly shaped by general thermodynamic principles such as osmotic limit, Gibbs energy dissipation, near equilibria and thermodynamic driving force. Each of these aspects

Biologically effective dose distribution based on the linear quadratic model and its clinical relevance

International Nuclear Information System (INIS)

Lee, Steve P.; Leu, Min Y.; Smathers, James B.; McBride, William H.; Parker, Robert G.; Withers, H. Rodney

1995-01-01

Purpose: Radiotherapy plans based on physical dose distributions do not necessarily entirely reflect the biological effects under various fractionation schemes. Over the past decade, the linear-quadratic (LQ) model has emerged as a convenient tool to quantify biological effects for radiotherapy. In this work, we set out to construct a mechanism to display biologically oriented dose distribution based on the LQ model. Methods and Materials: A computer program that converts a physical dose distribution calculated by a commercially available treatment planning system to a biologically effective dose (BED) distribution has been developed and verified against theoretical calculations. This software accepts a user's input of biological parameters for each structure of interest (linear and quadratic dose-response and repopulation kinetic parameters), as well as treatment scheme factors (number of fractions, fractional dose, and treatment time). It then presents a two-dimensional BED display in conjunction with anatomical structures. Furthermore, to facilitate clinicians' intuitive comparison with conventional fractionation regimen, a conversion of BED to normalized isoeffective dose (NID) is also allowed. Results: Two sample cases serve to illustrate the application of our tool in clinical practice. (a) For an orthogonal wedged pair of x-ray beams treating a maxillary sinus tumor, the biological effect at the ipsilateral mandible can be quantified, thus illustrates the so-called 'double-trouble' effects very well. (b) For a typical four-field, evenly weighted prostate treatment using 10 MV x-rays, physical dosimetry predicts a comparable dose at the femoral necks between an alternate two-fields/day and four-fields/day schups. However, our BED display reveals an approximate 21% higher BED for the two-fields/day scheme. This excessive dose to the femoral necks can be eliminated if the treatment is delivered with a 3:2 (anterio-posterior/posterio-anterior (AP

The Relevance of Biological Sciences in the 21st Century | Onyeka ...

African Journals Online (AJOL)

Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives ... Biological Sciences, as the name implies, is a group of sciences, rather than a ... knowledge is better assessed by the various problems of modern civilization ... in the improvement of food supply and elimination of hereditary diseases.

Xylella fastidiosa comparative genomic database is an information resource to explore the annotation, genomic features, and biology of different strains

Directory of Open Access Journals (Sweden)

Alessandro M. Varani

2012-01-01

Full Text Available The Xylella fastidiosa comparative genomic database is a scientific resource with the aim to provide a user-friendly interface for accessing high-quality manually curated genomic annotation and comparative sequence analysis, as well as for identifying and mapping prophage-like elements, a marked feature of Xylella genomes. Here we describe a database and tools for exploring the biology of this important plant pathogen. The hallmarks of this database are the high quality genomic annotation, the functional and comparative genomic analysis and the identification and mapping of prophage-like elements. It is available from web site http://www.xylella.lncc.br.

Enhanced feature integration in musicians

DEFF Research Database (Denmark)

Hansen, Niels Christian; Højlund, Andreas; Møller, Cecilie

the classical oddball control paradigm which used identical sounds. This novel finding supports the dependent processing hypothesis suggesting that musicians recruit overlapping neural resources facilitating more holistic representations of domain-relevant stimuli. These specialised refinements in predictive......Distinguishing and integrating features of sensory input is essential to human survival and no less paramount in music perception and cognition. Yet, little is known about training-induced plasticity of neural mechanisms for auditory feature integration. This study aimed to contrast the two...

Supervised Variational Relevance Learning, An Analytic Geometric Feature Selection with Applications to Omic Datasets.

Science.gov (United States)

Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B P; Caticha, Nestor

2015-01-01

We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a cost function that penalizes large intraclass distances and favors small interclass distances. We find analytically the metric tensor that minimizes the cost function. Preprocessing the patterns by doing linear transformations using the metric tensor yields a dataset which can be more efficiently classified. We test our methods using publicly available datasets, for some standard classifiers. Among these datasets, two were tested by the MAQC-II project and, even without the use of further preprocessing, our results improve on their performance.

New Perspectives on Rodent Models of Advanced Paternal Age: Relevance to Autism

Directory of Open Access Journals (Sweden)

Claire J Foldi

2011-06-01

Full Text Available Offspring of older fathers have an increased risk of various adverse health outcomes, including autism and schizophrenia. With respect to biological mechanisms for this association, there are many more germline cell divisions in the life history of a sperm relative to that of an oocyte. This leads to more opportunities for copy error mutations in germ cells from older fathers. Evidence also suggests that epigenetic patterning in the sperm from older men is altered. Rodent models provide an experimental platform to examine the association between paternal age and brain development. Several rodent models of advanced paternal age (APA have been published with relevance to intermediate phenotypes related to autism. All four published APA models vary in key features creating a lack of consistency with respect to behavioural phenotypes. A consideration of common phenotypes that emerge from these APA-related mouse models may be informative in the exploration of the molecular and neurobiological correlates of APA.

Testing aggressive behaviour in a feeding context: Importance of ethologically relevant stimuli.

Science.gov (United States)

González, Daniel; Szenczi, Péter; Bánszegi, Oxána; Hudson, Robyn

2018-05-01

The choice of stimuli used in tests of animal behaviour can have a critical effect on the outcome. Here we report two experiments showing how different foods influenced aggressive behaviour in competition tests at weaning among littermates of the domestic cat. Whereas in Experiment 1 canned food elicited almost no overt competition, a piece of raw beef rib elicited clearly aggressive behaviour among littermates. In Experiment 2 the food stimuli were chosen to differ from raw beef rib in various combinations of taste/smell, texture and monopolizability. Kittens showed different levels of aggression in response to the five stimuli tested, which suggests that the strong effect of beef rib in eliciting aggressive behaviour was due to a complex combination of features. We suggest that using stimuli approximating the evolved, functional significance to the species concerned is more likely to result in robust, biologically relevant behaviours than more artificial stimuli. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimized feature subsets for epileptic seizure prediction studies.

Science.gov (United States)

Direito, Bruno; Ventura, Francisco; Teixeira, César; Dourado, António

2011-01-01

The reduction of the number of EEG features to give as inputs to epilepsy seizure predictors is a needed step towards the development of a transportable device for real-time warning. This paper presents a comparative study of three feature selection methods, based on Support Vector Machines. Minimum-Redundancy Maximum-Relevance, Recursive Feature Elimination, Genetic Algorithms, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.

Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

Science.gov (United States)

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

Crossing Boundaries in Undergraduate Biology Education

Science.gov (United States)

Vanderklein, Dirk; Munakata, Mika; McManus, Jason

2016-01-01

In an effort to make mathematics relevant to biology students, the authors developed two modules that sought to integrate mathematics and ecology instruction to differing degrees. The modules were developed by a team of biology and mathematics educators and were implemented in an ecology course using three different instructional methods for three…

The Widespread Prevalence and Functional Significance of Silk-Like Structural Proteins in Metazoan Biological Materials.

Directory of Open Access Journals (Sweden)

Carmel McDougall

Full Text Available In nature, numerous mechanisms have evolved by which organisms fabricate biological structures with an impressive array of physical characteristics. Some examples of metazoan biological materials include the highly elastic byssal threads by which bivalves attach themselves to rocks, biomineralized structures that form the skeletons of various animals, and spider silks that are renowned for their exceptional strength and elasticity. The remarkable properties of silks, which are perhaps the best studied biological materials, are the result of the highly repetitive, modular, and biased amino acid composition of the proteins that compose them. Interestingly, similar levels of modularity/repetitiveness and similar bias in amino acid compositions have been reported in proteins that are components of structural materials in other organisms, however the exact nature and extent of this similarity, and its functional and evolutionary relevance, is unknown. Here, we investigate this similarity and use sequence features common to silks and other known structural proteins to develop a bioinformatics-based method to identify similar proteins from large-scale transcriptome and whole-genome datasets. We show that a large number of proteins identified using this method have roles in biological material formation throughout the animal kingdom. Despite the similarity in sequence characteristics, most of the silk-like structural proteins (SLSPs identified in this study appear to have evolved independently and are restricted to a particular animal lineage. Although the exact function of many of these SLSPs is unknown, the apparent independent evolution of proteins with similar sequence characteristics in divergent lineages suggests that these features are important for the assembly of biological materials. The identification of these characteristics enable the generation of testable hypotheses regarding the mechanisms by which these proteins assemble and direct the

A data integration approach for cell cycle analysis oriented to model simulation in systems biology

Directory of Open Access Journals (Sweden)

Mosca Ettore

2007-08-01

Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

Mathematical Biology Modules Based on Modern Molecular Biology and Modern Discrete Mathematics

Science.gov (United States)

Davies, Robin; Hodge, Terrell; Enyedi, Alexander

2010-01-01

We describe an ongoing collaborative curriculum materials development project between Sweet Briar College and Western Michigan University, with support from the National Science Foundation. We present a collection of modules under development that can be used in existing mathematics and biology courses, and we address a critical national need to introduce students to mathematical methods beyond the interface of biology with calculus. Based on ongoing research, and designed to use the project-based-learning approach, the modules highlight applications of modern discrete mathematics and algebraic statistics to pressing problems in molecular biology. For the majority of projects, calculus is not a required prerequisite and, due to the modest amount of mathematical background needed for some of the modules, the materials can be used for an early introduction to mathematical modeling. At the same time, most modules are connected with topics in linear and abstract algebra, algebraic geometry, and probability, and they can be used as meaningful applied introductions into the relevant advanced-level mathematics courses. Open-source software is used to facilitate the relevant computations. As a detailed example, we outline a module that focuses on Boolean models of the lac operon network. PMID:20810955

Mathematical biology modules based on modern molecular biology and modern discrete mathematics.

Science.gov (United States)

Robeva, Raina; Davies, Robin; Hodge, Terrell; Enyedi, Alexander

2010-01-01

We describe an ongoing collaborative curriculum materials development project between Sweet Briar College and Western Michigan University, with support from the National Science Foundation. We present a collection of modules under development that can be used in existing mathematics and biology courses, and we address a critical national need to introduce students to mathematical methods beyond the interface of biology with calculus. Based on ongoing research, and designed to use the project-based-learning approach, the modules highlight applications of modern discrete mathematics and algebraic statistics to pressing problems in molecular biology. For the majority of projects, calculus is not a required prerequisite and, due to the modest amount of mathematical background needed for some of the modules, the materials can be used for an early introduction to mathematical modeling. At the same time, most modules are connected with topics in linear and abstract algebra, algebraic geometry, and probability, and they can be used as meaningful applied introductions into the relevant advanced-level mathematics courses. Open-source software is used to facilitate the relevant computations. As a detailed example, we outline a module that focuses on Boolean models of the lac operon network.

Manufacturing economics of plant-made biologics: case studies in therapeutic and industrial enzymes.

Science.gov (United States)

Tusé, Daniel; Tu, Tiffany; McDonald, Karen A

2014-01-01

Production of recombinant biologics in plants has received considerable attention as an alternative platform to traditional microbial and animal cell culture. Industrially relevant features of plant systems include proper eukaryotic protein processing, inherent safety due to lack of adventitious agents, more facile scalability, faster production (transient systems), and potentially lower costs. Lower manufacturing cost has been widely claimed as an intuitive feature of the platform by the plant-made biologics community, even though cost information resides within a few private companies and studies accurately documenting such an advantage have been lacking. We present two technoeconomic case studies representing plant-made enzymes for diverse applications: human butyrylcholinesterase produced indoors for use as a medical countermeasure and cellulases produced in the field for the conversion of cellulosic biomass into ethanol as a fuel extender. Production economics were modeled based on results reported with the latest-generation expression technologies on Nicotiana host plants. We evaluated process unit operations and calculated bulk active and per-dose or per-unit costs using SuperPro Designer modeling software. Our analyses indicate that substantial cost advantages over alternative platforms can be achieved with plant systems, but these advantages are molecule/product-specific and depend on the relative cost-efficiencies of alternative sources of the same product.

Manufacturing Economics of Plant-Made Biologics: Case Studies in Therapeutic and Industrial Enzymes

Directory of Open Access Journals (Sweden)

Daniel Tusé

2014-01-01

Full Text Available Production of recombinant biologics in plants has received considerable attention as an alternative platform to traditional microbial and animal cell culture. Industrially relevant features of plant systems include proper eukaryotic protein processing, inherent safety due to lack of adventitious agents, more facile scalability, faster production (transient systems, and potentially lower costs. Lower manufacturing cost has been widely claimed as an intuitive feature of the platform by the plant-made biologics community, even though cost information resides within a few private companies and studies accurately documenting such an advantage have been lacking. We present two technoeconomic case studies representing plant-made enzymes for diverse applications: human butyrylcholinesterase produced indoors for use as a medical countermeasure and cellulases produced in the field for the conversion of cellulosic biomass into ethanol as a fuel extender. Production economics were modeled based on results reported with the latest-generation expression technologies on Nicotiana host plants. We evaluated process unit operations and calculated bulk active and per-dose or per-unit costs using SuperPro Designer modeling software. Our analyses indicate that substantial cost advantages over alternative platforms can be achieved with plant systems, but these advantages are molecule/product-specific and depend on the relative cost-efficiencies of alternative sources of the same product.

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

Science.gov (United States)

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Memory for Physical Features of Discourse as a Function of Their Relevance.

Science.gov (United States)

Fisher, Ronald P.; Cuervo, Asela

Memory for sex of the speaker and language of presentation of a spoken message was high and reliably better when the features were instrumental for comprehending the message than when they were not. This suggests that the physical characteristics of an event may be deeply or elaborately encoded when they are meaningful in light of the task…

The main features of electrical stimulation of biological tissues by implant electrodes: study from engineering perspective and equipment development to produce

International Nuclear Information System (INIS)

Suarez Bagnasco, D.; Alvarez Alonso, J.; Suarez Antola, R.

2004-08-01

The main features of electrical stimulation of biological tissues by implant electrodes are studied.These electrodes are applied in neural prostheses and cardiac pacing.Threshold phenomena are stressed and some aspects related with implant electrode design are discussed. A fairly through theoretical research about the optimal pulse shape for electrical stimulation of biological tissues is done.The excitation functional is introduced as a criterium to identify threshold pulses of electric current. We obtain the optimal pulse shapes that minimize the energy dissipated in tissues, or the energy taken by the load seen by the pulse generator, amongst other criteria.We show how these pulse shapes can be determined from experimentally measured strength-duration (S-D) curves using rectangular pulses of current. The development of a prototype of a new equipment is described.The equipment may be used to measure S-D curves and with this information it is able to syntetize the abovementioned optimal pulse shapes. The top-down design process is presented, involving both hardware and software.The construction and assembling of the prototype, as well as the implementation of software are described.Some testing and measures with the prototype, including test with biological tissues are described and assessed

Assessing biological invasions in European Seas: Biological traits of the most widespread non-indigenous species

Science.gov (United States)

Cardeccia, Alice; Marchini, Agnese; Occhipinti-Ambrogi, Anna; Galil, Bella; Gollasch, Stephan; Minchin, Dan; Narščius, Aleksas; Olenin, Sergej; Ojaveer, Henn

2018-02-01

The biological traits of the sixty-eight most widespread multicellular non-indigenous species (MWNIS) in European Seas: Baltic Sea, Western European Margin of the Atlantic Ocean and the Mediterranean Sea were examined. Data for nine biological traits was analyzed, and a total of 41 separate categories were used to describe the biological and ecological functions of these NIS. Our findings show that high dispersal ability, high reproductive rate and ecological generalization are the biological traits commonly associated with MWNIS. The functional groups that describe most of the 68 MWNIS are: photoautotrophic, zoobenthic (both sessile and motile) and nektonic predatory species. However, these 'most widespread' species comprise a wide range of taxa and biological trait profiles; thereby a clear "identikit of a perfect invader" for marine and brackish environments is difficult to define. Some traits, for example: "life form", "feeding method" and "mobility", feature multiple behaviours and strategies. Even species introduced by a single pathway, e.g. vessels, feature diverse biological trait profiles. MWNIS likely to impact community organization, structure and diversity are often associated with brackish environments. For many traits ("life form", "sociability", "reproductive type", "reproductive frequency", "haploid and diploid dispersal" and "mobility"), the categories mostly expressed by the impact-causing MWNIS do not differ substantially from the whole set of MWNIS.

The Importance of Biological Databases in Biological Discovery.

Science.gov (United States)

Baxevanis, Andreas D; Bateman, Alex

2015-06-19

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed. Copyright © 2015 John Wiley & Sons, Inc.

Mesoscopic models of biological membranes

DEFF Research Database (Denmark)

Venturoli, M.; Sperotto, Maria Maddalena; Kranenburg, M.

2006-01-01

Phospholipids are the main components of biological membranes and dissolved in water these molecules self-assemble into closed structures, of which bilayers are the most relevant from a biological point of view. Lipid bilayers are often used, both in experimental and by theoretical investigations...... to coarse grain a biological membrane. The conclusion of this comparison is that there can be many valid different strategies, but that the results obtained by the various mesoscopic models are surprisingly consistent. A second objective of this review is to illustrate how mesoscopic models can be used...

Biological fuel cells and their applications

OpenAIRE

Shukla, AK; Suresh, P; Berchmans, S; Rajendran, A

2004-01-01

One type of genuine fuel cell that does hold promise in the long-term is the biological fuel cell. Unlike conventional fuel cells, which employ hydrogen, ethanol and methanol as fuel, biological fuel cells use organic products produced by metabolic processes or use organic electron donors utilized in the growth processes as fuels for current generation. A distinctive feature of biological fuel cells is that the electrode reactions are controlled by biocatalysts, i.e. the biological redox-reac...

Bridging Physics and Biology Using Resistance and Axons

Science.gov (United States)

Dyer, Joshua M.

2014-01-01

When teaching physics, it is often difficult to get biology-oriented students to see the relevance of physics. A complaint often heard is that biology students are required to take physics for the Medical College Admission Test (MCAT) as part of a "weeding out" process, but that they don't feel like they need physics for biology. Despite…

Knowledge-based driver assistance systems traffic situation description and situation feature relevance

CERN Document Server

Huelsen, Michael

2014-01-01

The comprehension of a traffic situation plays a major role in driving a vehicle. Interpretable information forms a basis for future projection, decision making and action performing, such as navigating, maneuvering and driving control. Michael Huelsen provides an ontology-based generic traffic situation description capable of supplying various advanced driver assistance systems with relevant information about the current traffic situation of a vehicle and its environment. These systems are enabled to perform reasonable actions and approach visionary goals such as injury and accident free driv

Real-time hypothesis driven feature extraction on parallel processing architectures

DEFF Research Database (Denmark)

Granmo, O.-C.; Jensen, Finn Verner

2002-01-01

the problem of higher-order feature-content/feature-feature correlation, causally complexly interacting features are identified through Bayesian network d-separation analysis and combined into joint features. When used on a moderately complex object-tracking case, the technique is able to select...... extraction, which selectively extract relevant features one-by-one, have in some cases achieved real-time performance on single processing element architectures. In this paperwe propose a novel technique which combines the above two approaches. Features are selectively extracted in parallelizable sets...

Environmental biodosimetry: a biologically relevant tool for ecological risk assessment and biomonitoring

Energy Technology Data Exchange (ETDEWEB)

Ulsh, B. E-mail: ulshb@mcmaster.ca; Hinton, T.G.; Congdon, J.D.; Dugan, L.C.; Whicker, F.W.; Bedford, J.S

2003-07-01

Biodosimetry, the estimation of received doses by determining the frequency of radiation-induced chromosome aberrations, is widely applied in humans acutely exposed as a result of accidents or for clinical purposes, but biodosimetric techniques have not been utilized in organisms chronically exposed to radionuclides in contaminated environments. The application of biodosimetry to environmental exposure scenarios could greatly improve the accuracy, and reduce the uncertainties, of ecological risk assessments and biomonitoring studies, because no assumptions are required regarding external exposure rates and the movement of organisms into and out of contaminated areas. Furthermore, unlike residue analyses of environmental media environmental biodosimetry provides a genetically relevant biomarker of cumulative lifetime exposure. Symmetrical chromosome translocations can impact reproductive success, and could therefore prove to be ecologically relevant as well. We describe our experience in studying aberrations in the yellow-bellied slider turtle as an example of environmental biodosimetry.

e-Biologics: Fabrication of Sustainable Electronics with "Green" Biological Materials.

Science.gov (United States)

Lovley, Derek R

2017-06-27

The growing ubiquity of electronic devices is increasingly consuming substantial energy and rare resources for materials fabrication, as well as creating expansive volumes of toxic waste. This is not sustainable. Electronic biological materials (e-biologics) that are produced with microbes, or designed with microbial components as the guide for synthesis, are a potential green solution. Some e-biologics can be fabricated from renewable feedstocks with relatively low energy inputs, often while avoiding the harsh chemicals used for synthesizing more traditional electronic materials. Several are completely free of toxic components, can be readily recycled, and offer unique features not found in traditional electronic materials in terms of size, performance, and opportunities for diverse functionalization. An appropriate investment in the concerted multidisciplinary collaborative research required to identify and characterize e-biologics and to engineer materials and devices based on e-biologics could be rewarded with a new "green age" of sustainable electronic materials and devices. Copyright © 2017 Lovley.

Biologic Therapy and Asthma.

Science.gov (United States)

Viswanathan, Ravi K; Busse, William W

2018-02-01

Although airway inflammation is an intrinsic and key feature of asthma, this response varies in its intensity and translation to clinical characteristics and responsiveness to treatment. The observations that clinical heterogeneity is an important aspect of asthma and a feature that likely dictates and determines responses to treatment in severe asthma, patient responsiveness to medication is incomplete, and risks for exacerbation are increased. The development of biologics, which target selected and specific components of inflammation, has been a promising advance to achieve asthma control in patients with severe disease. This article reviews the current biologics available and under development and how their use has affected asthma and which subpopulations appear to benefit the greatest. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

[Physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands underlying biological activities of these complexes].

Science.gov (United States)

Vanin, A F; Borodulin, R R; Kubrina, L N; Mikoian, V D; Burbaev, D Sh

2013-01-01

Current notions and new experimental data of the authors on physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands (glutathione or cysteine), underlying the ability of the complexes to act as NO molecule and nitrosonium ion donors, are considered. This ability determines various biological activities of dinitrosyl iron complexes--inducing long-lasting vasodilation and thereby long-lasting hypotension in human and animals, inhibiting pellet aggregation, increasing red blood cell elasticity, thereby stimulating microcirculation, and reducing necrotic zone in animals with myocardial infarction. Moreover, dinitrosyl iron complexes are capable of accelerating skin wound healing, improving the function of penile cavernous tissue, blocking apoptosis development in cell cultures. When decomposed dinitrosyl iron complexes can exert cytotoxic effect that can be used for curing infectious and carcinogenic pathologies.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

An Improved Optimization Method for the Relevance Voxel Machine

DEFF Research Database (Denmark)

Ganz, Melanie; Sabuncu, M. R.; Van Leemput, Koen

2013-01-01

In this paper, we will re-visit the Relevance Voxel Machine (RVoxM), a recently developed sparse Bayesian framework used for predicting biological markers, e.g., presence of disease, from high-dimensional image data, e.g., brain MRI volumes. The proposed improvement, called IRVoxM, mitigates the ...

World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Schizophrenia. Part 3

DEFF Research Database (Denmark)

Hasan, Alkomiet; Falkai, Peter; Wobrock, Thomas

2015-01-01

These updated guidelines are based on the first edition of the World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for biological treatment of schizophrenia published in the years 2005 and 2006. For this 2015 revision, all available publications pertaining to the biological...... treatment of schizophrenia were reviewed systematically to allow for an evidence-based update. These guidelines provide evidence-based practice recommendations which are clinically and scientifically relevant. They are intended to be used by all physicians diagnosing and treating patients with schizophrenia...

Electron Transfer in Chemistry and Biology - The Primary Events in ...

Indian Academy of Sciences (India)

transfers, occurs in a cascade in many biological processes, including photosynthesis. ... the model reactions of photosynthetic ... biological relevance. GENERAL I ARTICLE of electrons, respectively. This has entirely changed the earlier framework of interpreting reactions in chemistry and biology. This shift in emphasis ...

On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

Science.gov (United States)

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.

IQ Predicts Biological Motion Perception in Autism Spectrum Disorders

Science.gov (United States)

Rutherford, M. D.; Troje, Nikolaus F.

2012-01-01

Biological motion is easily perceived by neurotypical observers when encoded in point-light displays. Some but not all relevant research shows significant deficits in biological motion perception among those with ASD, especially with respect to emotional displays. We tested adults with and without ASD on the perception of masked biological motion…

Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

Science.gov (United States)

Gutta, Sandeep; Cheng, Qi

2016-03-01

Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

Basics and principles of particle image velocimetry (PIV) for mapping biogenic and biologically relevant flows

NARCIS (Netherlands)

Stamhuis, Eize J.

2006-01-01

Particle image velocimetry (PIV) has proven to be a very useful technique in mapping animal-generated flows or flow patterns relevant to biota. Here, theoretical background is provided and experimental details of 2-dimensional digital PIV are explained for mapping flow produced by or relevant to

Physical interactions among plant MADS-box transcription factors and their biological relevance

NARCIS (Netherlands)

Nougalli Tonaco, I.A.

2008-01-01

The biological interpretation of the genome starts from transcription, and many different signaling pathways are integrated at this level. Transcription factors play a central role in the transcription process, because they select the down-stream genes and determine their spatial and temporal

Conservation biology in Asia: the major policy challenges.

Science.gov (United States)

McNeely, Jeffrey A; Kapoor-Vijay, Promila; Zhi, Lu; Olsvig-Whittaker, Linda; Sheikh, Kashif M; Smith, Andrew T

2009-08-01

With about half the world's human population and booming economies, Asia faces numerous challenges to its biodiversity. The Asia Section of the Society for Conservation Biology has identified some key policy issues in which significant progress can be made. These include developing new sources of funding for forest conservation; identifying potential impacts of energy alternatives on the conservation of biodiversity; curbing the trade in endangered species of plants and animals; a special focus on the conservation of mountain biodiversity; enhancing relevant research; ensuring that conservation biology contributes to major international conventions and funding mechanisms; using conservation biology to build a better understanding of zoonotic diseases; more effectively addressing human-animal conflicts; enhancing community-based conservation; and using conservation biology to help address the pervasive water-deficit problems in much of Asia. These challenges can be met through improved regional cooperation among the relevant stakeholders.

Language identification using excitation source features

CERN Document Server

Rao, K Sreenivasa

2015-01-01

This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivatio...

Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.

Science.gov (United States)

Downer, Joshua D; Rapone, Brittany; Verhein, Jessica; O'Connor, Kevin N; Sutter, Mitchell L

2017-05-24

Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations ( r noise ) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on r noise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in r noise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments. SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations ( r noise ) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on r noise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning

Integration of cardiac proteome biology and medicine by a specialized knowledgebase.

Science.gov (United States)

Zong, Nobel C; Li, Haomin; Li, Hua; Lam, Maggie P Y; Jimenez, Rafael C; Kim, Christina S; Deng, Ning; Kim, Allen K; Choi, Jeong Ho; Zelaya, Ivette; Liem, David; Meyer, David; Odeberg, Jacob; Fang, Caiyun; Lu, Hao-Jie; Xu, Tao; Weiss, James; Duan, Huilong; Uhlen, Mathias; Yates, John R; Apweiler, Rolf; Ge, Junbo; Hermjakob, Henning; Ping, Peipei

2013-10-12

Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.

Automatic processing of unattended object features by functional connectivity

Directory of Open Access Journals (Sweden)

Katja Martina Mayer

2013-05-01

Full Text Available Observers can selectively attend to object features that are relevant for a task. However, unattended task-irrelevant features may still be processed and possibly integrated with the attended features. This study investigated the neural mechanisms for processing both task-relevant (attended and task-irrelevant (unattended object features. The Garner paradigm was adapted for functional magnetic resonance imaging (fMRI to test whether specific brain areas process the conjunction of features or whether multiple interacting areas are involved in this form of feature integration. Observers attended to shape, colour, or non-rigid motion of novel objects while unattended features changed from trial to trial (change blocks or remained constant (no-change blocks during a given block. This block manipulation allowed us to measure the extent to which unattended features affected neural responses which would reflect the extent to which multiple object features are automatically processed. We did not find Garner interference at the behavioural level. However, we designed the experiment to equate performance across block types so that any fMRI results could not be due solely to differences in task difficulty between change and no-change blocks. Attention to specific features localised several areas known to be involved in object processing. No area showed larger responses on change blocks compared to no-change blocks. However, psychophysiological interaction analyses revealed that several functionally-localised areas showed significant positive interactions with areas in occipito-temporal and frontal areas that depended on block type. Overall, these findings suggest that both regional responses and functional connectivity are crucial for processing multi-featured objects.

An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity

Directory of Open Access Journals (Sweden)

Yu Wang

2014-01-01

Full Text Available Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH, to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same class. After the removal of outliers, relevance of features in each cluster is calculated based on their variations in this cluster. The feature relevance is incorporated into distance calculation for classification. The main advantage of SCCFSH lies in the fact that it is capable of solving a classification problem with feature space heterogeneity in an incremental way, which is favorable for online classification tasks with continuously changing data. Experimental results on a series of data sets and application to a database marketing problem show the efficiency and effectiveness of the proposed approach.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

OpenAIRE

Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

Predictive Feature Selection for Genetic Policy Search

Science.gov (United States)

2014-05-22

limited manual intervention are becoming increasingly desirable as more complex tasks in dynamic and high- tempo environments are explored. Reinforcement...states in many domains causes features relevant to the reward variations to be overlooked, which hinders the policy search. 3.4 Parameter Selection PFS...the current feature subset. This local minimum may be “deceptive,” meaning that it does not clearly lead to the global optimal policy ( Goldberg and

Natural Proline-Rich Cyclopolypeptides from Marine Organisms: Chemistry, Synthetic Methodologies and Biological Status.

Science.gov (United States)

Fang, Wan-Yin; Dahiya, Rajiv; Qin, Hua-Li; Mourya, Rita; Maharaj, Sandeep

2016-10-26

Peptides have gained increased interest as therapeutics during recent years. More than 60 peptide drugs have reached the market for the benefit of patients and several hundreds of novel therapeutic peptides are in preclinical and clinical development. The key contributor to this success is the potent and specific, yet safe, mode of action of peptides. Among the wide range of biologically-active peptides, naturally-occurring marine-derived cyclopolypeptides exhibit a broad range of unusual and potent pharmacological activities. Because of their size and complexity, proline-rich cyclic peptides (PRCPs) occupy a crucial chemical space in drug discovery that may provide useful scaffolds for modulating more challenging biological targets, such as protein-protein interactions and allosteric binding sites. Diverse pharmacological activities of natural cyclic peptides from marine sponges, tunicates and cyanobacteria have encouraged efforts to develop cyclic peptides with well-known synthetic methods, including solid-phase and solution-phase techniques of peptide synthesis. The present review highlights the natural resources, unique structural features and the most relevant biological properties of proline-rich peptides of marine-origin, focusing on the potential therapeutic role that the PRCPs may play as a promising source of new peptide-based novel drugs.

Biological treatment of Crohn's disease

DEFF Research Database (Denmark)

Nielsen, Ole Haagen; Bjerrum, Jacob Tveiten; Seidelin, Jakob Benedict

2012-01-01

Introduction of biological agents for the treatment of Crohn's disease (CD) has led to a transformation of the treatment paradigm. Several biological compounds have been approved for patients with CD refractory to conventional treatment: infliximab, adalimumab and certolizumab pegol (and...... natalizumab in several countries outside the European Union). However, despite the use of biologics for more than a decade, questions still remain about the true efficacy and the best treatment regimens - especially about when to discontinue treatment. Furthermore, a need for optimizing treatment...... with biologics still exists, as 20-40% of patients with CD (depending on selection criteria) do not have any relevant response to the current biological agents (i.e. primary failures). A better patient selection might maximize the clinical outcome while minimizing the complications associated with this type...

Identification of low variability textural features for heterogeneity quantification of 18F-FDG PET/CT imaging.

Science.gov (United States)

Cortes-Rodicio, J; Sanchez-Merino, G; Garcia-Fidalgo, M A; Tobalina-Larrea, I

To identify those textural features that are insensitive to both technical and biological factors in order to standardise heterogeneity studies on 18 F-FDG PET imaging. Two different studies were performed. First, nineteen series from a cylindrical phantom filled with different 18 F-FDG activity concentration were acquired and reconstructed using three different protocols. Seventy-two texture features were calculated inside a circular region of interest. The variability of each feature was obtained. Second, the data for 15 patients showing non-pathological liver were acquired. Anatomical and physiological features such as patient's weight, height, body mass index, metabolic active volume, blood glucose level, SUV and SUV standard deviation were also recorded. A liver covering region of interest was delineated and low variability textural features calculated in each patient. Finally, a multivariate Spearman's correlation analysis between biological factors and texture features was performed. Only eight texture features analysed show small variability (feature is, indeed, correlated (Ptextural features that are correlated with neither technical nor biological factors are run percentage, short-zone emphasis and intensity, making them suitable for quantifying functional changes or classifying patients. Other textural features are correlated with technical and biological factors and are, therefore, a source of errors if used for this purpose. Copyright © 2016 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Apparent diffusion coefficient value as a biomarker reflecting morphological and biological features of prostate cancer.

Science.gov (United States)

Bae, Hyeyeol; Yoshida, Soichiro; Matsuoka, Yoh; Nakajima, Hiroshi; Ito, Eisaku; Tanaka, Hiroshi; Oya, Miyako; Nakayama, Takayuki; Takeshita, Hideki; Kijima, Toshiki; Ishioka, Junichiro; Numao, Noboru; Koga, Fumitaka; Saito, Kazutaka; Akashi, Takumi; Fujii, Yasuhisa; Kihara, Kazunori

2014-03-01

To assess whether there is an association between the apparent diffusion coefficient (ADC) value and the pathological characteristics of prostate cancer. The study cohort consisted of 29 consecutive patients with prostate cancer treated with radical prostatectomy. All patients underwent diffusion-weighted MRI before the prostate biopsy. In 42 tumor foci, the associations of the ADC values with the clinicopathological characteristics and Ki-67 labeling index (LI) were analyzed. High-grade cancers (Gleason score [GS] ≥ 4 + 3), larger cancers (maximum diameter (MD) ≥ 16 mm), and highly proliferating cancers (Ki-67 LI ≥ 4.43 %) had significantly lower ADC values, respectively (P value according to age, prostate-specific antigen, presence of extra-prostatic extension, and intra-tumoral stroma proportion. Multivariate analysis showed that GS, Ki-67 LI, and MD had independent and significant correlations with ADC value (P value to predict high-grade cancer foci are 81.8 and 93.5 %, respectively. A low ADC value reflects the morphological and biological features of prostate cancer. Analyzing the ADC value may make it possible to more precisely predict the cancer aggressiveness of each focus before treatment.

Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features

Directory of Open Access Journals (Sweden)

Bissell MJ

2006-03-01

Full Text Available Abstract Background Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. Results Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile. In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO terms and the Conserved Domain Database (CDD protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occured consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists

Contextual Hub Analysis Tool (CHAT: A Cytoscape app for identifying contextually relevant hubs in biological networks [version 2; referees: 2 approved

Directory of Open Access Journals (Sweden)

Tanja Muetze

2016-08-01

Full Text Available Highly connected nodes (hubs in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT, which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest.   Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat.

EURASIP journal on bioinformatics & systems biology

National Research Council Canada - National Science Library

2006-01-01

"The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...

Self-assembled structures and pKa value of oleic acid in systems of biological relevance.

Science.gov (United States)

Salentinig, Stefan; Sagalowicz, Laurent; Glatter, Otto

2010-07-20

In the human digestion process, triglycerides are hydrolyzed by lipases to monoglycerides and the corresponding fatty acids. Here we report the self-assembly of structures in biologically relevant, emulsified oleic acid-monoolein mixtures at various pH values and oleic acid concentrations. Small-angle X-ray scattering, cryogenic transmission electron microscopy, and dynamic light scattering were used to investigate the structures formed, and to follow their transitions while these factors were varied. The addition of oleic acid to monoolein-based cubosomes was found to increase the critical packing parameter in the system. Structural transitions from bicontinuous cubosomes through hexosomes and micellar cubosomes (Fd3m symmetry) to emulsified microemulsions occur with increasing oleic acid concentration. At sufficiently high oleic acid concentration, the internal particle structure was also found to strongly depend on the pH of the aqueous phase: transformations from emulsified microemulsion through micellar cubosomes, hexosomes, and bicontinuous cubosomes to vesicles can be observed as a function of increasing pH. The reversible transition from liquid crystals to vesicles occurs at intestinal pH values (between pH 7 and 8). The hydrodynamic radius of the particles decreases from around 120 nm for internally structured particles to around 60 nm for vesicles. All transitions with pH are reversible. Finally, the apparent pK(a) for oleic acid in monoolein could be determined from the change of structure with pH. This value is within the physiological pH range of the intestine and depends somewhat on composition.

Feature Selection Using Adaboost for Face Expression Recognition

National Research Council Canada - National Science Library

Silapachote, Piyanuch; Karuppiah, Deepak R; Hanson, Allen R

2005-01-01

We propose a classification technique for face expression recognition using AdaBoost that learns by selecting the relevant global and local appearance features with the most discriminating information...

On the interplay between mathematics and biology: hallmarks toward a new systems biology.

Science.gov (United States)

Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M; Alghamdi, Mohammed Ali

2015-03-01

This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach. Copyright © 2014 Elsevier B.V. All rights reserved.

Classifying Written Texts Through Rhythmic Features

NARCIS (Netherlands)

Balint, Mihaela; Dascalu, Mihai; Trausan-Matu, Stefan

2016-01-01

Rhythm analysis of written texts focuses on literary analysis and it mainly considers poetry. In this paper we investigate the relevance of rhythmic features for categorizing texts in prosaic form pertaining to different genres. Our contribution is threefold. First, we define a set of rhythmic

Dysmorphic features and developmental outcome of 2-year-old children.

Science.gov (United States)

Seggers, Jorien; Haadsma, Maaike L; Bos, Arend F; Heineman, Maas Jan; Middelburg, Karin J; van den Heuvel, Edwin R; Hadders-Algra, Mijna

2014-11-01

The aim of this study was to assess the associations between dysmorphic features and neurological, mental, psychomotor, and behavioural development in order to improve our understanding of aetiological pathways leading to minor developmental problems. In our cross-sectional study, 272 generally healthy 2-year-olds (143 males, 129 females; median gestational age 39 weeks, [range 30-43wks]), born after a parental history of subfertility either with or without fertility treatment, were examined. Dysmorphic features were classified as abnormalities (clinically relevant or not), minor anomalies, or common variants according to Merks' classification system. Hempel's neurological assessment resulted in a neurological optimality score (NOS) and fluency score. Mental and psychomotor development were assessed with the Dutch version of the Bayley Scales of Infant Development and behavioural development with the Achenbach Child Behaviour Checklist. Of the different types of dysmorphic feature, clinically relevant abnormalities were most strongly associated with a lower NOS (difference -2.53, 95% confidence interval [CI] -4.23 to -0.83) and fluency score (difference -0.62, 95% CI -1.1 to -0.15). The presence of one or more abnormalities (clinically relevant or not) or one or more common variants was significantly associated with a lower NOS, and the presence of three or more minor anomalies was associated with lower fluency scores. Dysmorphic features were not associated with mental, psychomotor, or behavioural development. As dysmorphic features originate during the first trimester of pregnancy, the association between dysmorphic features and minor alterations in neurodevelopment may suggest an early ontogenetic origin of subtle neurological deviations. © 2014 Mac Keith Press.

The Molecular Biology of Pestiviruses.

Science.gov (United States)

Tautz, Norbert; Tews, Birke Andrea; Meyers, Gregor

2015-01-01

Pestiviruses are among the economically most important pathogens of livestock. The biology of these viruses is characterized by unique and interesting features that are both crucial for their success as pathogens and challenging from a scientific point of view. Elucidation of these features at the molecular level has made striking progress during recent years. The analyses revealed that major aspects of pestivirus biology show significant similarity to the biology of human hepatitis C virus (HCV). The detailed molecular analyses conducted for pestiviruses and HCV supported and complemented each other during the last three decades resulting in elucidation of the functions of viral proteins and RNA elements in replication and virus-host interaction. For pestiviruses, the analyses also helped to shed light on the molecular basis of persistent infection, a special strategy these viruses have evolved to be maintained within their host population. The results of these investigations are summarized in this chapter. © 2015 Elsevier Inc. All rights reserved.

Students' Personal Connection with Science: Investigating the Multidimensional Phenomenological Structure of Self-Relevance

Science.gov (United States)

Hartwell, Matthew; Kaplan, Avi

2018-01-01

This paper presents findings from a two-phase mixed methods study investigating the phenomenological structure of self-relevance among ninth-grade junior high school biology students (Phase 1: N = 118; Phase 2: N = 139). We begin with a phenomenological multidimensional definition of self-relevance as comprising three dimensions: the academic…

Functionally relevant microorganisms to enhanced biological phosphorus removal performance at full-scale wastewater treatment plants in the United States.

Science.gov (United States)

Gu, April Z; Saunders, A; Neethling, J B; Stensel, H D; Blackall, L L

2008-08-01

The abundance and relevance ofAccumulibacter phosphatis (presumed to be polyphosphate-accumulating organisms [PAOs]), Competibacter phosphatis (presumed to be glycogen-accumulating organisms [GAOs]), and tetrad-forming organisms (TFOs) to phosphorus removal performance at six full-scale enhanced biological phosphorus removal (EBPR) wastewater treatment plants were investigated. Coexistence of various levels of candidate PAOs and GAOs were found at these facilities. Accumulibacter were found to be 5 to 20% of the total bacterial population, and Competibacter were 0 to 20% of the total bacteria population. The TFO abundance varied from nondetectable to dominant. Anaerobic phosphorus (P) release to acetate uptake ratios (P(rel)/HAc(up)) obtained from bench tests were correlated positively with the abundance ratio of Accumulibacter/(Competibacter +TFOs) and negatively with the abundance of (Competibacter +TFOs) for all plants except one, suggesting the relevance of these candidate organisms to EBPR processes. However, effluent phosphorus concentration, amount of phosphorus removed, and process stability in an EBPR system were not directly related to high PAO abundance or mutually exclusive with a high GAO fraction. The plant that had the lowest average effluent phosphorus and highest stability rating had the lowest P(rel)/HAc(up) and the most TFOs. Evaluation of full-scale EBPR performance data indicated that low effluent phosphorus concentration and high process stability are positively correlated with the influent readily biodegradable chemical oxygen demand-to-phosphorus ratio. A system-level carbon-distribution-based conceptual model is proposed for capturing the dynamic competition between PAOs and GAOs and their effect on an EBPR process, and the results from this study seem to support the model hypothesis.

The value of DCE-MRI in assessing histopathological and molecular biological features in induced rat epithelial ovarian carcinomas.

Science.gov (United States)

Yuan, Su Juan; Qiao, Tian Kui; Qiang, Jin Wei; Cai, Song Qi; Li, Ruo Kun

2017-09-26

To investigate dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for assessing histopathological and molecular biological features in induced rat epithelial ovarian carcinomas (EOCs). 7,12-dimethylbenz[A]anthracene (DMBA) was applied to induce EOCs in situ in 46 SD rats. Conventional MRI and DCE-MRI were performed to evaluate the morphology and perfusion features of the tumors, including the time-signal intensity curve (TIC), volume transfer constant (K trans ), rate constant (K ep ), extravascular extracellular space volume ratio (V e ) and initial area under the curve (IAUC). DCE-MRI parameters were correlated with histological grade, microvascular density (MVD), vascular endothelial growth factor (VEGF) and fraction of Ki67-positive cells and the serum level of cancer antigen 125 (CA125). Thirty-five of the 46 rats developed EOCs. DCE-MRI showed type III TIC more frequently than type II (29/35 vs. 6/35, p values showed significant differences in different histological grades in overall and pairwise comparisons except for IAUC in grade 2 vs. grade 3 (all p values among the three grade groups (p > 0.05). K trans , K ep and IAUC values were positively correlated with MVD, VEGF and Ki67 expression (all p  0.05). TIC types and perfusion parameters of DCE-MRI can reflect tumor grade, angiogenesis and cell proliferation to some extent, thereby helping treatment planning and predicting prognosis.

A redundancy-removing feature selection algorithm for nominal data

Directory of Open Access Journals (Sweden)

Zhihua Li

2015-10-01

Full Text Available No order correlation or similarity metric exists in nominal data, and there will always be more redundancy in a nominal dataset, which means that an efficient mutual information-based nominal-data feature selection method is relatively difficult to find. In this paper, a nominal-data feature selection method based on mutual information without data transformation, called the redundancy-removing more relevance less redundancy algorithm, is proposed. By forming several new information-related definitions and the corresponding computational methods, the proposed method can compute the information-related amount of nominal data directly. Furthermore, by creating a new evaluation function that considers both the relevance and the redundancy globally, the new feature selection method can evaluate the importance of each nominal-data feature. Although the presented feature selection method takes commonly used MIFS-like forms, it is capable of handling high-dimensional datasets without expensive computations. We perform extensive experimental comparisons of the proposed algorithm and other methods using three benchmarking nominal datasets with two different classifiers. The experimental results demonstrate the average advantage of the presented algorithm over the well-known NMIFS algorithm in terms of the feature selection and classification accuracy, which indicates that the proposed method has a promising performance.

Bacteriophage lambda: early pioneer and still relevant

Science.gov (United States)

Casjens, Sherwood R.; Hendrix, Roger W.

2015-01-01

Molecular genetic research on bacteriophage lambda carried out during its golden age from the mid 1950's to mid 1980's was critically important in the attainment of our current understanding of the sophisticated and complex mechanisms by which the expression of genes is controlled, of DNA virus assembly and of the molecular nature of lysogeny. The development of molecular cloning techniques, ironically instigated largely by phage lambda researchers, allowed many phage workers to switch their efforts to other biological systems. Nonetheless, since that time the ongoing study of lambda and its relatives have continued to give important new insights. In this review we give some relevant early history and describe recent developments in understanding the molecular biology of lambda's life cycle. PMID:25742714

The Features of Female Managers' Personality Traits in Organization

Science.gov (United States)

Gabdreeva, Guzel Sh.; Khalfieva, Alisa R.

2016-01-01

The relevance of the "female" management features study is driven by the active penetration of women to management in various fields and the emergence of a new social category "Business-women". The article contains the results of a study aimed to identify the features of personal properties and structure of low-level,…

Neuro-symbolic representation learning on biological knowledge graphs

KAUST Repository

Alshahrani, Mona

2017-04-21

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge.We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of SemanticWeb based knowledge bases in biology to use in machine learning and data analytics.https://github.com/bio-ontology-research-group/walking-rdf-and-owl.robert.hoehndorf@kaust.edu.sa.Supplementary data are available at Bioinformatics online.

The relevance of segments reports – measurement methodology

Directory of Open Access Journals (Sweden)

Tomasz Zimnicki

2017-09-01

Full Text Available The segment report is one of the areas of financial statements, and it obliges a company to provide infor-mation about the economic situation in each of its activity areas. The article evaluates the change of segment reporting standards from IAS14R to IFRS8 in the context of feature relevance. It presents the construction of a measure which allows the relevance of segment disclosures to be determined. The created measure was used to study periodical reports published by companies listed on the main market of the Warsaw Stock Exchange from three reporting periods – 2008, 2009 and 2013. Based on the re-search results, it was found that the change of segment reporting standards from IAS14R to IFRS8 in the context of relevance was legitimate.

Alkali Metal Ion Complexes with Phosphates, Nucleotides, Amino Acids, and Related Ligands of Biological Relevance. Their Properties in Solution.

Science.gov (United States)

Crea, Francesco; De Stefano, Concetta; Foti, Claudia; Lando, Gabriele; Milea, Demetrio; Sammartano, Silvio

2016-01-01

Alkali metal ions play very important roles in all biological systems, some of them are essential for life. Their concentration depends on several physiological factors and is very variable. For example, sodium concentrations in human fluids vary from quite low (e.g., 8.2 mmol dm(-3) in mature maternal milk) to high values (0.14 mol dm(-3) in blood plasma). While many data on the concentration of Na(+) and K(+) in various fluids are available, the information on other alkali metal cations is scarce. Since many vital functions depend on the network of interactions occurring in various biofluids, this chapter reviews their complex formation with phosphates, nucleotides, amino acids, and related ligands of biological relevance. Literature data on this topic are quite rare if compared to other cations. Generally, the stability of alkali metal ion complexes of organic and inorganic ligands is rather low (usually log K  Na(+) > K(+) > Rb(+) > Cs(+). For example, for citrate it is: log K ML = 0.88, 0.80, 0.48, 0.38, and 0.13 at 25 °C and infinite dilution. Some considerations are made on the main aspects related to the difficulties in the determination of weak complexes. The importance of the alkali metal ion complexes was also studied in the light of modelling natural fluids and in the use of these cations as probes for different processes. Some empirical relationships are proposed for the dependence of the stability constants of Na(+) complexes on the ligand charge, as well as for correlations among log K values of NaL, KL or LiL species (L = generic ligand).

Reflections on rural people's knowledge and skill and relevance in ...

African Journals Online (AJOL)

UNLICENSED

objective is to assess the relevance of indigenous knowledge in agriculture. ... transmit the knowledge to the youths and researchers to document it and government to protect it. ... mechanisms to protect the earth's biological diversity. ... and other development agencies to embrace Agenda 21 as .... ecological characteristics.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

Science.gov (United States)

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

Science.gov (United States)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Visual data mining of biological networks: one size does not fit all.

Directory of Open Access Journals (Sweden)

Chiara Pastrello

Full Text Available High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.

Increasing the biological value of dietary cutlets

OpenAIRE

SYZDYKOVA L.S.; DIKHANBAYEVA F.T.; BAZYLHANOVA E.CH

2015-01-01

Relevance of work: meat products are the main source of the proteins, necessary for activity of the person. In this article is determined the biological value of the cutlets with dietary properties. The purpose of this work is development of the production technology of dietary cutlets in branches of public catering and determination of their biological value. As a result of work dietary cutlets with the increased biological value due to addition of oatmeal are received.

Approaches to chemical synthetic biology.

Science.gov (United States)

Chiarabelli, Cristiano; Stano, Pasquale; Anella, Fabrizio; Carrara, Paolo; Luisi, Pier Luigi

2012-07-16

Synthetic biology is first represented in terms of two complementary aspects, the bio-engineering one, based on the genetic manipulation of extant microbial forms in order to obtain forms of life which do not exist in nature; and the chemical synthetic biology, an approach mostly based on chemical manipulation for the laboratory synthesis of biological structures that do not exist in nature. The paper is mostly devoted to shortly review chemical synthetic biology projects currently carried out in our laboratory. In particular, we describe: the minimal cell project, then the "Never Born Proteins" and lastly the Never Born RNAs. We describe and critically analyze the main results, emphasizing the possible relevance of chemical synthetic biology for the progress in basic science and biotechnology. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Improved identification of primary biological aerosol particles using single-particle mass spectrometry

Directory of Open Access Journals (Sweden)

M. A. Zawadowicz

2017-06-01

Full Text Available Measurements of primary biological aerosol particles (PBAP, especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture using SPMS. We show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodology to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04–2 % of particles in the 200–3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36–56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust–biological mixtures.

Rethinking the central dogma: noncoding RNAs are biologically relevant.

Science.gov (United States)

Robinson, Victoria L

2009-01-01

Non-coding RNAs (ncRNAs) are a large class of functional molecules with over 100 unique classes described to date. ncRNAs are diverse in terms of their function and size. A relatively new class of small ncRNA, called microRNAs (miRNA), have received a great deal of attention in the literature in recent years. miRNAs are endogenously encoded gene families that demonstrate striking evolutionary conservation. miRNAs serve essential and diverse physiological functions such as differentiation and development, proliferation, maintaining cell type phenotypes, and many others. The discovery and ongoing investigation of miRNAs is part of a revolution in biology that is changing the basic concepts of gene expression and RNA functionality. A single miRNA can participate in controlling the expression of up to several hundred protein-coding genes by interacting with mRNAs, generally in 3' untranslated regions. Our new and developing understanding of miRNAs, and other ncRNAs, promises to lead to significant contributions to medicine. Specifically, miRNAs are likely to serve as the basis for novel therapies and diagnostic tools.

Immunolocalisation of members of the polypeptide N-acetylgalactosaminyl transferase (ppGalNAc-T) family is consistent with biologically relevant altered cell surface glycosylation in breast cancer

DEFF Research Database (Denmark)

Brooks, Susan A; Carter, Tracey M; Bennett, Eric P

2007-01-01

understood, may mediate the synthesis of varied glycoforms of cellular proteins with different biological activities. Disruptions in glycosylation are a common feature of cancer and may have functional significance. Immunocytochemistry with confocal scanning laser microscopy was employed to detect members...... of the ppGalNAc-T family, ppGalNAc-T1, -T2, -T3, -T4 and -T6 in a range of breast cell lines. The cells were chosen to represent a range of phenotypes from 'normal'/benign (HMT 3,522), primary, non-metastatic breast cancer (BT 474), to aggressive, metastatic breast cancer (ZR75-1, T47D, MCF-7, DU 4...... tightly restricted ppGalNAc-T's may result in initiation of O-linked glycosylation at normally unoccupied potential glycosylation sites leading to altered glycoforms of proteins with changed biological activity which may contribute to the pathogenesis of cancer....

Interactive Effects of Working Memory Self-Regulatory Ability and Relevance Instructions on Text Processing

Science.gov (United States)

Hamilton, Nancy Jo

2012-01-01

Reading is a process that requires the enactment of many cognitive processes. Each of these processes uses a certain amount of working memory resources, which are severely constrained by biology. More efficiency in the function of working memory may mediate the biological limits of same. Reading relevancy instructions may be one such method to…

Vesicular monoamine transporter protein expression correlates with clinical features, tumor biology, and MIBG avidity in neuroblastoma: a report from the Children's Oncology Group

International Nuclear Information System (INIS)

Temple, William; Mendelsohn, Lori; Nekritz, Erin; Gustafson, W.C.; Matthay, Katherine K.; Kim, Grace E.; Lin, Lawrence; Giacomini, Kathy; Naranjo, Arlene; Van Ryn, Collin; Yanik, Gregory A.; Kreissman, Susan G.; Hogarty, Michael; DuBois, Steven G.

2016-01-01

Vesicular monoamine transporters 1 and 2 (VMAT1 and VMAT2) are thought to mediate MIBG uptake in adult neuroendocrine tumors. In neuroblastoma, the norepinephrine transporter (NET) has been investigated as the principal MIBG uptake protein, though some tumors without NET expression concentrate MIBG. We investigated VMAT expression in neuroblastoma and correlated expression with MIBG uptake and clinical features. We evaluated VMAT1 and VMAT2 expression by immunohistochemistry (IHC) in neuroblastoma tumors from 76 patients with high-risk metastatic disease treated in a uniform cooperative group trial (COG A3973). All patients had baseline MIBG diagnostic scans centrally reviewed. IHC results were scored as the product of intensity grading (0 - 3+) and percent of tumor cells expressing the protein of interest. The association between VMAT1 and VMAT2 scores and clinical and biological features was tested using Wilcoxon rank-sum tests. Patient characteristics were typical of high-risk neuroblastoma, though the cohort was intentionally enriched in patients with MIBG-nonavid tumors (n = 20). VMAT1 and VMAT2 were expressed in 62 % and 75 % of neuroblastoma tumors, respectively. VMAT1 and VMAT2 scores were both significantly lower in MYCN amplified tumors and in tumors with high mitotic karyorrhectic index. MIBG-avid tumors had significantly higher VMAT2 scores than MIBG-nonavid tumors (median 216 vs. 45; p = 0.04). VMAT1 expression did not correlate with MIBG avidity. VMAT1 and VMAT2 are expressed in the majority of neuroblastomas. Expression correlates with other biological features. The expression level of VMAT2 but not that of VMAT1 correlates with avidity for MIBG. (orig.)

Vesicular monoamine transporter protein expression correlates with clinical features, tumor biology, and MIBG avidity in neuroblastoma: a report from the Children's Oncology Group

Energy Technology Data Exchange (ETDEWEB)

Temple, William; Mendelsohn, Lori; Nekritz, Erin; Gustafson, W.C.; Matthay, Katherine K. [UCSF School of Medicine, Department of Pediatrics, San Francisco, CA (United States); UCSF Benioff Children' s Hospital, San Francisco, CA (United States); Kim, Grace E. [UCSF School of Medicine, Department of Pathology, San Francisco, CA (United States); Lin, Lawrence; Giacomini, Kathy [UCSF School of Pharmacy, Department of Bioengineering and Therapeutic Sciences, San Francisco, CA (United States); Naranjo, Arlene; Van Ryn, Collin [University of Florida, Children' s Oncology Group Statistics and Data Center, Gainesville, FL (United States); Yanik, Gregory A. [University of Michigan, CS Mott Children' s Hospital, Ann Arbor, MI (United States); Kreissman, Susan G. [Duke University Medical Center, Durham, NC (United States); Hogarty, Michael [University of Pennsylvania, Children' s Hospital of Philadelphia and Perelman School of Medicine, Philadelphia, PA (United States); DuBois, Steven G. [UCSF School of Medicine, Department of Pediatrics, San Francisco, CA (United States); UCSF Benioff Children' s Hospital, San Francisco, CA (United States); UCSF School of Medicine, San Francisco, CA (United States)

2016-03-15

Vesicular monoamine transporters 1 and 2 (VMAT1 and VMAT2) are thought to mediate MIBG uptake in adult neuroendocrine tumors. In neuroblastoma, the norepinephrine transporter (NET) has been investigated as the principal MIBG uptake protein, though some tumors without NET expression concentrate MIBG. We investigated VMAT expression in neuroblastoma and correlated expression with MIBG uptake and clinical features. We evaluated VMAT1 and VMAT2 expression by immunohistochemistry (IHC) in neuroblastoma tumors from 76 patients with high-risk metastatic disease treated in a uniform cooperative group trial (COG A3973). All patients had baseline MIBG diagnostic scans centrally reviewed. IHC results were scored as the product of intensity grading (0 - 3+) and percent of tumor cells expressing the protein of interest. The association between VMAT1 and VMAT2 scores and clinical and biological features was tested using Wilcoxon rank-sum tests. Patient characteristics were typical of high-risk neuroblastoma, though the cohort was intentionally enriched in patients with MIBG-nonavid tumors (n = 20). VMAT1 and VMAT2 were expressed in 62 % and 75 % of neuroblastoma tumors, respectively. VMAT1 and VMAT2 scores were both significantly lower in MYCN amplified tumors and in tumors with high mitotic karyorrhectic index. MIBG-avid tumors had significantly higher VMAT2 scores than MIBG-nonavid tumors (median 216 vs. 45; p = 0.04). VMAT1 expression did not correlate with MIBG avidity. VMAT1 and VMAT2 are expressed in the majority of neuroblastomas. Expression correlates with other biological features. The expression level of VMAT2 but not that of VMAT1 correlates with avidity for MIBG. (orig.)

Neutron Scattering in Biology Techniques and Applications

CERN Document Server

Fitter, Jörg; Katsaras, John

2006-01-01

The advent of new neutron facilities and the improvement of existing sources and instruments world wide supply the biological community with many new opportunities in the areas of structural biology and biological physics. The present volume offers a clear description of the various neutron-scattering techniques currently being used to answer biologically relevant questions. Their utility is illustrated through examples by some of the leading researchers in the field of neutron scattering. This volume will be a reference for researchers and a step-by-step guide for young scientists entering the field and the advanced graduate student.

Feature-specific encoding flexibility in visual working memory.

Directory of Open Access Journals (Sweden)

Aki Kondo

Full Text Available The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location, and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape can be flexibly added to object representations.

Feature-specific encoding flexibility in visual working memory.

Science.gov (United States)

Kondo, Aki; Saiki, Jun

2012-01-01

The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location), and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape) can be flexibly added to object representations.

Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics.

Science.gov (United States)

Lin, Xiaohui; Li, Chao; Zhang, Yanhui; Su, Benzhe; Fan, Meng; Wei, Hai

2017-12-26

Feature selection is an important topic in bioinformatics. Defining informative features from complex high dimensional biological data is critical in disease study, drug development, etc. Support vector machine-recursive feature elimination (SVM-RFE) is an efficient feature selection technique that has shown its power in many applications. It ranks the features according to the recursive feature deletion sequence based on SVM. In this study, we propose a method, SVM-RFE-OA, which combines the classification accuracy rate and the average overlapping ratio of the samples to determine the number of features to be selected from the feature rank of SVM-RFE. Meanwhile, to measure the feature weights more accurately, we propose a modified SVM-RFE-OA (M-SVM-RFE-OA) algorithm that temporally screens out the samples lying in a heavy overlapping area in each iteration. The experiments on the eight public biological datasets show that the discriminative ability of the feature subset could be measured more accurately by combining the classification accuracy rate with the average overlapping degree of the samples compared with using the classification accuracy rate alone, and shielding the samples in the overlapping area made the calculation of the feature weights more stable and accurate. The methods proposed in this study can also be used with other RFE techniques to define potential biomarkers from big biological data.

Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics

Directory of Open Access Journals (Sweden)

Xiaohui Lin

2017-12-01

Full Text Available Feature selection is an important topic in bioinformatics. Defining informative features from complex high dimensional biological data is critical in disease study, drug development, etc. Support vector machine-recursive feature elimination (SVM-RFE is an efficient feature selection technique that has shown its power in many applications. It ranks the features according to the recursive feature deletion sequence based on SVM. In this study, we propose a method, SVM-RFE-OA, which combines the classification accuracy rate and the average overlapping ratio of the samples to determine the number of features to be selected from the feature rank of SVM-RFE. Meanwhile, to measure the feature weights more accurately, we propose a modified SVM-RFE-OA (M-SVM-RFE-OA algorithm that temporally screens out the samples lying in a heavy overlapping area in each iteration. The experiments on the eight public biological datasets show that the discriminative ability of the feature subset could be measured more accurately by combining the classification accuracy rate with the average overlapping degree of the samples compared with using the classification accuracy rate alone, and shielding the samples in the overlapping area made the calculation of the feature weights more stable and accurate. The methods proposed in this study can also be used with other RFE techniques to define potential biomarkers from big biological data.

Morphological and biological features of seedlings of some Trifolium species

Directory of Open Access Journals (Sweden)

Valentina A. Kalinkina

2013-04-01

Full Text Available The author conducted morphological and biological characteristics of seedlings of six species belonging to three sections: Lupinaster(T. lupinasterL, T. pacificumBobr, T. eximium Steph. Ex. DC., Chronosemium(T. campestre Schreb. and Trifolium (T. arvenseL., T. pratense L. of the genus Trifolium. Dimensional and qualitative morphological characteristics of the main structural elements of the seedlings of these species are represented in the article.

Impact of e-AV Biology Website for Learning about Renewable Energy

Science.gov (United States)

Nugraini, Siti Hadiati; Choo, Koo Ah; Hin, Hew Soon; Hoon, Teoh Sian

2013-01-01

This paper considers the design and development of a Website for Biology in senior high schools in Indonesia. The teaching media, namely e-AV Biology, was developed with the main features of video lessons and other features in supporting the students' learning process. Some video lessons describe the production process of Biofuel or Renewable…

Structure Biology of Membrane Bound Enzymes

Energy Technology Data Exchange (ETDEWEB)

Fu, Dax [Johns Hopkins Univ., Baltimore, MD (United States). School of Medicine. Dept. of Physiology

2016-11-30

The overall goal of the proposed research is to understand the membrane-associated active processes catalyzed by an alkane $\\square$-hydroxylase (AlkB) from eubacterium Pseudomonase oleovorans. AlkB performs oxygenation of unactivated hydrocarbons found in crude oils. The enzymatic reaction involves energy-demanding steps in the membrane with the uses of structurally unknown metal active sites featuring a diiron [FeFe] center. At present, a critical barrier to understanding the membrane-associated reaction mechanism is the lack of structural information. The structural biology efforts have been challenged by technical difficulties commonly encountered in crystallization and structural determination of membrane proteins. The specific aims of the current budget cycle are to crystalize AlkB and initiate X-ray analysis to set the stage for structural determination. The long-term goals of our structural biology efforts are to provide an atomic description of AlkB structure, and to uncover the mechanisms of selective modification of hydrocarbons. The structural information will help elucidating how the unactivated C-H bonds of saturated hydrocarbons are oxidized to initiate biodegradation and biotransformation processes. The knowledge gained will be fundamental to biotechnological applications to biofuel transformation of non-edible oil feedstock. Renewable biodiesel is a promising energy carry that can be used to reduce fossil fuel dependency. The proposed research capitalizes on prior BES-supported efforts on over-expression and purification of AlkB to explore the inner workings of a bioenergy-relevant membrane-bound enzyme.

Intertwining personal and reward relevance: evidence from the drift-diffusion model.

Science.gov (United States)

Yankouskaya, A; Bührle, R; Lugt, E; Stolte, M; Sui, J

2018-01-24

In their seminal paper 'Is our self nothing but reward', Northoff and Hayes (Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) proposed three models of the relationship between self and reward and opened a continuing debate about how these different fields can be linked. To date, none of the proposed models received strong empirical support. The present study tested common and distinct effects of personal relevance and reward values by de-componenting different stages of perceptual decision making using a drift-diffusion approach. We employed a recently developed associative matching paradigm where participants (N = 40) formed mental associations between five geometric shapes and five labels referring personal relevance in the personal task, or five shape-label pairings with different reward values in the reward task and then performed a matching task by indicating whether a displayed shape-label pairing was correct or incorrect. We found that common effects of personal relevance and monetary reward were manifested in the facilitation of behavioural performance for high personal relevance and high reward value as socially important signals. The differential effects between personal and monetary relevance reflected non-decisional time in a perceptual decision process, and task-specific prioritization of stimuli. Our findings support the parallel processing model (Northoff & Hayes, Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) and suggest that self-specific processing occurs in parallel with high reward processing. Limitations and further directions are discussed.

Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance* | Office of Cancer Genomics

Science.gov (United States)

The Cancer Target Discovery and Development (CTD^2) Network was established to accelerate the transformation of "Big Data" into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding.

Neuro-symbolic representation learning on biological knowledge graphs.

Science.gov (United States)

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Inorganic concepts relevant to metal binding, activity, and toxicity in a biological system

Energy Technology Data Exchange (ETDEWEB)

Hoeschele, J.D. (Warner-Lambert Co., Ann Arbor, MI (USA). Parke-Davis Pharmaceutical Research Div.); Turner, J.E.; England, M.W. (Oak Ridge National Lab., TN (USA))

1990-01-01

The purpose of this paper is to review selected physical and inorganic concepts and factors which might be important in assessing and/or understanding the fact and disposition of a metal system in a biological environment. Hopefully, such inquiries will ultimately permit us to understand, rationalize, and predict differences and trends in biological effects as a function of the basic nature of a metal system and, in optimal cases, serve as input to a system of guidelines for the notion of Chemical Dosimetry.'' The plan of this paper is to first review, in general terms, the basic principles of the Crystal Field Theory (CFT), a unifying theory of bonding in metal complexes. This will provide the necessary theoretical background for the subsequent discussion of selected concepts and factors. 21 refs., 7 figs., 6 tabs.

Biology, Bionomics and Molecular Biology of Anopheles sinensis Wiedemann 1828 (Diptera: Culicidae), Main Malaria Vector in China.

Science.gov (United States)

Feng, Xinyu; Zhang, Shaosen; Huang, Fang; Zhang, Li; Feng, Jun; Xia, Zhigui; Zhou, Hejun; Hu, Wei; Zhou, Shuisen

2017-01-01

China has set a goal to eliminate all malaria in the country by 2020, but it is unclear if current understanding of malaria vectors and transmission is sufficient to achieve this objective. Anopheles sinensis is the most widespread malaria vector specie in China, which is also responsible for vivax malaria outbreak in central China. We reviewed literature from 1954 to 2016 on An. sinensis with emphasis on biology, bionomics, and molecular biology. A total of 538 references were relevant and included. An. sienesis occurs in 29 Chinese provinces. Temperature can affect most life-history parameters. Most An. sinensis are zoophilic, but sometimes they are facultatively anthropophilic. Sporozoite analysis demonstrated An. sinensis efficacy on Plasmodium vivax transmission. An. sinensis was not stringently refractory to P. falciparum under experimental conditions, however, sporozoite was not found in salivary glands of field collected An. sinensis . The literature on An. sienesis biology and bionomics was abundant, but molecular studies, such as gene functions and mechanisms, were limited. Only 12 molecules (genes, proteins or enzymes) have been studied. In addition, there were considerable untapped omics resources for potential vector control tools. Existing information on An. sienesis could serve as a baseline for advanced research on biology, bionomics and genetics relevant to vector control strategies.

Biological radiolesions and repair

International Nuclear Information System (INIS)

Laskowski, W.

1981-01-01

In 7 chapters, the book answers the following questions: 1) What reactions are induced in biological matter by absorption of radiation energy. 2) In what parts of the cell do the radiation-induced reactions with detectable biological effects occur. 3) In which way are these cell components changed by different qualities of radiation. 4) What are the cell mechanisms by which radiation-induced changes can be repaired. 5) What is the importance of these repair processes for man, his life and evolution. At the end of each chapter, there is a bibliography of relevant publications in this field. (orig./MG) [de

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

[How to be prudent with synthetic biology. Synthetic Biology and the precautionary principle].

Science.gov (United States)

Rodríguez López, Blanca

2014-01-01

Synthetic biology is a new discipline that is twofold: firstly it offers the promise to pay benefits that can alleviate some of the ills that plague mankind; On the other hand, like all technologies, holds risks. Given these, the most critical and concerned about the risks, invoke the application of the precautionary principle, common in cases where an activity or new technology creates risks to the environment and/or human health, but far from universally accepted happens to be currently one of the most controversial principles. In this paper the question of the risks and benefits of synthetic biology and the relevance of applying the precautionary principle are analyzed. To do this we proceed as follows. The first part focuses on synthetic biology. At first, this discipline is characterized, with special attention to what is novel compared to the known as "genetic engineering". In the second stage both the benefits and the risks associated with it are discussed. The first part concludes with a review of the efforts currently being made to control or minimize the risks. The second part aims to analyze the precautionary principle and its possible relevance to the case of Synthetic Biology. At first, the different versions and interpretations of the principle and the various criticisms of which has been the subject are reviewed. Finally, after discarding the Precautionary Principle as an useful tool, it is seen as more appropriate some recent proposals to treat technologies that take into account not only risks but also their benefits.

Prediction of interface residue based on the features of residue interaction network.

Science.gov (United States)

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular Imaging in Synthetic Biology, and Synthetic Biology in Molecular Imaging.

Science.gov (United States)

Gilad, Assaf A; Shapiro, Mikhail G

2017-06-01

Biomedical synthetic biology is an emerging field in which cells are engineered at the genetic level to carry out novel functions with relevance to biomedical and industrial applications. This approach promises new treatments, imaging tools, and diagnostics for diseases ranging from gastrointestinal inflammatory syndromes to cancer, diabetes, and neurodegeneration. As these cellular technologies undergo pre-clinical and clinical development, it is becoming essential to monitor their location and function in vivo, necessitating appropriate molecular imaging strategies, and therefore, we have created an interest group within the World Molecular Imaging Society focusing on synthetic biology and reporter gene technologies. Here, we highlight recent advances in biomedical synthetic biology, including bacterial therapy, immunotherapy, and regenerative medicine. We then discuss emerging molecular imaging approaches to facilitate in vivo applications, focusing on reporter genes for noninvasive modalities such as magnetic resonance, ultrasound, photoacoustic imaging, bioluminescence, and radionuclear imaging. Because reporter genes can be incorporated directly into engineered genetic circuits, they are particularly well suited to imaging synthetic biological constructs, and developing them provides opportunities for creative molecular and genetic engineering.

DYNAMIC FEATURE SELECTION FOR WEB USER IDENTIFICATION ON LINGUISTIC AND STYLISTIC FEATURES OF ONLINE TEXTS

Directory of Open Access Journals (Sweden)

A. A. Vorobeva

2017-01-01

Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

Science.gov (United States)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Designing attractive gamification features for collaborative storytelling websites.

Science.gov (United States)

Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

2013-06-01

Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

Optical sensors and their applications for probing biological systems

DEFF Research Database (Denmark)

Palanco, Marta Espina

There is a great interest in exploring and developing new optical sensitive methodologies for probing complex biological systems. In this project we developed non-invasive and sensitive biosensor strategies for studying physiologically relevant chemical and physical properties of plant and mammal......There is a great interest in exploring and developing new optical sensitive methodologies for probing complex biological systems. In this project we developed non-invasive and sensitive biosensor strategies for studying physiologically relevant chemical and physical properties of plant...... of a trapped cell. The project could provide new insights into the desired biosensor for future membrane-protein cell studies....

Stimulus-response correspondence effect as a function of temporal overlap between relevant and irrelevant information processing.

Science.gov (United States)

Wang, Dong-Yuan Debbie; Richard, F Dan; Ray, Brittany

2016-01-01

The stimulus-response correspondence (SRC) effect refers to advantages in performance when stimulus and response correspond in dimensions or features, even if the common features are irrelevant to the task. Previous research indicated that the SRC effect depends on the temporal course of stimulus information processing. The current study investigated how the temporal overlap between relevant and irrelevant stimulus processing influences the SRC effect. In this experiment, the irrelevant stimulus (a previously associated tone) preceded the relevant stimulus (a coloured rectangle). The irrelevant and relevant stimuli onset asynchrony was varied to manipulate the temporal overlap between the irrelevant and relevant stimuli processing. Results indicated that the SRC effect size varied as a quadratic function of the temporal overlap between the relevant stimulus and irrelevant stimulus. This finding extends previous experimental observations that the SRC effect size varies in an increasing or decreasing function with reaction time. The current study demonstrated a quadratic function between effect size and the temporal overlap.

Why relevance theory is relevant for lexicography

DEFF Research Database (Denmark)

Bothma, Theo; Tarp, Sven

2014-01-01

This article starts by providing a brief summary of relevance theory in information science in relation to the function theory of lexicography, explaining the different types of relevance, viz. objective system relevance and the subjective types of relevance, i.e. topical, cognitive, situational...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...

Using synthetic biology to make cells tomorrow's test tubes.

Science.gov (United States)

Garcia, Hernan G; Brewster, Robert C; Phillips, Rob

2016-04-18

The main tenet of physical biology is that biological phenomena can be subject to the same quantitative and predictive understanding that physics has afforded in the context of inanimate matter. However, the inherent complexity of many of these biological processes often leads to the derivation of complex theoretical descriptions containing a plethora of unknown parameters. Such complex descriptions pose a conceptual challenge to the establishment of a solid basis for predictive biology. In this article, we present various exciting examples of how synthetic biology can be used to simplify biological systems and distill these phenomena down to their essential features as a means to enable their theoretical description. Here, synthetic biology goes beyond previous efforts to engineer nature and becomes a tool to bend nature to understand it. We discuss various recent and classic experiments featuring applications of this synthetic approach to the elucidation of problems ranging from bacteriophage infection, to transcriptional regulation in bacteria and in developing embryos, to evolution. In all of these examples, synthetic biology provides the opportunity to turn cells into the equivalent of a test tube, where biological phenomena can be reconstituted and our theoretical understanding put to test with the same ease that these same phenomena can be studied in the in vitro setting.

Predicting Subtype Selectivity for Adenosine Receptor Ligands with Three-Dimensional Biologically Relevant Spectrum (BRS-3D)

Science.gov (United States)

He, Song-Bing; Ben Hu; Kuang, Zheng-Kun; Wang, Dong; Kong, De-Xin

2016-11-01

Adenosine receptors (ARs) are potential therapeutic targets for Parkinson’s disease, diabetes, pain, stroke and cancers. Prediction of subtype selectivity is therefore important from both therapeutic and mechanistic perspectives. In this paper, we introduced a shape similarity profile as molecular descriptor, namely three-dimensional biologically relevant spectrum (BRS-3D), for AR selectivity prediction. Pairwise regression and discrimination models were built with the support vector machine methods. The average determination coefficient (r2) of the regression models was 0.664 (for test sets). The 2B-3 (A2B vs A3) model performed best with q2 = 0.769 for training sets (10-fold cross-validation), and r2 = 0.766, RMSE = 0.828 for test sets. The models’ robustness and stability were validated with 100 times resampling and 500 times Y-randomization. We compared the performance of BRS-3D with 3D descriptors calculated by MOE. BRS-3D performed as good as, or better than, MOE 3D descriptors. The performances of the discrimination models were also encouraging, with average accuracy (ACC) 0.912 and MCC 0.792 (test set). The 2A-3 (A2A vs A3) selectivity discrimination model (ACC = 0.882 and MCC = 0.715 for test set) outperformed an earlier reported one (ACC = 0.784). These results demonstrated that, through multiple conformation encoding, BRS-3D can be used as an effective molecular descriptor for AR subtype selectivity prediction.

Realistic biological approaches for improving thermoradiotherapy

DEFF Research Database (Denmark)

Horsman, Michael R

2016-01-01

There is now definitive clinical evidence that hyperthermia can successfully improve the response of certain human tumour types to radiation therapy, but, there is still the need for improvement. From a biological standpoint this can be achieved by either targeting the cellular or vascular...... or radiation in preclinical models and clear benefits in tumour response observed. But few of these methods have actually been combined with thermoradiotherapy. Furthermore, very few combinations have been tested in relevant normal tissue studies, despite the fact that it is the normal tissue response...... that controls the maximal heat or radiation treatment that can be applied. Here we review the most clinically relevant biological approaches that have been shown to enhance thermoradiotherapy, or have the potential to be applied in this context, and suggest how these should be moved forward into the clinic....

The Comparative Diagnostic Features of Canine and Human Lymphoma

Directory of Open Access Journals (Sweden)

Davis M. Seelig

2016-06-01

Full Text Available The non-Hodgkin lymphomas (NHLs are a heterogeneous family of lymphoid malignancies that are among the most common neoplasms of both dogs and humans. Owing to shared molecular, signaling, incidence, and pathologic features, there is a strong framework supporting the utilization of canine lymphoma as a comparative, large animal model of human NHL. In alignment with the biologic similarities, the current approach towards the diagnosis and classification of canine lymphoma is based upon the human World Health Organization guidelines. While this approach has contributed to an increasing appreciation of the potential biological scope of canine lymphoma, it has also become apparent that the most appropriate diagnostic philosophy must be multimodal, namely by requiring knowledge of microscopic, immunophenotypic, and clinical features before establishing a final disease diagnosis. This review seeks to illustrate the comparative similarities and differences in the diagnosis of canine lymphoma through the presentation of the microscopic and immunophenotypic features of its most common forms.

The Comparative Diagnostic Features of Canine and Human Lymphoma.

Science.gov (United States)

Seelig, Davis M; Avery, Anne C; Ehrhart, E J; Linden, Michael A

2016-06-01

The non-Hodgkin lymphomas (NHLs) are a heterogeneous family of lymphoid malignancies that are among the most common neoplasms of both dogs and humans. Owing to shared molecular, signaling, incidence, and pathologic features, there is a strong framework supporting the utilization of canine lymphoma as a comparative, large animal model of human NHL. In alignment with the biologic similarities, the current approach towards the diagnosis and classification of canine lymphoma is based upon the human World Health Organization guidelines. While this approach has contributed to an increasing appreciation of the potential biological scope of canine lymphoma, it has also become apparent that the most appropriate diagnostic philosophy must be multimodal, namely by requiring knowledge of microscopic, immunophenotypic, and clinical features before establishing a final disease diagnosis. This review seeks to illustrate the comparative similarities and differences in the diagnosis of canine lymphoma through the presentation of the microscopic and immunophenotypic features of its most common forms.

Synthetic Biology and Personalized Medicine

Science.gov (United States)

Jain, K.K.

2013-01-01

Synthetic biology, application of synthetic chemistry to biology, is a broad term that covers the engineering of biological systems with structures and functions not found in nature to process information, manipulate chemicals, produce energy, maintain cell environment and enhance human health. Synthetic biology devices contribute not only to improve our understanding of disease mechanisms, but also provide novel diagnostic tools. Methods based on synthetic biology enable the design of novel strategies for the treatment of cancer, immune diseases metabolic disorders and infectious diseases as well as the production of cheap drugs. The potential of synthetic genome, using an expanded genetic code that is designed for specific drug synthesis as well as delivery and activation of the drug in vivo by a pathological signal, was already pointed out during a lecture delivered at Kuwait University in 2005. Of two approaches to synthetic biology, top-down and bottom-up, the latter is more relevant to the development of personalized medicines as it provides more flexibility in constructing a partially synthetic cell from basic building blocks for a desired task. PMID:22907209

Biological effects of particle radiation

International Nuclear Information System (INIS)

Sakamoto, Kiyohiko

1988-01-01

Conventional radiations such as photons, gamma rays or electrons show several physical or biological disadvantages to bring tumors to cure, therefore, more and more attentions is being paid to new modalitie such as fast neutrons, protons, negative pions and heavy ions, which are expected to overcome some of the defects of the conventional radiations. Except for fast neutrons, these particle radiations show excellet physical dose localization in tissue, moreover, in terms of biological effects, they demonstrate several features compared to conventional radiations, namely low oxygen enhancement ratio, high value of relative biological effectiveness, smaller cellular recovery, larger therapeutic gain factor and less cell cycle dependency in radiation sensitivity. In present paper the biological effects of particle radiations are shown comparing to the effects of conventional radiations. (author)

Features generated for computational splice-site prediction correspond to functional elements

Directory of Open Access Journals (Sweden)

Wilbur W John

2007-10-01

Full Text Available Abstract Background Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals. Results We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract and auxiliary signals (including GGG triplets and exon splicing enhancers. We present evidence that features identified by FGA include splicing signals not found by other methods. Conclusion Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.

Component Composition Using Feature Models

DEFF Research Database (Denmark)

Eichberg, Michael; Klose, Karl; Mitschke, Ralf

2010-01-01

interface description languages. If this variability is relevant when selecting a matching component then human interaction is required to decide which components can be bound. We propose to use feature models for making this variability explicit and (re-)enabling automatic component binding. In our...... approach, feature models are one part of service specifications. This enables to declaratively specify which service variant is provided by a component. By referring to a service's variation points, a component that requires a specific service can list the requirements on the desired variant. Using...... these specifications, a component environment can then determine if a binding of the components exists that satisfies all requirements. The prototypical environment Columbus demonstrates the feasibility of the approach....

Fluid models and simulations of biological cell phenomena

Science.gov (United States)

Greenspan, H. P.

1982-01-01

The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

BioModels Database: a repository of mathematical models of biological processes.

Science.gov (United States)

Chelliah, Vijayalakshmi; Laibe, Camille; Le Novère, Nicolas

2013-01-01

BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

Solid-supported synthesis: From pharmacologically relevant heterocycles to biologically active surfaces

DEFF Research Database (Denmark)

Komnatnyy, Vitaly V.

for solid-phase synthesis, methods for on - and off-bead screening of combinatorial libraries and their applic ation to various biological targets. The first part of the thesis is dedicated to the development of methodology for the synthesis of structurally diverse heterocyclic scaffolds via N...... methods for the controlled organo-functionalization of titanium, one of the most prominent materials in medicinal device industry, have been suggested . Initial acidic and oxidative treatment s of the metal surface genera te reactive hydroxyl moieties , which are subsequently modified with synthetically...... versatile amine -containing reagents. Subsequent applications in antimicrobial peptide synthesis, metal -catalysis, release from the surface, and polymer grafti ng, are also presented....

Identification of protein features encoded by alternative exons using Exon Ontology.

Science.gov (United States)

Tranchevent, Léon-Charles; Aubé, Fabien; Dulaurier, Louis; Benoit-Pilven, Clara; Rey, Amandine; Poret, Arnaud; Chautard, Emilie; Mortada, Hussein; Desmet, François-Olivier; Chakrama, Fatima Zahra; Moreno-Garcia, Maira Alejandra; Goillot, Evelyne; Janczarski, Stéphane; Mortreux, Franck; Bourgeois, Cyril F; Auboeuf, Didier

2017-06-01

Transcriptomic genome-wide analyses demonstrate massive variation of alternative splicing in many physiological and pathological situations. One major challenge is now to establish the biological contribution of alternative splicing variation in physiological- or pathological-associated cellular phenotypes. Toward this end, we developed a computational approach, named "Exon Ontology," based on terms corresponding to well-characterized protein features organized in an ontology tree. Exon Ontology is conceptually similar to Gene Ontology-based approaches but focuses on exon-encoded protein features instead of gene level functional annotations. Exon Ontology describes the protein features encoded by a selected list of exons and looks for potential Exon Ontology term enrichment. By applying this strategy to exons that are differentially spliced between epithelial and mesenchymal cells and after extensive experimental validation, we demonstrate that Exon Ontology provides support to discover specific protein features regulated by alternative splicing. We also show that Exon Ontology helps to unravel biological processes that depend on suites of coregulated alternative exons, as we uncovered a role of epithelial cell-enriched splicing factors in the AKT signaling pathway and of mesenchymal cell-enriched splicing factors in driving splicing events impacting on autophagy. Freely available on the web, Exon Ontology is the first computational resource that allows getting a quick insight into the protein features encoded by alternative exons and investigating whether coregulated exons contain the same biological information. © 2017 Tranchevent et al.; Published by Cold Spring Harbor Laboratory Press.

Bone biology and physiology: Part I. The fundamentals.

Science.gov (United States)

Buck, Donald W; Dumanian, Gregory A

2012-06-01

The principles of bone biology and physiology permeate all subspecialty practices in plastic and reconstructive surgery from hand surgery to aesthetic surgery. Despite its importance in our practices, the biology of bone healing and bone physiology rarely surfaces within textbooks, literature reviews, or residency curricula. In this article, the authors present the first of a two-part series reviewing the important concepts of bone biology and bone physiology relevant to plastic surgery in an effort to ameliorate this educational gap.

Biological Evidence Management for DNA Analysis in Cases of Sexual Assault

Science.gov (United States)

Magalhães, Teresa; Dinis-Oliveira, Ricardo Jorge; Silva, Benedita; Corte-Real, Francisco; Nuno Vieira, Duarte

2015-01-01

Biological evidence with forensic interest may be found in several cases of assault, being particularly relevant if sexually related. Sexual assault cases are characterized by low rates of disclosure, reporting, prosecution, and conviction. Biological evidence is sometimes the only way to prove the occurrence of sexual contact and to identify the perpetrator. The major focus of this review is to propose practical approaches and guidelines to help health, forensic, and law enforcement professionals to deal with biological evidence for DNA analysis. Attention should be devoted to avoiding contamination, degradation, and loss of biological evidence, as well as respecting specific measures to properly handle evidence (i.e., selection, collection, packing, sealing, labeling, storage, preservation, transport, and guarantee of the chain custody). Biological evidence must be carefully managed since the relevance of any finding in Forensic Genetics is determined, in the first instance, by the integrity and quantity of the samples submitted for analysis. PMID:26587562

Biological Evidence Management for DNA Analysis in Cases of Sexual Assault

Directory of Open Access Journals (Sweden)

Teresa Magalhães

2015-01-01

Full Text Available Biological evidence with forensic interest may be found in several cases of assault, being particularly relevant if sexually related. Sexual assault cases are characterized by low rates of disclosure, reporting, prosecution, and conviction. Biological evidence is sometimes the only way to prove the occurrence of sexual contact and to identify the perpetrator. The major focus of this review is to propose practical approaches and guidelines to help health, forensic, and law enforcement professionals to deal with biological evidence for DNA analysis. Attention should be devoted to avoiding contamination, degradation, and loss of biological evidence, as well as respecting specific measures to properly handle evidence (i.e., selection, collection, packing, sealing, labeling, storage, preservation, transport, and guarantee of the chain custody. Biological evidence must be carefully managed since the relevance of any finding in Forensic Genetics is determined, in the first instance, by the integrity and quantity of the samples submitted for analysis.

The effect of graphene oxide on surface features, biological performance and bio-stability of calcium phosphate coating applied by pulse electrochemical deposition

Science.gov (United States)

Fathyunes, Leila; Khalil-Allafi, Jafar

2018-04-01

In the current study, the effect of second phase of graphene oxide (GO) on the surface features and biological behavior of calcium phosphate (CaP) coating was evaluated. To do so, the GO-CaP composite coating was applied on TiO2 nanotubular arrays using pulse electrochemical deposition. The SEM and AFM images showed that, the CaP-based coating with uniform and refined microstructure could be formed through its compositing with GO sheets. The biological assessment of the coatings was also conducted by cell culture test and MTT assay. Based on findings, the GO-CaP coating showed the better biocompatibility compared to the CaP coating. This could be owing to the fact that the composite coating provided the lower roughness, moderately wettable surface with a contact angle of 23.5° ± 2.6° and the higher stability in the biological environments because of being involved with only the stable phase of CHA. However, in the CaP coating, spreading of cells could be limited by the plate-like crystals with larger size. The higher solubility of the CaP coating in the cell culture medium possibly owing to the existence of some metastable CaP phases like OCP in addition to the dominant phase of CHA in this coating could be another reason for its less biocompatibility. At last, the CaP coating showed the higher apatite-forming ability in SBF solution after its compositing with GO.

Molecular biology of the cell

CERN Document Server

Alberts, Bruce; Lewis, Julian

2000-01-01

Molecular Biology of the Cell is the classic in-dept text reference in cell biology. By extracting the fundamental concepts from this enormous and ever-growing field, the authors tell the story of cell biology, and create a coherent framework through which non-expert readers may approach the subject. Written in clear and concise language, and beautifully illustrated, the book is enjoyable to read, and it provides a clear sense of the excitement of modern biology. Molecular Biology of the Cell sets forth the current understanding of cell biology (completely updated as of Autumn 2001), and it explores the intriguing implications and possibilities of the great deal that remains unknown. The hallmark features of previous editions continue in the Fourth Edition. The book is designed with a clean and open, single-column layout. The art program maintains a completely consistent format and style, and includes over 1,600 photographs, electron micrographs, and original drawings by the authors. Clear and concise concept...

S-Nitrosothiol measurements in biological systems⋄

Science.gov (United States)

Gow, Andrew; Doctor, Allan; Mannick, Joan; Gaston, Benjamin

2007-01-01

S-Nitrosothiol (SNO) cysteine modifications are regulated signaling reactions that dramatically affect, and are affected by, protein conformation. The lability of the S-NO bond can make SNO-modified proteins cumbersome to measure accurately. Here, we review methodologies for detecting SNO modifications in biology. There are three caveats. 1) Many assays for biological SNOs are used near the limit of detection: standard curves must be in the biologically relevant concentration range. 2) The assays that are most reliable are those that modify SNO protein or peptide chemistry the least. 3) Each result should be quantitatively validated using more than one assay. Improved assays are needed and are in development. PMID:17379583

Review of biological monitoring programs at nuclear facilities

International Nuclear Information System (INIS)

Quintana, L.R.; Oakes, T.W.; Shank, K.E.

Biological monitoring programs, as well as relevant radioecological research studies, are reviewed at specific Department of Energy facilities; the program at Oak Ridge National Laboratory is discussed in detail. The biological measurements that are being used for interpreting the impact of a facility on its surrounding environment and nearby population are given. Suggestions which could facilitate interlaboratory comparison studies are presented

Cytosine methylation is a conserved epigenetic feature found throughout the phylum Platyhelminthes

Science.gov (United States)

2013-01-01

Background The phylum Platyhelminthes (flatworms) contains an important group of bilaterian organisms responsible for many debilitating and chronic infectious diseases of human and animal populations inhabiting the planet today. In addition to their biomedical and veterinary relevance, some platyhelminths are also frequently used models for understanding tissue regeneration and stem cell biology. Therefore, the molecular (genetic and epigenetic) characteristics that underlie trophic specialism, pathogenicity or developmental maturation are likely to be pivotal in our continued studies of this important metazoan group. Indeed, in contrast to earlier studies that failed to detect evidence of cytosine or adenine methylation in parasitic flatworm taxa, our laboratory has recently defined a critical role for cytosine methylation in Schistosoma mansoni oviposition, egg maturation and ovarian development. Thus, in order to identify whether this epigenetic modification features in other platyhelminth species or is a novelty of S. mansoni, we conducted a study simultaneously surveying for DNA methylation machinery components and DNA methylation marks throughout the phylum using both parasitic and non-parasitic representatives. Results Firstly, using both S. mansoni DNA methyltransferase 2 (SmDNMT2) and methyl-CpG binding domain protein (SmMBD) as query sequences, we illustrate that essential DNA methylation machinery components are well conserved throughout the phylum. Secondly, using both molecular (methylation specific amplification polymorphism, MSAP) and immunological (enzyme-linked immunoabsorbent assay, ELISA) methodologies, we demonstrate that representative species (Echinococcus multilocularis, Protopolystoma xenopodis, Schistosoma haematobium, Schistosoma japonicum, Fasciola hepatica and Polycelis nigra) within all four platyhelminth classes (Cestoda, Monogenea, Trematoda and ‘Turbellaria’) contain methylated cytosines within their genome compartments

Biological aspects of chondrosarcoma: Leaps and hurdles.

Science.gov (United States)

Mery, Benoîte; Espenel, Sophie; Guy, Jean-Baptiste; Rancoule, Chloé; Vallard, Alexis; Aloy, Marie-Thérèse; Rodriguez-Lafrasse, Claire; Magné, Nicolas

2018-06-01

Chondrosarcomas are characterized by their chemo- and radioresistance leading to a therapeutic surgical approach which remains the only available treatment with a 10-year survival between 30% and 80% depending on the grade. Non-surgical treatments are under investigation and rely on an accurate biological understanding of drug resistance mechanisms. Novel targeted therapy which represents a new relevant therapeutic approach will open new treatment options by targeting several pathways responsible for processes of proliferation and invasion. Survival pathways such as PI3K, AKT, mTOR and VEGF have been shown to be involved in proliferation of chondrosarcoma cells and antiapoptotic proteins may also play a relevant role. Other proteins such as p53 or COX2 have been identified as potential new targets. This review provides an insight into the biological substantial treatment challenges of CHS and focuses on improving our understanding of CH biology through an overview of major signaling pathways that could represent targets for new therapeutic approaches. Copyright © 2018 Elsevier B.V. All rights reserved.

Feature selection for high-dimensional integrated data

KAUST Repository

Zheng, Charles

2012-04-26

Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.

Feature selection for high-dimensional integrated data

KAUST Repository

Zheng, Charles; Schwartz, Scott; Chapkin, Robert S.; Carroll, Raymond J.; Ivanov, Ivan

2012-01-01

Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.

Biology and relevance of human acute myeloid leukemia stem cells.

Science.gov (United States)

Thomas, Daniel; Majeti, Ravindra

2017-03-23

Evidence of human acute myeloid leukemia stem cells (AML LSCs) was first reported nearly 2 decades ago through the identification of rare subpopulations of engrafting cells in xenotransplantation assays. These AML LSCs were shown to reside at the apex of a cellular hierarchy that initiates and maintains the disease, exhibiting properties of self-renewal, cell cycle quiescence, and chemoresistance. This cancer stem cell model offers an explanation for chemotherapy resistance and disease relapse and implies that approaches to treatment must eradicate LSCs for cure. More recently, a number of studies have both refined and expanded our understanding of LSCs and intrapatient heterogeneity in AML using improved xenotransplant models, genome-scale analyses, and experimental manipulation of primary patient cells. Here, we review these studies with a focus on the immunophenotype, biological properties, epigenetics, genetics, and clinical associations of human AML LSCs and discuss critical questions that need to be addressed in future research. © 2017 by The American Society of Hematology.

Sub-terahertz resonance spectroscopy of biological macromolecules and cells

Science.gov (United States)

Globus, Tatiana; Moyer, Aaron; Gelmont, Boris; Khromova, Tatyana; Sizov, Igor; Ferrance, Jerome

2013-05-01

Recently we introduced a Sub-THz spectroscopic system for characterizing vibrational resonance features from biological materials. This new, continuous-wave, frequency-domain spectroscopic sensor operates at room temperature between 315 and 480 GHz with spectral resolution of at least 1 GHz and utilizes the source and detector components from Virginia Diode, Inc. In this work we present experimental results and interpretation of spectroscopic signatures from bacterial cells and their biological macromolecule structural components. Transmission and absorption spectra of the bacterial protein thioredoxin, DNA and lyophilized cells of Escherichia coli (E. coli), as well as spores of Bacillus subtillis and B. atrophaeus have been characterized. Experimental results for biomolecules are compared with absorption spectra calculated using molecular dynamics simulation, and confirm the underlying physics for resonance spectroscopy based on interactions between THz radiation and vibrational modes or groups of modes of atomic motions. Such interactions result in multiple intense and narrow specific resonances in transmission/absorption spectra from nano-gram samples with spectral line widths as small as 3 GHz. The results of this study indicate diverse relaxation dynamic mechanisms relevant to sub-THz vibrational spectroscopy, including long-lasting processes. We demonstrate that high sensitivity in resolved specific absorption fingerprints provides conditions for reliable detection, identification and discrimination capability, to the level of strains of the same bacteria, and for monitoring interactions between biomaterials and reagents in near real-time. Additionally, it creates the basis for the development of new types of advanced biological sensors through integrating the developed system with a microfluidic platform for biomaterial samples.

BayesMD: flexible biological modeling for motif discovery

DEFF Research Database (Denmark)

Tang, Man-Hung Eric; Krogh, Anders; Winther, Ole

2008-01-01

We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained on trans......We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fashion. A mixture of Dirichlets is used as prior over nucleotide probabilities in binding sites. It is trained...

Uncovering the Biology of Cancers in Adolescents and Young Adults

Science.gov (United States)

Evidence suggests that some adolescent and young adult cancers may have unique genetic and biological features. Researchers are trying to better understand the biology of these cancers in order to identify potential therapeutic targets.

Reconstruction of biological networks based on life science data integration.

Science.gov (United States)

Kormeier, Benjamin; Hippe, Klaus; Arrigo, Patrizio; Töpel, Thoralf; Janowski, Sebastian; Hofestädt, Ralf

2010-10-27

For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH--an integration toolkit for building life science data warehouses, CardioVINEdb--a information system for biological data in cardiovascular-disease and VANESA--a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms.

Science.gov (United States)

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning. © 2016 K. Southard et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

High school and college biology: A multi-level model of the effects of high school biology courses on student academic performance in introductory college biology courses

Science.gov (United States)

Loehr, John Francis

The issue of student preparation for college study in science has been an ongoing concern for both college-bound students and educators of various levels. This study uses a national sample of college students enrolled in introductory biology courses to address the relationship between high school biology preparation and subsequent introductory college biology performance. Multi-Level Modeling was used to investigate the relationship between students' high school science and mathematics experiences and college biology performance. This analysis controls for student demographic and educational background factors along with factors associated with the college or university attended. The results indicated that high school course-taking and science instructional experiences have the largest impact on student achievement in the first introductory college biology course. In particular, enrollment in courses, such as high school Calculus and Advanced Placement (AP) Biology, along with biology course content that focuses on developing a deep understanding of the topics is found to be positively associated with student achievement in introductory college biology. On the other hand, experiencing high numbers of laboratory activities, demonstrations, and independent projects along with higher levels of laboratory freedom are associated with negative achievement. These findings are relevant to high school biology teachers, college students, their parents, and educators looking beyond the goal of high school graduation.

Tensor-based Multi-view Feature Selection with Applications to Brain Diseases

Science.gov (United States)

Cao, Bokai; He, Lifang; Kong, Xiangnan; Yu, Philip S.; Hao, Zhifeng; Ragin, Ann B.

2015-01-01

In the era of big data, we can easily access information from multiple views which may be obtained from different sources or feature subsets. Generally, different views provide complementary information for learning tasks. Thus, multi-view learning can facilitate the learning process and is prevalent in a wide range of application domains. For example, in medical science, measurements from a series of medical examinations are documented for each subject, including clinical, imaging, immunologic, serologic and cognitive measures which are obtained from multiple sources. Specifically, for brain diagnosis, we can have different quantitative analysis which can be seen as different feature subsets of a subject. It is desirable to combine all these features in an effective way for disease diagnosis. However, some measurements from less relevant medical examinations can introduce irrelevant information which can even be exaggerated after view combinations. Feature selection should therefore be incorporated in the process of multi-view learning. In this paper, we explore tensor product to bring different views together in a joint space, and present a dual method of tensor-based multi-view feature selection (dual-Tmfs) based on the idea of support vector machine recursive feature elimination. Experiments conducted on datasets derived from neurological disorder demonstrate the features selected by our proposed method yield better classification performance and are relevant to disease diagnosis. PMID:25937823

NetProt: Complex-based Feature Selection.

Science.gov (United States)

Goh, Wilson Wen Bin; Wong, Limsoon

2017-08-04

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

Quantification of biologically effective environmental UV irradiance

Science.gov (United States)

Horneck, G.

To determine the impact of environmental UV radiation on human health and ecosystems demands monitoring systems that weight the spectral irradiance according to the biological responses under consideration. In general, there are three different approaches to quantify a biologically effective solar irradiance: (i) weighted spectroradiometry where the biologically weighted radiometric quantities are derived from spectral data by multiplication with an action spectrum of a relevant photobiological reaction, e.g. erythema, DNA damage, skin cancer, reduced productivity of terrestrial plants and aquatic foodweb; (ii) wavelength integrating chemical-based or physical dosimetric systems with spectral sensitivities similar to a biological response curve; and (iii) biological dosimeters that directly weight the incident UV components of sunlight in relation to the effectiveness of the different wavelengths and to interactions between them. Most biological dosimeters, such as bacteria, bacteriophages, or biomolecules, are based on the UV sensitivity of DNA. If precisely characterized, biological dosimeters are applicable as field and personal dosimeters.

Invited Review Article: Advanced light microscopy for biological space research

Science.gov (United States)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

International Nuclear Information System (INIS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; Loon, Jack J. W. A. van; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-01-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy

Invited Review Article: Advanced light microscopy for biological space research

Energy Technology Data Exchange (ETDEWEB)

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be [Laboratory of Cell Biology and Histology, Department of Veterinary Sciences, University of Antwerp, Antwerp (Belgium); Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent (Belgium); Beghuin, Didier [Lambda-X, Nivelles (Belgium); Schwarz, Christian J. [European Space Agency (ESA), ESTEC, TEC-MMG, Noordwijk (Netherlands); Jones, David B. [Institute for Experimental Orthopaedics and Biomechanics, Philipps University, Marburg (Germany); Loon, Jack J. W. A. van [Department of Oral and Maxillofacial Surgery/Oral Pathology, VU University Medical Center and Department of Oral Cell Biology, Academic Centre for Dentistry Amsterdam, Amsterdam (Netherlands); Bereiter-Hahn, Juergen; Stelzer, Ernst H. K. [Physical Biology, BMLS (FB15, IZN), Goethe University, Frankfurt am Main (Germany)

2014-10-15

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Neuron's eye view: Inferring features of complex stimuli from neural responses.

Directory of Open Access Journals (Sweden)

Xin Chen

2017-08-01

Full Text Available Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set.

Computational Modeling of Biological Systems From Molecules to Pathways

CERN Document Server

2012-01-01

Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

Biological relevance of human papillomaviruses in vulvar cancer.

Science.gov (United States)

Halec, Gordana; Alemany, Laia; Quiros, Beatriz; Clavero, Omar; Höfler, Daniela; Alejo, Maria; Quint, Wim; Pawlita, Michael; Bosch, Francesc X; de Sanjose, Silvia

2017-04-01

The carcinogenic role of high-risk human papillomavirus (HR-HPV) types in the increasing subset of vulvar intraepithelial neoplasia and vulvar cancer in young women has been established. However, the actual number of vulvar cancer cases attributed to HPV is still imprecisely defined. In an attempt to provide a more precise definition of HPV-driven vulvar cancer, we performed HPV-type-specific E6*I mRNA analyses available for 20 HR-/possible HR (pHR)-HPV types, on tissue samples from 447 cases of vulvar cancer. HPV DNA genotyping was performed using SPF10-LiPA 25 assay due to its high sensitivity in formalin-fixed paraffin-embedded tissues. Data on p16 INK4a expression was available for comparative analysis via kappa statistics. The use of highly sensitive assays covering the detection of HPV mRNA in a broad spectrum of mucosal HPV types resulted in the detection of viral transcripts in 87% of HPV DNA+ vulvar cancers. Overall concordance between HPV mRNA+ and p16 INK4a upregulation (strong, diffuse immunostaining in >25% of tumor cells) was 92% (K=0.625, 95% confidence interval (CI)=0.531-0.719). Among these cases, 83% were concordant pairs of HPV mRNA+ and p16 INK4a + and 9% were concordant pairs of HPV mRNA- and p16 INK4a -. Our data confirm the biological role of HR-/pHR-HPV types in the great majority of HPV DNA+ vulvar cancers, resulting in an HPV-attributable fraction of at least 21% worldwide. Most HPV DNA+ vulvar cancers were associated with HPV16 (85%), but a causative role for other, less frequently occurring mucosal HPV types (HPV26, 66, 67, 68, 70 and 73) was also confirmed at the mRNA level for the first time. These findings should be taken into consideration for future screening options as HPV-associated vulvar preneoplastic lesions have increased in incidence in younger women and require different treatment than vulvar lesions that develop from rare autoimmune-related mechanisms in older women.

Involuntary top-down control by search-irrelevant features: Visual working memory biases attention in an object-based manner.

Science.gov (United States)

Foerster, Rebecca M; Schneider, Werner X

2018-03-01

Many everyday tasks involve successive visual-search episodes with changing targets. Converging evidence suggests that these targets are retained in visual working memory (VWM) and bias attention from there. It is unknown whether all or only search-relevant features of a VWM template bias attention during search. Bias signals might be configured exclusively to task-relevant features so that only search-relevant features bias attention. Alternatively, VWM might maintain objects in the form of bound features. Then, all template features will bias attention in an object-based manner, so that biasing effects are ranked by feature relevance. Here, we investigated whether search-irrelevant VWM template features bias attention. Participants had to saccade to a target opposite a distractor. A colored cue depicted the target prior to each search trial. The target was predefined only by its identity, while its color was irrelevant. When target and cue matched not only in identity (search-relevant) but also in color (search-irrelevant), saccades went more often and faster directly to the target than without any color match (Experiment 1). When introducing a cue-distractor color match (Experiment 2), direct target saccades were most likely when target and cue matched in the search-irrelevant color and least likely in case of a cue-distractor color match. When cue and target were never colored the same (Experiment 3), cue-colored distractors still captured the eyes more often than different-colored distractors despite color being search-irrelevant. As participants were informed about the misleading color, the result argues against a strategical and voluntary usage of color. Instead, search-irrelevant features biased attention obligatorily arguing for involuntary top-down control by object-based VWM templates. Copyright © 2017 Elsevier B.V. All rights reserved.

MET overexpression, gene amplification and relevant clinicopathological features in gastric adenocarcinoma.

Science.gov (United States)

Zhang, Jing; Guo, Lei; Liu, Xiuyun; Li, Wenbin; Ying, Jianming

2017-02-07

This study was conducted to investigate the expression of MET in Chinese gastric adenocarcinoma cohort, the correlation between MET overexpression and clinical pathological features, HER2 expression and MET gene amplification. A total of 816 gastric adenocarcinoma patients were included and MET and HER2 immunohistochemical (IHC) staining were performed. IHC and dual-color silver in situ hybridization analysis were performed in the tissue microarrays, constructed from the 240 patients who were randomly selected. MET overexpression (IHC 3+) was observed in 6.0% (49/816) of the cohort. MET overexpression rate was higher in patients with poor prognostic factors, such as clinical stages III/IV (p =0.012) and pathologic stages T3/T4 (p =0.027). The HER2 overexpression (IHC 3+) rate was 8.8% (72/816) and MET overexpression rate was higher in HER2 positive patients (9.7%, 7/72). A high concordance rate (94.6%) between MET overexpression and gene amplification was demonstrated. Therefore, MET overexpression could serve as a prognostic biomarker and a potential therapeutic target for gastric cancer.

Topic modeling for cluster analysis of large biological and medical datasets.

Science.gov (United States)

Zhao, Weizhong; Zou, Wen; Chen, James J

2014-01-01

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

The LAILAPS Search Engine: Relevance Ranking in Life Science Databases

Directory of Open Access Journals (Sweden)

Lange Matthias

2010-06-01

Full Text Available Search engines and retrieval systems are popular tools at a life science desktop. The manual inspection of hundreds of database entries, that reflect a life science concept or fact, is a time intensive daily work. Hereby, not the number of query results matters, but the relevance does. In this paper, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases.

Feature singletons attract spatial attention independently of feature priming.

Science.gov (United States)

Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

2017-08-01

People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

Electro-induced reactions of biologically important molecules

International Nuclear Information System (INIS)

Kocisek, J.

2010-01-01

The thesis presents the results of research activities in the field of electron interactions with biologically relevant molecules which was carried out during my PhD studies at the Department of Experimental Physics, Comenius University in Bratislava. Electron induced interactions with biologically relevant molecules were experimentally studied using crossed electron-molecule beams experiment. The obtained results, were presented in four publications in international scientific journals. First study of deals with electron impact ionisation of furanose alcohols [see 1. in list of author publications on page 22]. It has been motivated by most important works in the field of electron induced damages of DNA bases [4]. Studied 3-hydroxytetrahydrofuran and tetrahydrofurfuryl alcohol, are important model molecules for more complex biological systems (e.g. deoxyribose).The influence of hydroxyl group on stabilisation of the positive ions of the molecules, together with the stability of furan ring in ionized form are main themes of the study. The studies of small amides and aminoacids are connected to scientific studies in the field of formation of the aminoacids and other biologically relevant molecules in space and works trying to explain electron induced processes in more complex molecules[12, 13, 24]. The most important results were obtained for aminoacid Serine [see 2. in list of author publications on page 22]. We have showed that additional OH group of Serine considerably lower the reaction enthalpy limit of reactions resulting to formation of neutral water molecules, in comparison to other amino acids. Also the study of (M-H)- reaction channel using the electron beam with FWHM under 100 meV is of high importance in the field. The last part of the thesis is focused on the electron interactions with organosilane compounds. Materials prepared from organosilane molecules in plasmas have wide range of applications in both biology and medicine. We have studied electron

Set membership experimental design for biological systems

Directory of Open Access Journals (Sweden)

Marvel Skylar W

2012-03-01

Full Text Available Abstract Background Experimental design approaches for biological systems are needed to help conserve the limited resources that are allocated for performing experiments. The assumptions used when assigning probability density functions to characterize uncertainty in biological systems are unwarranted when only a small number of measurements can be obtained. In these situations, the uncertainty in biological systems is more appropriately characterized in a bounded-error context. Additionally, effort must be made to improve the connection between modelers and experimentalists by relating design metrics to biologically relevant information. Bounded-error experimental design approaches that can assess the impact of additional measurements on model uncertainty are needed to identify the most appropriate balance between the collection of data and the availability of resources. Results In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available. This approach leverages many of the recent advances in bounded-error parameter and state estimation methods that use interval analysis to generate parameter sets and state bounds consistent with uncertain data measurements. We devise a novel approach using set-based uncertainty propagation to estimate measurement ranges at candidate time points. We then use these estimated measurements at the candidate time points to evaluate which candidate measurements furthest reduce model uncertainty. A method for quickly combining multiple candidate time points is presented and allows for determining the effect of adding multiple measurements. Biologically relevant metrics are developed and used to predict when new data measurements should be acquired, which system components should be measured and how many additional measurements should be obtained. Conclusions The practicability of our approach is illustrated with a case study. This

Turing patterns and biological explanation

DEFF Research Database (Denmark)

Serban, Maria

2017-01-01

, promoting theory exploration, and acting as constitutive parts of empirically adequate explanations of naturally occurring phenomena, such as biological pattern formation. Focusing on the roles that minimal model explanations play in science motivates the adoption of a broader diachronic view of scientific......Turing patterns are a class of minimal mathematical models that have been used to discover and conceptualize certain abstract features of early biological development. This paper examines a range of these minimal models in order to articulate and elaborate a philosophical analysis...

Biology and Mechanics of Blood Flows Part I: Biology

CERN Document Server

Thiriet, Marc

2008-01-01

Biology and Mechanics of Blood Flows presents the basic knowledge and state-of-the-art techniques necessary to carry out investigations of the cardiovascular system using modeling and simulation. Part I of this two-volume sequence, Biology, addresses the nanoscopic and microscopic scales. The nanoscale corresponds to the scale of biochemical reaction cascades involved in cell adaptation to mechanical stresses among other stimuli. The microscale is the scale of stress-induced tissue remodeling associated with acute or chronic loadings. The cardiovascular system, like any physiological system, has a complicated three-dimensional structure and composition. Its time dependent behavior is regulated, and this complex system has many components. In this authoritative work, the author provides a survey of relevant cell components and processes, with detailed coverage of the electrical and mechanical behaviors of vascular cells, tissues, and organs. Because the behaviors of vascular cells and tissues are tightly coupl...

Teaching Biology through Statistics: Application of Statistical Methods in Genetics and Zoology Courses

Science.gov (United States)

Colon-Berlingeri, Migdalisel; Burrowes, Patricia A.

2011-01-01

Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the…

Synthetic Biology and the Argument from Continuity with Established Technologies

DEFF Research Database (Denmark)

Christiansen, Andreas

2015-01-01

) that it ignores the distinction between what reasons we have and what we should do all things considered. I then illustrate the Continuity Argument and its problems in the case where human manipulation of organisms’ genetic makeup is a suggested reason for finding synthetic biology problematic. Finally, I suggest......Defenders of synthetic biology commonly make reference to the fact that established technologies, such as domestication or selective breeding, share some of the features of synthetic biology that critics argue make it ethically problematic. In this chapter, I reconstruct such references...... as instances of a type of argument which I dub the Continuity Argument. Roughly, the Continuity Argument seeks to show that if we are not disposed to reject the established technology, then features that this technology share with synthetic biology cannot provide reasons to find it ethically problematic. I...

Feature Optimization for Long-Range Visual Homing in Changing Environments

Directory of Open Access Journals (Sweden)

Qidan Zhu

2014-02-01

Full Text Available This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

Permutation importance: a corrected feature importance measure.

Science.gov (United States)

Altmann, André; Toloşi, Laura; Sander, Oliver; Lengauer, Thomas

2010-05-15

In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility. However, in the past years effective estimators of feature relevance have been derived for highly complex or non-parametric models such as support vector machines and RandomForest (RF) models. Recently, it has been observed that RF models are biased in such a way that categorical variables with a large number of categories are preferred. In this work, we introduce a heuristic for normalizing feature importance measures that can correct the feature importance bias. The method is based on repeated permutations of the outcome vector for estimating the distribution of measured importance for each variable in a non-informative setting. The P-value of the observed importance provides a corrected measure of feature importance. We apply our method to simulated data and demonstrate that (i) non-informative predictors do not receive significant P-values, (ii) informative variables can successfully be recovered among non-informative variables and (iii) P-values computed with permutation importance (PIMP) are very helpful for deciding the significance of variables, and therefore improve model interpretability. Furthermore, PIMP was used to correct RF-based importance measures for two real-world case studies. We propose an improved RF model that uses the significant variables with respect to the PIMP measure and show that its prediction accuracy is superior to that of other existing models. R code for the method presented in this article is available at http://www.mpi-inf.mpg.de/ approximately altmann/download/PIMP.R CONTACT: altmann@mpi-inf.mpg.de, laura.tolosi@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online.

Feature diagnosticity and task context shape activity in human scene-selective cortex.

Science.gov (United States)

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

Reconstruction of biological networks based on life science data integration

Directory of Open Access Journals (Sweden)

Kormeier Benjamin

2010-06-01

Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

Integrated pathway clusters with coherent biological themes for target prioritisation.

Directory of Open Access Journals (Sweden)

Yi-An Chen

Full Text Available Prioritising candidate genes for further experimental characterisation is an essential, yet challenging task in biomedical research. One way of achieving this goal is to identify specific biological themes that are enriched within the gene set of interest to obtain insights into the biological phenomena under study. Biological pathway data have been particularly useful in identifying functional associations of genes and/or gene sets. However, biological pathway information as compiled in varied repositories often differs in scope and content, preventing a more effective and comprehensive characterisation of gene sets. Here we describe a new approach to constructing biologically coherent gene sets from pathway data in major public repositories and employing them for functional analysis of large gene sets. We first revealed significant overlaps in gene content between different pathways and then defined a clustering method based on the shared gene content and the similarity of gene overlap patterns. We established the biological relevance of the constructed pathway clusters using independent quantitative measures and we finally demonstrated the effectiveness of the constructed pathway clusters in comparative functional enrichment analysis of gene sets associated with diverse human diseases gathered from the literature. The pathway clusters and gene mappings have been integrated into the TargetMine data warehouse and are likely to provide a concise, manageable and biologically relevant means of functional analysis of gene sets and to facilitate candidate gene prioritisation.

Is 'class effect' relevant when assessing the benefit/risk profile of a biologic agent?

NARCIS (Netherlands)

Sterry, W.; Kerkhof, P.C.M. van de

2012-01-01

Psoriasis is a chronic, genetically predisposed skin disorder, characterised by thickened scaly plaques. Although no therapy is recognised as curative, therapies aimed at symptom control include biologic agents that are generally designed to block molecular activation of cellular pathways of a

Benign vascular lesions of bone: radiologic and pathologic features

Energy Technology Data Exchange (ETDEWEB)

Wenger, D.E.; Wold, L.E. [Mayo Foundation, Rochester, MN (United States)

2000-02-01

The benign vascular tumors of bone represent a diverse group of tumors that can present with a broad spectrum of clinical signs and symptoms. They can also present a significant diagnostic challenge due to their widely variable radiographic imaging and histologic features. Some of the tumors manifest as clearly benign lesions with tissue-specific diagnostic imaging features, while others have non-specific imaging features that may simulate malignant neoplasm. This article will provide a review of the nomenclature and the characteristic radiographic and pathologic features of the benign vascular lesions of bone. The information will aid in improving our diagnostic accuracy and enhance our understanding of the biologic potential of this diverse group of osseous lesions. (orig.)

Benign vascular lesions of bone: radiologic and pathologic features

International Nuclear Information System (INIS)

Wenger, D.E.; Wold, L.E.

2000-01-01

The benign vascular tumors of bone represent a diverse group of tumors that can present with a broad spectrum of clinical signs and symptoms. They can also present a significant diagnostic challenge due to their widely variable radiographic imaging and histologic features. Some of the tumors manifest as clearly benign lesions with tissue-specific diagnostic imaging features, while others have non-specific imaging features that may simulate malignant neoplasm. This article will provide a review of the nomenclature and the characteristic radiographic and pathologic features of the benign vascular lesions of bone. The information will aid in improving our diagnostic accuracy and enhance our understanding of the biologic potential of this diverse group of osseous lesions. (orig.)

Expectancies as core features of mental disorders.

Science.gov (United States)

Rief, Winfried; Glombiewski, Julia A; Gollwitzer, Mario; Schubö, Anna; Schwarting, Rainer; Thorwart, Anna

2015-09-01

Expectancies are core features of mental disorders, and change in expectations is therefore one of the core mechanisms of treatment in psychiatry. We aim to improve our understanding of expectancies by summarizing factors that contribute to their development, persistence, and modification. We pay particular attention to the issue of persistence of expectancies despite experiences that contradict them. Based on recent research findings, we propose a new model for expectation persistence and expectation change. When expectations are established, effects are evident in neural and other biological systems, for example, via anticipatory reactions, different biological reactions to expected versus unexpected stimuli, etc. Psychological 'immunization' and 'assimilation', implicit self-confirming processes, and stability of biological processes help us to better understand why expectancies persist even in the presence of expectation violations. Learning theory, attentional processes, social influences, and biological determinants contribute to the development, persistence, and modification of expectancies. Psychological interventions should focus on optimizing expectation violation to achieve optimal treatment outcome and to avoid treatment failures.

Biological challenges of true space settlement

Science.gov (United States)

Mankins, John C.; Mankins, Willa M.; Walter, Helen

2018-05-01

"Space Settlements" - i.e., permanent human communities beyond Earth's biosphere - have been discussed within the space advocacy community since the 1970s. Now, with the end of the International Space Station (ISS) program fast approaching (planned for 2024-2025) and the advent of low cost Earth-to-orbit (ETO) transportation in the near future, the concept is coming once more into mainstream. Considerable attention has been focused on various issues associated with the engineering and human health considerations of space settlement such as artificial gravity and radiation shielding. However, relatively little attention has been given to the biological implications of a self-sufficient space settlement. Three fundamental questions are explored in this paper: (1) what are the biological "foundations" of truly self-sufficient space settlements in the foreseeable future, (2) what is the minimum scale for such self-sustaining human settlements, and (3) what are the integrated biologically-driven system requirements for such settlements? The paper examines briefly the implications of the answers to these questions in relevant potential settings (including free space, the Moon and Mars). Finally, this paper suggests relevant directions for future research and development in order for such space settlements to become viable in the future.

Seeing without knowing: task relevance dissociates between visual awareness and recognition.

Science.gov (United States)

Eitam, Baruch; Shoval, Roy; Yeshurun, Yaffa

2015-03-01

We demonstrate that task relevance dissociates between visual awareness and knowledge activation to create a state of seeing without knowing-visual awareness of familiar stimuli without recognizing them. We rely on the fact that in order to experience a Kanizsa illusion, participants must be aware of its inducers. While people can indicate the orientation of the illusory rectangle with great ease (signifying that they have consciously experienced the illusion's inducers), almost 30% of them could not report the inducers' color. Thus, people can see, in the sense of phenomenally experiencing, but not know, in the sense of recognizing what the object is or activating appropriate knowledge about it. Experiment 2 tests whether relevance-based selection operates within objects and shows that, contrary to the pattern of results found with features of different objects in our previous studies and replicated in Experiment 1, selection does not occur when both relevant and irrelevant features belong to the same object. We discuss these findings in relation to the existing theories of consciousness and to attention and inattentional blindness, and the role of cognitive load, object-based attention, and the use of self-reports as measures of awareness. © 2015 New York Academy of Sciences.

Nano- and micro-fabrication for single-molecule biological studies

NARCIS (Netherlands)

Huang, Z.

2012-01-01

Heterogeneity is a general feature in biological system. In order to avoid possible misleading effects of ensemble averaging, and to ensure a correct understanding of the biological system, it is very important to look into individuals, such as a single bio-molecule or a single cell, for details.

Beyond the obvious limits of ore deposits: The use of mineralogical, geochemical, and biological features for the remote detection of mineralization

Science.gov (United States)

Kelley, D.L.; Kelley, K.D.; Coker, W.B.; Caughlin, B.; Doherty, M.E.

2006-01-01

Far field features of ore deposits include mineralogical, geochemical, or biological attributes that can be recognized beyond the obvious limits of the deposits. They can be primary, if formed in association with mineralization or alteration processes, or secondary, if formed from the interaction of ore deposits with the hydrosphere and biosphere. This paper examines a variety of far field features of different ore deposit types and considers novel applications to exploration and discovery. Primary far field features include mineral and rock chemistry, isotopic or element halos, fluid pathways and thermal anomalies in host-rock sequences. Examples include the use of apatite chemistry to distinguish intrusive rocks permissive for iron oxide copper gold (IOCG) and porphyry deposits; resistate mineral (e.g., rutile, tourmaline) chemistry in exploration for volcanogenic massive sulfide (VMS), orogenic gold, and porphyry deposits; and pyrite chemistry to vector toward sedimentary exhalative (sedex) deposits. Distinctive whole-rock geochemical signatures also can be recognized as a far field feature of porphyry deposits. For example, unique Sr/Y ratios in whole-rock samples, used to distinguish barren versus fertile magmas for Cu mineralization, result from the differentiation of oxidized hydrous melts. Anomalous concentrations of halogen elements (Cl, Br, and I) have been found for distances of up to 200 m away from some mineralized centers. Variations in isotopic composition between ore-bearing and barren intrusions and/or systematic vertical and lateral zonation in sulfur, carbon, or oxygen isotope values have been documented for some deposit types. Owing to the thermal aureole that extends beyond the area of mineralization for some deposits, detection of paleothermal effects through methods such as conodont alteration indices, vitrinite or bitumen reflectance, illite crystallinity, and apatite or zircon thermochronology studies also can be valuable, particularly for

Celluloid angels: a research study of nurses in feature films 1900-2007.

Science.gov (United States)

Stanley, David J

2008-10-01

This paper is a report of a study examining the influence on how nursing and nurses are portrayed in feature films made between 1900 and 2007, with a nurse as their main or a principle character and a story-line related specifically to nursing. Nurses and the nursing profession are frequently portrayed negatively or stereotypically in the media, with nurses often being portrayed as feminine and caring but not as leaders or professionals capable of autonomous practice. A mixed method approach was used to examine feature films made in the Western world. Over 36,000 feature film synopses were reviewed (via CINAHL, ProQuest and relevant movie-specific literature) for the keywords 'nurse'/'nursing'. Identified films were analysed quantitatively to determine their country of production, genre, plot(s) and other relevant data, and qualitatively to identify the emergence of themes related to the image of nurses/nursing in films. For the period from 1900 to 2007, 280 relevant feature films were identified. Most films were made in the United States of America or United Kingdom, although in recent years films have been increasingly produced in other countries. Early films portrayed nurses as self-sacrificial heroines, sex objects and romantics. More recent films increasingly portray them as strong and self-confident, professionals. Nurse-related films offer a unique insight into the image of nurses and how they have been portrayed. Nurses need to be aware of the impact the film industry has on how nurses and nursing are perceived and represented in feature films.

Robustness: confronting lessons from physics and biology.

Science.gov (United States)

Lesne, Annick

2008-11-01

The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

Science.gov (United States)

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

Molecular biology - Part II: Beneficial liaisons: Radiobiology meets cellular and molecular biology

International Nuclear Information System (INIS)

Stevenson, Mary Ann; Coleman, C. Norman

1997-01-01

Purpose: The purpose of this course is to familiarize radiation oncologists with the concepts and terminology of molecular and cellular biology that are especially relevant to radiation oncology. The ability of radiation oncologists to remain current with the new discoveries of modern biology is essential to the development of improved therapeutic strategies and, importantly, to the proper balance between investment in technology and biology. Objective: This year, this Refresher Course is part of a three-part ''series'' including Drs. McKenna and Dritschilo. The objective is to provide continuing education for the academic and practicing radiation oncologist, physicist and biologist in the modern biologic concepts of cancer and its treatment. An effort will be made to relate these general concepts to the clinic by providing a broad view as to potential new biological treatments which might enhance the efficacy of radiation therapy. The specific focus of this Course will vary from year to year. Some of the classic radiation biology models which form the basis of clinical practice and laboratory research will be examined and 'newer' models will be presented which take into account the emerging knowledge of cellular and molecular biology. A few techniques in molecular and cellular biology will be described to the extent necessary to understand their basic concepts and their applicability. Aspects of radiation biology which will be covered include cell cycle, radiation-induced changes in the cellular phenotype, and considerations of the effect of the tumor microenvironment. It is not the expectation that the attendees will become experts in the particular subjects presented. Rather, it is the intent to increase their curiosity as to the new knowledge that is emerging and to demonstrate that these seemingly complicated areas can be understood and appreciated with a modicum of the effort

Molecular biology - Part II: Beneficial liaisons: Radiobiology meets cellular and molecular biology

International Nuclear Information System (INIS)

Stevenson, Mary Ann; Coleman, C. Norman

1996-01-01

Purpose: The purpose of this course is to familiarize radiation oncologists with the concepts and terminology of molecular and cellular biology that are especially relevant to radiation oncology. The ability of radiation oncologists to remain current with the new discoveries of modern biology is essential to the development of improved therapeutic strategies and, importantly, to the proper balance between investment in technology and biology. Objective: This year, this Refresher Course is part of a three-part 'series' including Drs. Martin Brown and Amato Giaccia. The objective is to provide continuing education for the academic and practicing radiation oncologist, physicist and biologist in the modern biologic concepts of cancer and its treatment. An effort will be made to relate these general concepts to the clinic by providing a broad view as to potential new biological treatments which might enhance the efficacy of radiation therapy. The specific focus of this Course will vary from year to year. Some of the classic radiation biology models which form the basis of clinical practice and laboratory research will be examined and 'newer' models will be presented which take into account the emerging knowledge of cellular and molecular biology. A few techniques in molecular and cellular biology will be described to the extent necessary to understand their basic concepts and their applicability. Aspects of radiation biology which will be covered include cell cycle, radiation-induced changes in the cellular phenotype, and considerations of the effect of the tumor microenvironment. It is not the expectation that the attendees will become experts in the particular subjects presented. Rather, it is the intent to increase their curiosity as to the new knowledge that is emerging and to demonstrate that these seemingly complicated areas can be understood and appreciated with a modicum of the effort

The emerging age of cell-free synthetic biology.

Science.gov (United States)

Smith, Mark Thomas; Wilding, Kristen M; Hunt, Jeremy M; Bennett, Anthony M; Bundy, Bradley C

2014-08-25

The engineering of and mastery over biological parts has catalyzed the emergence of synthetic biology. This field has grown exponentially in the past decade. As increasingly more applications of synthetic biology are pursued, more challenges are encountered, such as delivering genetic material into cells and optimizing genetic circuits in vivo. An in vitro or cell-free approach to synthetic biology simplifies and avoids many of the pitfalls of in vivo synthetic biology. In this review, we describe some of the innate features that make cell-free systems compelling platforms for synthetic biology and discuss emerging improvements of cell-free technologies. We also select and highlight recent and emerging applications of cell-free synthetic biology. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Framework for the Integration of Mobile Device Features in PLM

OpenAIRE

Hopf, Jens Michael

2016-01-01

Currently, companies have covered their business processes with stationary workstations while mobile business applications have limited relevance. Companies can cover their overall business processes more time-efficiently and cost-effectively when they integrate mobile users in workflows using mobile device features. The objective is a framework that can be used to model and control business applications for PLM processes using mobile device features to allow a totally new user experience.

Cascade detection for the extraction of localized sequence features; specificity results for HIV-1 protease and structure-function results for the Schellman loop.

Science.gov (United States)

Newell, Nicholas E

2011-12-15

The extraction of the set of features most relevant to function from classified biological sequence sets is still a challenging problem. A central issue is the determination of expected counts for higher order features so that artifact features may be screened. Cascade detection (CD), a new algorithm for the extraction of localized features from sequence sets, is introduced. CD is a natural extension of the proportional modeling techniques used in contingency table analysis into the domain of feature detection. The algorithm is successfully tested on synthetic data and then applied to feature detection problems from two different domains to demonstrate its broad utility. An analysis of HIV-1 protease specificity reveals patterns of strong first-order features that group hydrophobic residues by side chain geometry and exhibit substantial symmetry about the cleavage site. Higher order results suggest that favorable cooperativity is weak by comparison and broadly distributed, but indicate possible synergies between negative charge and hydrophobicity in the substrate. Structure-function results for the Schellman loop, a helix-capping motif in proteins, contain strong first-order features and also show statistically significant cooperativities that provide new insights into the design of the motif. These include a new 'hydrophobic staple' and multiple amphipathic and electrostatic pair features. CD should prove useful not only for sequence analysis, but also for the detection of multifactor synergies in cross-classified data from clinical studies or other sources. Windows XP/7 application and data files available at: https://sites.google.com/site/cascadedetect/home. nacnewell@comcast.net Supplementary information is available at Bioinformatics online.

The potential roles of biological soil crusts in dryland hydrologic cycles

Science.gov (United States)

Belnap, J.

2006-01-01

Biological soil crusts (BSCs) are the dominant living cover in many drylands of the world. They possess many features that can influence different aspects of local hydrologic cycles, including soil porosity, absorptivity, roughness, aggregate stability, texture, pore formation, and water retention. The influence of biological soil crusts on these factors depends on their internal and external structure, which varies with climate, soil, and disturbance history. This paper presents the different types of biological soil crusts, discusses how crust type likely influences various aspects of the hydrologic cycle, and reviews what is known and not known about the influence of biological crusts on sediment production and water infiltration versus runoff in various drylands around the world. Most studies examining the effect of biological soil crusts on local hydrology are done by comparing undisturbed sites with those recently disturbed by the researchers. Unfortunately, this greatly complicates interpretation of the results. Applied disturbances alter many soil features such as soil texture, roughness, aggregate stability, physical crusting, porosity, and bulk density in ways that would not necessarily be the same if crusts were not naturally present. Combined, these studies show little agreement on how biological crusts affect water infiltration or runoff. However, when studies are separated by biological crust type and utilize naturally occurring differences among these types, results indicate that biological crusts in hyperarid regions reduce infiltration and increase runoff, have mixed effects in and regions, and increase infiltration and reduce runoff in semiarid cool and cold drylands. However, more studies are needed before broad generalizations can be made on how biological crusts affect infiltration and runoff. We especially need studies that control for sub-surface soil features such as bulk density, micro- and macropores, and biological crust structure. Unlike

Two bridges between biology and learning

Directory of Open Access Journals (Sweden)

Jorun Nyléhn

2016-04-01

Full Text Available Human biology, in terms of organization of our brains and our evolutionary past, constrains and enables learning. Two examples where neurobiology and evolution influences learning are given and discussed in relation to education: mirror neurons and adaptive memory. Mirror neurons serves imitation and understanding of other peoples intentions. Adaptive memory implies that our memory is an adaptation influenced by our evolutionary past, enabling us to solve problems in the present and in the future. Additionally, the aim is to contribute to bridges between natural and social sciences in an attempt to achieve an improved understanding of learning. The relevance of perspectives on learning founded in biology are discussed, and the article argues for including biological perspectives in discussions of education and learning processes.

Synthetic biology, inspired by synthetic chemistry.

Science.gov (United States)

Malinova, V; Nallani, M; Meier, W P; Sinner, E K

2012-07-16

The topic synthetic biology appears still as an 'empty basket to be filled'. However, there is already plenty of claims and visions, as well as convincing research strategies about the theme of synthetic biology. First of all, synthetic biology seems to be about the engineering of biology - about bottom-up and top-down approaches, compromising complexity versus stability of artificial architectures, relevant in biology. Synthetic biology accounts for heterogeneous approaches towards minimal and even artificial life, the engineering of biochemical pathways on the organismic level, the modelling of molecular processes and finally, the combination of synthetic with nature-derived materials and architectural concepts, such as a cellular membrane. Still, synthetic biology is a discipline, which embraces interdisciplinary attempts in order to have a profound, scientific base to enable the re-design of nature and to compose architectures and processes with man-made matter. We like to give an overview about the developments in the field of synthetic biology, regarding polymer-based analogs of cellular membranes and what questions can be answered by applying synthetic polymer science towards the smallest unit in life, namely a cell. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Biología molecular y cáncer de tiroides Molecular biology and thyroid cancer

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Juan Cassola Santana

2010-12-01

Full Text Available Se realiza una revisión actualizada sobre aspectos de biología molecular que servirán de base al cirujano actuante para un mejor conocimiento del cáncer tiroideo. El objetivo radica en alertar a los cirujanos sobre las nuevas evaluaciones a las que podrán someterse los tumores de la tiroides, que implicarán cambios en toda la gama de conductas actuales en estos casos. Se señalan aspectos que sin duda cambiarán los conceptos que se manejan hoy día.A updating review is carry out on the features of molecular biology as a basis for acting surgeon to a better knowledge of thyroid cancer. The objective is to alert surgeons on the new assessments for this type of cancer, implicating changes in all the range of current behaviors in these cases. The features that will change the nowadays concepts in this respect.

Dynamic binding of visual features by neuronal/stimulus synchrony.

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Iwabuchi, A

1998-05-01

When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

Relevance of and New Developments in Serology for Toxoplasmosis.

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Dard, Céline; Fricker-Hidalgo, Hélène; Brenier-Pinchart, Marie-Pierre; Pelloux, Hervé

2016-06-01

Toxoplasmosis is a widespread parasitic disease caused by the intracellular parasite Toxoplasma gondii with a wide spectrum of clinical outcomes. The biological diagnosis of toxoplasmosis is often difficult and of paramount importance because clinical features are not sufficient to discriminate between toxoplasmosis and other illnesses. Serological tests are the most widely used biological tools for the diagnosis of toxoplasmosis worldwide. This review focuses on the crucial role of serology in providing answers to the most important questions related to the epidemiology and diagnosis of toxoplasmosis in human pathology. Notwithstanding their undeniable importance, serological tools need to be continuously improved and the interpretation of the ensuing results remains complex in many circumstances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatiotemporal Features for Asynchronous Event-based Data

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Xavier eLagorce

2015-02-01

Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

Continuum analysis of biological systems conserved quantities, fluxes and forces

CERN Document Server

Suraishkumar, G K

2014-01-01

This book addresses the analysis, in the continuum regime, of biological systems at various scales, from the cellular level to the industrial one. It presents both fundamental conservation principles (mass, charge, momentum and energy) and relevant fluxes resulting from appropriate driving forces, which are important for the analysis, design and operation of biological systems. It includes the concept of charge conservation, an important principle for biological systems that is not explicitly covered in any other book of this kind. The book is organized in five parts: mass conservation; charge conservation; momentum conservation; energy conservation; and multiple conservations simultaneously applied. All mathematical aspects are presented step by step, allowing any reader with a basic mathematical background (calculus, differential equations, linear algebra, etc.) to follow the text with ease. The book promotes an intuitive understanding of all the relevant principles and in so doing facilitates their applica...

SIP-FS: a novel feature selection for data representation

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Yiyou Guo

2018-02-01

Full Text Available Abstract Multiple features are widely used to characterize real-world datasets. It is desirable to select leading features with stability and interpretability from a set of distinct features for a comprehensive data description. However, most of existing feature selection methods focus on the predictability (e.g., prediction accuracy of selected results yet neglect stability. To obtain compact data representation, a novel feature selection method is proposed to improve stability, and interpretability without sacrificing predictability (SIP-FS. Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types. Several feature types (each contains a certain number of features can then be selected and evaluated quantitatively to determine what types contribute to a specific class, thereby enhancing the so-called interpretability of features. Moreover, stability is introduced in the criterion of SIP-FS to obtain consistent results of ranking. We conduct experiments on three publicly available datasets using one-versus-all strategy to select class-specific features. The experiments illustrate that SIP-FS achieves significant performance improvements in terms of stability and interpretability with desirable prediction accuracy and indicates advantages over several state-of-the-art approaches.

Biological network extraction from scientific literature: state of the art and challenges.

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Li, Chen; Liakata, Maria; Rebholz-Schuhmann, Dietrich

2014-09-01

Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical entities. It is necessary to be able to combine data from all available resources to judge the functionality, complexity and completeness of any given network overall, but especially the full integration of relevant information from the scientific literature is still an ongoing and complex task. Currently, the text-mining research community is steadily moving towards processing the full body of the scientific literature by making use of rich linguistic features such as full text parsing, to extract biological interactions. The next step will be to combine these with information from scientific databases to support hypothesis generation for the discovery of new knowledge and the extension of biological networks. The generation of comprehensive networks requires technologies such as entity grounding, coordination resolution and co-reference resolution, which are not fully solved and are required to further improve the quality of results. Here, we analyse the state of the art for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora, discuss challenges involved and identify directions for future research. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.

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Bineng Zhong

Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.

Correlation between γ-ray-induced DNA double-strand breakage and cell killing after biologically relevant doses: analysis by pulsed-field gel electrophoresis

International Nuclear Information System (INIS)

Murray, D.

1994-01-01

We examined the degree of correlation between γ-ray-induced lethality and DNA double-strand breaks (dsbs) after biologically relevant doses of radiation. Radiation lethality was modified by treating 14 C-labelled Chinese hamster ovary cells with either of two aminothiols (WR-1065 or WR-255591) and the associated effect on dsb induction was determined by pulsed-field gel electrophoresis (PFGE). The use of phosphorimaging to analyse the distribution of 14 C-activity in the gel greatly improved the low-dose resolution of the PFGE assay. Both WR-1065 and WR-255591 protected against dsb induction and lethality to a similar extent after low doses of radiation. although this correlation broke down when supralethal doses were used to induce dsbs. Thus, the level of dsbs induced in these cells as measured by PFGE after survival-curve doses of γ-radiation is consistently predictive of the degree of lethality obtained, implying a cause-effect relationship between these two parameters and confirming previous results obtained using the neutral filter elution assay for dsbs. (author)

Ranked retrieval of Computational Biology models.

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Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

2010-08-11

The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

PathText: a text mining integrator for biological pathway visualizations

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Kemper, Brian; Matsuzaki, Takuya; Matsuoka, Yukiko; Tsuruoka, Yoshimasa; Kitano, Hiroaki; Ananiadou, Sophia; Tsujii, Jun'ichi

2010-01-01

Motivation: Metabolic and signaling pathways are an increasingly important part of organizing knowledge in systems biology. They serve to integrate collective interpretations of facts scattered throughout literature. Biologists construct a pathway by reading a large number of articles and interpreting them as a consistent network, but most of the models constructed currently lack direct links to those articles. Biologists who want to check the original articles have to spend substantial amounts of time to collect relevant articles and identify the sections relevant to the pathway. Furthermore, with the scientific literature expanding by several thousand papers per week, keeping a model relevant requires a continuous curation effort. In this article, we present a system designed to integrate a pathway visualizer, text mining systems and annotation tools into a seamless environment. This will enable biologists to freely move between parts of a pathway and relevant sections of articles, as well as identify relevant papers from large text bases. The system, PathText, is developed by Systems Biology Institute, Okinawa Institute of Science and Technology, National Centre for Text Mining (University of Manchester) and the University of Tokyo, and is being used by groups of biologists from these locations. Contact: brian@monrovian.com. PMID:20529930

The biological significance and clinical applications of exosomes in ovarian cancer.

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Dorayappan, Kalpana Deepa Priya; Wallbillich, John J; Cohn, David E; Selvendiran, Karuppaiyah

2016-07-01

Exosomes are nano-sized (20-100nm) vesicles released by a variety of cells and are generated within the endosomal system or at the plasma membrane. There is emerging evidence that exosomes play a key role in intercellular communication in ovarian and other cancers. The protein and microRNA content of exosomes has been implicated in various intracellular processes that mediate oncogenesis, tumor spread, and drug resistance. Exosomes may prime distant tissue sites for reception of future metastases and their release can be mediated by the tumor microenvironment (e.g., hypoxia). Ovarian cancer-derived exosomes have unique features that could be leveraged for use as biomarkers to facilitate improved detection and treatment of the disease. Further, exosomes have the potential to serve as targets and/or drug delivery vehicles in the treatment of ovarian cancer. In this review we discuss the biological and clinical significance of exosomes relevant to the progression, detection, and treatment of ovarian cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Macroscopic sessile tumor architecture is a pathologic feature of biologically aggressive upper tract urothelial carcinoma.

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Fritsche, Hans-Martin; Novara, Giacomo; Burger, Maximilian; Gupta, Amit; Matsumoto, Kazumasa; Kassouf, Wassim; Sircar, Kanishka; Zattoni, Filiberto; Walton, Tom; Tritschler, Stefan; Baba, Shiro; Bastian, Patrick J; Martínez-Salamanca, Juan I; Seitz, Christian; Otto, Wolfgang; Wieland, Wolf Ferdinand; Karakiewicz, Pierre I; Ficarra, Vincenzo; Hartmann, Arndt; Shariat, Shahrokh F

2012-09-01

Macroscopic sessile tumor architecture was associated with adverse outcomes after radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC). Before inclusion in daily clinical decision-making, the prognostic value of tumor architecture needs to be validated in an independent, external dataset. We tested whether macroscopic tumor architecture improves outcome prediction in an international cohort of patients. We retrospectively studied 754 patients treated with RNU for UTUC without neoadjuvant chemotherapy at 9 centers located in Asia, Canada, and Europe. Tumor architecture was macroscopically categorized as either papillary or sessile. Univariable and multivariable Cox regression analyses were used to address recurrence-free (RFS) and cancer-specific survival (CSS) estimates. Macroscopic sessile architecture was present in 20% of the patients. Its prevalence increased with advancing pathologic stage and it was significantly associated with established features of biologically aggressive UTUC, such as tumor grade, lymph node metastasis, lymphovascular invasion, and concomitant CIS (all P values architecture were 85% and 90%, compared with 58% and 66% for those with macroscopic sessile architecture, respectively (P values architecture was an independent predictor of both RFS (hazard ratio {HR}: 1.5; P = 0.036) and CSS (HR: 1.5; P = 0.03). We confirmed the independent prognostic value of macroscopic tumor architecture in a large, independent, multicenter UTUC cohort. It should be reported in every pathology report and included in post-RNU predictive models in order to refine current clinical decision making regarding follow-up protocol and adjuvant therapy. Copyright © 2012 Elsevier Inc. All rights reserved.

Identifying novel genes and biological processes relevant to the development of cancer therapy-induced mucositis: An informative gene network analysis.

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Cielito C Reyes-Gibby

biological processes, including pathways related to inflammation and oxidative stress, that are relevant to mucositis development, thus providing the basis for future studies to improve the management and treatment of mucositis in patients with cancer.

Identifying novel genes and biological processes relevant to the development of cancer therapy-induced mucositis: An informative gene network analysis.

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Reyes-Gibby, Cielito C; Melkonian, Stephanie C; Wang, Jian; Yu, Robert K; Shelburne, Samuel A; Lu, Charles; Gunn, Gary Brandon; Chambers, Mark S; Hanna, Ehab Y; Yeung, Sai-Ching J; Shete, Sanjay

2017-01-01

Mucositis is a complex, dose-limiting toxicity of chemotherapy or radiotherapy that leads to painful mouth ulcers, difficulty eating or swallowing, gastrointestinal distress, and reduced quality of life for patients with cancer. Mucositis is most common for those undergoing high-dose chemotherapy and hematopoietic stem cell transplantation and for those being treated for malignancies of the head and neck. Treatment and management of mucositis remain challenging. It is expected that multiple genes are involved in the formation, severity, and persistence of mucositis. We used Ingenuity Pathway Analysis (IPA), a novel network-based approach that integrates complex intracellular and intercellular interactions involved in diseases, to systematically explore the molecular complexity of mucositis. As a first step, we searched the literature to identify genes that harbor or are close to the genetic variants significantly associated with mucositis. Our literature review identified 27 candidate genes, of which ERCC1, XRCC1, and MTHFR were the most frequently studied for mucositis. On the basis of this 27-gene list, we used IPA to generate gene networks for mucositis. The most biologically significant novel molecules identified through IPA analyses included TP53, CTNNB1, MYC, RB1, P38 MAPK, and EP300. Additionally, uracil degradation II (reductive) and thymine degradation pathways (p = 1.06-08) were most significant. Finally, utilizing 66 SNPs within the 8 most connected IPA-derived candidate molecules, we conducted a genetic association study for oral mucositis in the head and neck cancer patients who were treated using chemotherapy and/or radiation therapy (186 head and neck cancer patients with oral mucositis vs. 699 head and neck cancer patients without oral mucositis). The top ranked gene identified through this association analysis was RB1 (rs2227311, p-value = 0.034, odds ratio = 0.67). In conclusion, gene network analysis identified novel molecules and biological