Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2015-01-01

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

Identifying marker genes in transcription profiling data using a mixture of feature relevance experts.

PubMed

Chow, M L; Moler, E J; Mian, I S

2001-03-08

Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring. This work proposes a mixture of feature relevance experts as a method for identifying marker genes and illustrates the idea using published data from samples labeled as acute lymphoblastic and myeloid leukemia (ALL, AML). A feature relevance expert implements an algorithm that calculates how well a gene distinguishes samples, reorders genes according to this relevance measure, and uses a supervised learning method [here, support vector machines (SVMs)] to determine the generalization performances of different nested gene subsets. The mixture of three feature relevance experts examined implement two existing and one novel feature relevance measures. For each expert, a gene subset consisting of the top 50 genes distinguished ALL from AML samples as completely as all 7,070 genes. The 125 genes at the union of the top 50s are plausible markers for a prototype decision support system. Chromosomal aberration and other data support the prediction that the three genes at the intersection of the top 50s, cystatin C, azurocidin, and adipsin, are good targets for investigating the basic biology of ALL/AML. The same data were employed to identify markers that distinguish samples based on their labels of T cell/B cell, peripheral blood/bone marrow, and male/female. Selenoprotein W may discriminate T cells from B cells. Results from analysis of transcription profiling data from tumor/nontumor colon adenocarcinoma samples support the general utility of the aforementioned approach. Theoretical issues such as choosing SVM kernels and their parameters, training and evaluating feature relevance experts, and the impact of potentially mislabeled samples on marker identification (feature selection) are discussed.

Robust k-mer frequency estimation using gapped k-mers

PubMed Central

Ghandi, Mahmoud; Mohammad-Noori, Morteza

2013-01-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome. PMID:23861010

Robust k-mer frequency estimation using gapped k-mers.

PubMed

Ghandi, Mahmoud; Mohammad-Noori, Morteza; Beer, Michael A

2014-08-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

Unsupervised Feature Learning With Winner-Takes-All Based STDP

PubMed Central

Ferré, Paul; Mamalet, Franck; Thorpe, Simon J.

2018-01-01

We present a novel strategy for unsupervised feature learning in image applications inspired by the Spike-Timing-Dependent-Plasticity (STDP) biological learning rule. We show equivalence between rank order coding Leaky-Integrate-and-Fire neurons and ReLU artificial neurons when applied to non-temporal data. We apply this to images using rank-order coding, which allows us to perform a full network simulation with a single feed-forward pass using GPU hardware. Next we introduce a binary STDP learning rule compatible with training on batches of images. Two mechanisms to stabilize the training are also presented : a Winner-Takes-All (WTA) framework which selects the most relevant patches to learn from along the spatial dimensions, and a simple feature-wise normalization as homeostatic process. This learning process allows us to train multi-layer architectures of convolutional sparse features. We apply our method to extract features from the MNIST, ETH80, CIFAR-10, and STL-10 datasets and show that these features are relevant for classification. We finally compare these results with several other state of the art unsupervised learning methods. PMID:29674961

Making Biology Relevant to Undergraduates

ERIC Educational Resources Information Center

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…

Examining the impact of question surface features on students' answers to constructed-response questions on photosynthesis.

PubMed

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. © 2015 M. Weston et al. CBE—Life Sciences Education © 2015 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).

DOT2: Macromolecular Docking With Improved Biophysical Models

PubMed Central

Roberts, Victoria A.; Thompson, Elaine E.; Pique, Michael E.; Perez, Martin S.; Eyck, Lynn Ten

2015-01-01

Computational docking is a useful tool for predicting macromolecular complexes, which are often difficult to determine experimentally. Here we present the DOT2 software suite, an updated version of the DOT intermolecular docking program. DOT2 provides straightforward, automated construction of improved biophysical models based on molecular coordinates, offering checkpoints that guide the user to include critical features. DOT has been updated to run more quickly, allow flexibility in grid size and spacing, and generate a complete list of favorable candidate configu-rations. Output can be filtered by experimental data and rescored by the sum of electrostatic and atomic desolvation energies. We show that this rescoring method improves the ranking of correct complexes for a wide range of macromolecular interactions, and demonstrate that biologically relevant models are essential for biologically relevant results. The flexibility and versatility of DOT2 accommodate realistic models of complex biological systems, improving the likelihood of a successful docking outcome. PMID:23695987

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

Applications of Microfluidics in Quantitative Biology.

PubMed

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.

Relevant Features of Science: Values in Conservation Biology

ERIC Educational Resources Information Center

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…

A model of proto-object based saliency

PubMed Central

Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

2013-01-01

Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

Statistical interpretation of machine learning-based feature importance scores for biomarker discovery.

PubMed

Huynh-Thu, Vân Anh; Saeys, Yvan; Wehenkel, Louis; Geurts, Pierre

2012-07-01

Univariate statistical tests are widely used for biomarker discovery in bioinformatics. These procedures are simple, fast and their output is easily interpretable by biologists but they can only identify variables that provide a significant amount of information in isolation from the other variables. As biological processes are expected to involve complex interactions between variables, univariate methods thus potentially miss some informative biomarkers. Variable relevance scores provided by machine learning techniques, however, are potentially able to highlight multivariate interacting effects, but unlike the p-values returned by univariate tests, these relevance scores are usually not statistically interpretable. This lack of interpretability hampers the determination of a relevance threshold for extracting a feature subset from the rankings and also prevents the wide adoption of these methods by practicians. We evaluated several, existing and novel, procedures that extract relevant features from rankings derived from machine learning approaches. These procedures replace the relevance scores with measures that can be interpreted in a statistical way, such as p-values, false discovery rates, or family wise error rates, for which it is easier to determine a significance level. Experiments were performed on several artificial problems as well as on real microarray datasets. Although the methods differ in terms of computing times and the tradeoff, they achieve in terms of false positives and false negatives, some of them greatly help in the extraction of truly relevant biomarkers and should thus be of great practical interest for biologists and physicians. As a side conclusion, our experiments also clearly highlight that using model performance as a criterion for feature selection is often counter-productive. Python source codes of all tested methods, as well as the MATLAB scripts used for data simulation, can be found in the Supplementary Material.

The Role of Competitive Inhibition and Top-Down Feedback in Binding during Object Recognition

PubMed Central

Wyatte, Dean; Herd, Seth; Mingus, Brian; O’Reilly, Randall

2012-01-01

How does the brain bind together visual features that are processed concurrently by different neurons into a unified percept suitable for processes such as object recognition? Here, we describe how simple, commonly accepted principles of neural processing can interact over time to solve the brain’s binding problem. We focus on mechanisms of neural inhibition and top-down feedback. Specifically, we describe how inhibition creates competition among neural populations that code different features, effectively suppressing irrelevant information, and thus minimizing illusory conjunctions. Top-down feedback contributes to binding in a similar manner, but by reinforcing relevant features. Together, inhibition and top-down feedback contribute to a competitive environment that ensures only the most appropriate features are bound together. We demonstrate this overall proposal using a biologically realistic neural model of vision that processes features across a hierarchy of interconnected brain areas. Finally, we argue that temporal synchrony plays only a limited role in binding – it does not simultaneously bind multiple objects, but does aid in creating additional contrast between relevant and irrelevant features. Thus, our overall theory constitutes a solution to the binding problem that relies only on simple neural principles without any binding-specific processes. PMID:22719733

Non-mammalian models in behavioral neuroscience: consequences for biological psychiatry

PubMed Central

Maximino, Caio; Silva, Rhayra Xavier do Carmo; da Silva, Suéllen de Nazaré Santos; Rodrigues, Laís do Socorro dos Santos; Barbosa, Hellen; de Carvalho, Tayana Silva; Leão, Luana Ketlen dos Reis; Lima, Monica Gomes; Oliveira, Karen Renata Matos; Herculano, Anderson Manoel

2015-01-01

Current models in biological psychiatry focus on a handful of model species, and the majority of work relies on data generated in rodents. However, in the same sense that a comparative approach to neuroanatomy allows for the identification of patterns of brain organization, the inclusion of other species and an adoption of comparative viewpoints in behavioral neuroscience could also lead to increases in knowledge relevant to biological psychiatry. Specifically, this approach could help to identify conserved features of brain structure and behavior, as well as to understand how variation in gene expression or developmental trajectories relates to variation in brain and behavior pertinent to psychiatric disorders. To achieve this goal, the current focus on mammalian species must be expanded to include other species, including non-mammalian taxa. In this article, we review behavioral neuroscientific experiments in non-mammalian species, including traditional “model organisms” (zebrafish and Drosophila) as well as in other species which can be used as “reference.” The application of these domains in biological psychiatry and their translational relevance is considered. PMID:26441567

USSR Space Life Sciences Digest, issue 16

NASA Technical Reports Server (NTRS)

Hooke, Lydia Razran (Editor); Teeter, Ronald (Editor); Siegel, Bette (Editor); Donaldson, P. Lynn (Editor); Leveton, Lauren B. (Editor); Rowe, Joseph (Editor)

1988-01-01

This is the sixteenth issue of NASA's USSR Life Sciences Digest. It contains abstracts of 57 papers published in Russian language periodicals or presented at conferences and of 2 new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. An additional feature is the review of a book concerned with metabolic response to the stress of space flight. The abstracts included in this issue are relevant to 33 areas of space biology and medicine. These areas are: adaptation, biological rhythms, bionics, biospherics, body fluids, botany, cardiovascular and respiratory systems, developmental biology, endocrinology, enzymology, exobiology, gastrointestinal system, genetics, gravitational biology, habitability and environmental effects, hematology, human performance, immunology, life support systems, man-machine systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception, personnel selection, psychology, radiobiology, reproductive biology, and space biology.

Aqueous silicates in biological sol-gel applications: new perspectives for old precursors.

PubMed

Coradin, Thibaud; Livage, Jacques

2007-09-01

Identification of silica sol-gel chemistry with silicon alkoxide hydrolysis and condensation processes is common in modern materials science. However, aqueous silicates exhibit several features indicating that they may be more suitable precursors for specific fields of research and applications related to biology and medicine. In this Account, we illustrate the potentialities of such aqueous precursors for biomimetic studies, bio-hybrid material design, and bioencapsulation routes. We emphasize that the natural relevance, the biocompatibility, and the low ecological impact of silicate chemistry may balance its lack of diversity, flexibility, and processability.

Will systems biology offer new holistic paradigms to life sciences?

PubMed Central

Conti, Filippo; Valerio, Maria Cristina; Zbilut, Joseph P.

2008-01-01

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms. PMID:19003440

Endotoxin contamination: a key element in the interpretation of nanosafety studies.

PubMed

Li, Yang; Boraschi, Diana

2016-02-01

The study of toxicity and potential risks of engineered nanoparticles is of particular importance in nanomedicine. Endotoxin, a common contaminant of bacterial origin, has biological effects that can mask the true biological effects of nanoparticles, if its presence is overlooked. In this review, we report the features of nanoparticle contamination by endotoxin, and the different biological effects of endotoxin-contaminated nanoparticles. We will describe different methods for endotoxin detection applied to nanoparticles, and discuss their pros and cons. Eventually, we describe various methods for eliminating endotoxin contamination in nanoparticles. Although there is no universal technique for efficiently removing endotoxin from nanoparticles, specific solutions can be found case by case, which can allow us to perform nanosafety studies in biologically relevant conditions.

The hormesis database: the occurrence of hormetic dose responses in the toxicological literature.

PubMed

Calabrese, Edward J; Blain, Robyn B

2011-10-01

In 2005 we published an assessment of dose responses that satisfied a priori evaluative criteria for inclusion within the relational retrieval hormesis database (Calabrese and Blain, 2005). The database included information on study characteristics (e.g., biological model, gender, age and other relevant aspects, number of doses, dose distribution/range, quantitative features of the dose response, temporal features/repeat measures, and physical/chemical properties of the agents). The 2005 article covered information for about 5000 dose responses; the present article has been expanded to cover approximately 9000 dose responses. This assessment extends and strengthens the conclusion of the 2005 paper that the hormesis concept is broadly generalizable, being independent of biological model, endpoint measured and chemical class/physical agent. It also confirmed the definable quantitative features of hormetic dose responses in which the strong majority of dose responses display maximum stimulation less than twice that of the control group and a stimulatory width that is within approximately 10-20-fold of the estimated toxicological or pharmacological threshold. The remarkable consistency of the quantitative features of the hormetic dose response suggests that hormesis may provide an estimate of biological plasticity that is broadly generalized across plant, microbial and animal (invertebrate and vertebrate) models. Copyright © 2011 Elsevier Inc. All rights reserved.

Analysis of Biological Features Associated with Meiotic Recombination Hot and Cold Spots in Saccharomyces cerevisiae

PubMed Central

Hansen, Loren; Kim, Nak-Kyeong; Mariño-Ramírez, Leonardo; Landsman, David

2011-01-01

Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; and GC content. Previous studies have associated H3K4me3, H3K36me3, and GC content with areas of mitotic recombination. H3K14ac and H3K79me3 are novel predictions and thus represent good candidates for further experimental study. We also show nucleosome occupancy maps produced using next generation sequencing exhibit a bias at DSB hot spots and this bias is strong enough to obscure biologically relevant information. A computational approach using feature selection can productively be used to identify promising biological associations. H3K14ac and H3K79me3 are novel predictions of chromatin marks associated with meiotic DSBs. Next generation sequencing can exhibit a bias that is strong enough to lead to incorrect conclusions. Care must be taken when interpreting high throughput sequencing data where systematic biases have been documented. PMID:22242140

Genetics in the 21st Century: The Benefits & Challenges of Incorporating a Project-Based Genetics Unit in Biology Classrooms

ERIC Educational Resources Information Center

Alozie, Nonye; Eklund, Jennifer; Rogat, Aaron; Krajcik, Joseph

2010-01-01

How can science instruction help students and teachers engage in relevant genetics content that stimulates learning and heightens curiosity? Project-based science can enhance learning and thinking in science classrooms. We describe how we use project-based science features as a framework for a genetics unit, discuss some of the challenges…

Classifying transcription factor targets and discovering relevant biological features

PubMed Central

Holloway, Dustin T; Kon, Mark; DeLisi, Charles

2008-01-01

Background An important goal in post-genomic research is discovering the network of interactions between transcription factors (TFs) and the genes they regulate. We have previously reported the development of a supervised-learning approach to TF target identification, and used it to predict targets of 104 transcription factors in yeast. We now include a new sequence conservation measure, expand our predictions to include 59 new TFs, introduce a web-server, and implement an improved ranking method to reveal the biological features contributing to regulation. The classifiers combine 8 genomic datasets covering a broad range of measurements including sequence conservation, sequence overrepresentation, gene expression, and DNA structural properties. Principal Findings (1) Application of the method yields an amplification of information about yeast regulators. The ratio of total targets to previously known targets is greater than 2 for 11 TFs, with several having larger gains: Ash1(4), Ino2(2.6), Yaf1(2.4), and Yap6(2.4). (2) Many predicted targets for TFs match well with the known biology of their regulators. As a case study we discuss the regulator Swi6, presenting evidence that it may be important in the DNA damage response, and that the previously uncharacterized gene YMR279C plays a role in DNA damage response and perhaps in cell-cycle progression. (3) A procedure based on recursive-feature-elimination is able to uncover from the large initial data sets those features that best distinguish targets for any TF, providing clues relevant to its biology. An analysis of Swi6 suggests a possible role in lipid metabolism, and more specifically in metabolism of ceramide, a bioactive lipid currently being investigated for anti-cancer properties. (4) An analysis of global network properties highlights the transcriptional network hubs; the factors which control the most genes and the genes which are bound by the largest set of regulators. Cell-cycle and growth related regulators dominate the former; genes involved in carbon metabolism and energy generation dominate the latter. Conclusion Postprocessing of regulatory-classifier results can provide high quality predictions, and feature ranking strategies can deliver insight into the regulatory functions of TFs. Predictions are available at an online web-server, including the full transcriptional network, which can be analyzed using VisAnt network analysis suite. Reviewers This article was reviewed by Igor Jouline, Todd Mockler(nominated by Valerian Dolja), and Sandor Pongor. PMID:18513408

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

PubMed

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.

USSR Space Life Sciences Digest, issue 15

NASA Technical Reports Server (NTRS)

Hooke, Lydia Razran (Editor); Teeter, Ronald (Editor); Garshnek, Victoria (Editor); Rowe, Joseph (Editor)

1988-01-01

This is the 15th issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 59 papers published in Russian language periodicals or presented at conferences and of two new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. An additional feature is a review of a conference devoted to the physiology of extreme states. The abstracts included in this issue have been identified as relevant to 29 areas of space biology and medicine. These areas are adaptation, biological rhythms, biospherics, body fluids, botany, cardiovascular and respiratory systems, endocrinology, enzymology, equipment and instrumentation, exobiology, genetics, habitability and environment effects, human performance, immunology, life support systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception. personnel selection, psychology, radiobiology, reproductive biology, and space biology and medicine.

Environmental chemicals and breast cancer: An updated review of epidemiological literature informed by biological mechanisms.

PubMed

Rodgers, Kathryn M; Udesky, Julia O; Rudel, Ruthann A; Brody, Julia Green

2018-01-01

Many common environmental chemicals are mammary gland carcinogens in animal studies, activate relevant hormonal pathways, or enhance mammary gland susceptibility to carcinogenesis. Breast cancer's long latency and multifactorial etiology make evaluation of these chemicals in humans challenging. For chemicals previously identified as mammary gland toxicants, we evaluated epidemiologic studies published since our 2007 review. We assessed whether study designs captured relevant exposures and disease features suggested by toxicological and biological evidence of genotoxicity, endocrine disruption, tumor promotion, or disruption of mammary gland development. We systematically searched the PubMed database for articles with breast cancer outcomes published in 2006-2016 using terms for 134 environmental chemicals, sources, or biomarkers of exposure. We critically reviewed the articles. We identified 158 articles. Consistent with experimental evidence, a few key studies suggested higher risk for exposures during breast development to dichlorodiphenyltrichloroethane (DDT), dioxins, perfluorooctane-sulfonamide (PFOSA), and air pollution (risk estimates ranged from 2.14 to 5.0), and for occupational exposure to solvents and other mammary carcinogens, such as gasoline components (risk estimates ranged from 1.42 to 3.31). Notably, one 50-year cohort study captured exposure to DDT during several critical windows for breast development (in utero, adolescence, pregnancy) and when this chemical was still in use. Most other studies did not assess exposure during a biologically relevant window or specify the timing of exposure. Few studies considered genetic variation, but the Long Island Breast Cancer Study Project reported higher breast cancer risk for polycyclic aromatic hydrocarbons (PAHs) in women with certain genetic variations, especially in DNA repair genes. New studies that targeted toxicologically relevant chemicals and captured biological hypotheses about genetic variants or windows of breast susceptibility added to evidence of links between environmental chemicals and breast cancer. However, many biologically relevant chemicals, including current-use consumer product chemicals, have not been adequately studied in humans. Studies are challenged to reconstruct exposures that occurred decades before diagnosis or access biological samples stored that long. Other problems include measuring rapidly metabolized chemicals and evaluating exposure to mixtures. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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.

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

PubMed Central

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

2015-01-01

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. PMID:25678986

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

PubMed

Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

2018-05-01

This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

Font size matters--emotion and attention in cortical responses to written words.

PubMed

Bayer, Mareike; Sommer, Werner; Schacht, Annekathrin

2012-01-01

For emotional pictures with fear-, disgust-, or sex-related contents, stimulus size has been shown to increase emotion effects in attention-related event-related potentials (ERPs), presumably reflecting the enhanced biological impact of larger emotion-inducing pictures. If this is true, size should not enhance emotion effects for written words with symbolic and acquired meaning. Here, we investigated ERP effects of font size for emotional and neutral words. While P1 and N1 amplitudes were not affected by emotion, the early posterior negativity started earlier and lasted longer for large relative to small words. These results suggest that emotion-driven facilitation of attention is not necessarily based on biological relevance, but might generalize to stimuli with arbitrary perceptual features. This finding points to the high relevance of written language in today's society as an important source of emotional meaning.

Medicinal Chemical Properties of Successful Central Nervous System Drugs

PubMed Central

Pajouhesh, Hassan; Lenz, George R.

2005-01-01

Summary: Fundamental physiochemical features of CNS drugs are related to their ability to penetrate the blood-brain barrier affinity and exhibit CNS activity. Factors relevant to the success of CNS drugs are reviewed. CNS drugs show values of molecular weight, lipophilicity, and hydrogen bond donor and acceptor that in general have a smaller range than general therapeutics. Pharmacokinetic properties can be manipulated by the medicinal chemist to a significant extent. The solubility, permeability, metabolic stability, protein binding, and human ether-ago-go-related gene inhibition of CNS compounds need to be optimized simultaneously with potency, selectivity, and other biological parameters. The balance between optimizing the physiochemical and pharmacokinetic properties to make the best compromises in properties is critical for designing new drugs likely to penetrate the blood brain barrier and affect relevant biological systems. This review is intended as a guide to designing CNS therapeutic agents with better drug-like properties. PMID:16489364

Alternate Metabolic Programs Define Regional Variation of Relevant Biological Features in Renal Cell Carcinoma Progression.

PubMed

Brooks, Samira A; Khandani, Amir H; Fielding, Julia R; Lin, Weili; Sills, Tiffany; Lee, Yueh; Arreola, Alexandra; Milowsky, Mathew I; Wallen, Eric M; Woods, Michael E; Smith, Angie B; Nielsen, Mathew E; Parker, Joel S; Lalush, David S; Rathmell, W Kimryn

2016-06-15

Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans. ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis. Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA- and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype. Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease. Clin Cancer Res; 22(12); 2950-9. ©2016 AACR. ©2016 American Association for Cancer Research.

PDC-SGB: Prediction of effective drug combinations using a stochastic gradient boosting algorithm.

PubMed

Xu, Qian; Xiong, Yi; Dai, Hao; Kumari, Kotni Meena; Xu, Qin; Ou, Hong-Yu; Wei, Dong-Qing

2017-03-21

Combinatorial therapy is a promising strategy for combating complex diseases by improving the efficacy and reducing the side effects. To facilitate the identification of drug combinations in pharmacology, we proposed a new computational model, termed PDC-SGB, to predict effective drug combinations by integrating biological, chemical and pharmacological information based on a stochastic gradient boosting algorithm. To begin with, a set of 352 golden positive samples were collected from the public drug combination database. Then, a set of 732 dimensional feature vector involving biological, chemical and pharmaceutical information was constructed for each drug combination to describe its properties. To avoid overfitting, the maximum relevance & minimum redundancy (mRMR) method was performed to extract useful ones by removing redundant subsets. Based on the selected features, the three different type of classification algorithms were employed to build the drug combination prediction models. Our results demonstrated that the model based on the stochastic gradient boosting algorithm yield out the best performance. Furthermore, it is indicated that the feature patterns of therapy had powerful ability to discriminate effective drug combinations from non-effective ones. By analyzing various features, it is shown that the enriched features occurred frequently in golden positive samples can help predict novel drug combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity.

PubMed

Wagner, Andreas

2014-02-18

Novel phenotypes can originate either through mutations in existing genotypes or through phenotypic plasticity, the ability of one genotype to form multiple phenotypes. From molecules to organisms, plasticity is a ubiquitous feature of life, and a potential source of exaptations, adaptive traits that originated for nonadaptive reasons. Another ubiquitous feature is robustness to mutations, although it is unknown whether such robustness helps or hinders the origin of new phenotypes through plasticity. RNA is ideal to address this question, because it shows extensive plasticity in its secondary structure phenotypes, a consequence of their continual folding and unfolding, and these phenotypes have important biological functions. Moreover, RNA is to some extent robust to mutations. This robustness structures RNA genotype space into myriad connected networks of genotypes with the same phenotype, and it influences the dynamics of evolving populations on a genotype network. In this study I show that both effects help accelerate the exploration of novel phenotypes through plasticity. My observations are based on many RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules. They are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolution of biological RNA. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

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

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

PubMed

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.

Chemical warfare agents. Classes and targets.

PubMed

Schwenk, Michael

2018-09-01

Synthetic toxic chemicals (toxicants) and biological poisons (toxins) have been developed as chemical warfare agents in the last century. At the time of their initial consideration as chemical weapon, only restricted knowledge existed about their mechanisms of action. There exist two different types of acute toxic action: nonspecific cytotoxic mechanisms with multiple chemo-biological interactions versus specific mechanisms that tend to have just a single or a few target biomolecules. TRPV1- and TRPA-receptors are often involved as chemosensors that induce neurogenic inflammation. The present work briefly surveys classes and toxicologically relevant features of chemical warfare agents and describes mechanisms of toxic action. Copyright © 2017 Elsevier B.V. All rights reserved.

Antimalarial activity of synthetic 1,2,4-trioxanes and cyclic peroxy ketals, a quantum similarity study

NASA Astrophysics Data System (ADS)

Gironés, X.; Gallegos, A.; Carbó-Dorca, R.

2001-12-01

In this work, the antimalarial activity of two series of 20 and 7 synthetic 1,2,4-trioxanes and a set of 20 cyclic peroxy ketals are tested for correlation search by means of Molecular Quantum Similarity Measures (MQSM). QSAR models, dealing with different biological responses (IC90, IC50 and ED90) of the parasite Plasmodium Falciparum, are constructed using MQSM as molecular descriptors and are satisfactorily correlated. The statistical results of the 20 1,2,4-trioxanes are deeply analyzed to elucidate the relevant structural features in the biological activity, revealing the importance of phenyl substitutions.

Texture sensing of cytoskeletal dynamics in cell migration

NASA Astrophysics Data System (ADS)

Das, Satarupa; Lee, Rachel; Hourwitz, Matthew J.; Sun, Xiaoyu; Parent, Carole; Fourkas, John T.; Losert, Wolfgang

Migrating cells can be directed towards a target by gradients in properties such as chemical concentration or mechanical properties of the surrounding microenvironment. In previous studies we have shown that micro/nanotopographical features on scales comparable to those of natural collagen fibers can guide fast migrating amoeboid cells by aligning actin polymerization waves to such nanostructures. We find that actin microfilaments and microtubules are aligned along the nanoridge topographies, modulating overall cell polarity and directional migration in epithelial cells. This work shows that topographic features on a biologically relevant length scale can modulate migration outcomes by affecting the texture sensing property of the cytoskeleton.

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

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

USGS Publications Warehouse

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.

Thalamic neuron models encode stimulus information by burst-size modulation

PubMed Central

Elijah, Daniel H.; Samengo, Inés; Montemurro, Marcelo A.

2015-01-01

Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons. PMID:26441623

Wurfelspiel-based training data methods for ATR

NASA Astrophysics Data System (ADS)

Peterson, James K.

2004-09-01

A data object is constructed from a P by M Wurfelspiel matrix W by choosing an entry from each column to construct a sequence A0A1"AM-1. Each of the PM possibilities are designed to correspond to the same category according to some chosen measure. This matrix could encode many types of data. (1) Musical fragments, all of which evoke sadness; each column entry is a 4 beat sequence with a chosen A0A1A2 thus 16 beats long (W is P by 3). (2) Paintings, all of which evoke happiness; each column entry is a layer and a given A0A1A2 is a painting constructed using these layers (W is P by 3). (3) abstract feature vectors corresponding to action potentials evoked from a biological cell's exposure to a toxin. The action potential is divided into four relevant regions and each column entry represents the feature vector of a region. A given A0A1A2 is then an abstraction of the excitable cell's output (W is P by 4). (4) abstract feature vectors corresponding to an object such as a face or vehicle. The object is divided into four categories each assigned an abstract feature vector with the resulting concatenation an abstract representation of the object (W is P by 4). All of the examples above correspond to one particular measure (sad music, happy paintings, an introduced toxin, an object to recognize)and hence, when a Wurfelspiel matrix is constructed, relevant training information for recognition is encoded that can be used in many algorithms. The focus of this paper is on the application of these ideas to automatic target recognition (ATR). In addition, we discuss a larger biologically based model of temporal cortex polymodal sensor fusion which can use the feature vectors extracted from the ATR Wurfelspiel data.

Thalamic neuron models encode stimulus information by burst-size modulation.

PubMed

Elijah, Daniel H; Samengo, Inés; Montemurro, Marcelo A

2015-01-01

Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons.

USSR Space Life Sciences Digest, Issue 10

NASA Technical Reports Server (NTRS)

Hooke, Lydia Razran; Radtke, Mike; Teeter, Ronald; Garshnek, Victoria; Rowe, Joseph E.

1987-01-01

The USSR Space Life Sciences Digest contains abstracts of 37 papers recently published in Russian language periodicals and bound collections and of five new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. Additional features include the translation of a book chapter concerning use of biological rhythms as a basis for cosmonaut selection, excerpts from the diary of a participant in a long-term isolation experiment, and a picture and description of the Mir space station. The abstracts included in this issue were identified as relevant to 25 areas of aerospace medicine and space biology. These areas are adaptation, biological rhythms, biospherics, body fluids, botany, cardiovascular and respiratory systems, developmental biology, endocrinology, enzymology, group dynamics, habitability and environmental effects, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism, microbiology, morphology and cytology, musculosketal system, neurophysiology, nutrition, personnel selection, psychology, and radiobiology.

Hierarchical ensemble of global and local classifiers for face recognition.

PubMed

Su, Yu; Shan, Shiguang; Chen, Xilin; Gao, Wen

2009-08-01

In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper proposes a novel face recognition method which exploits both global and local discriminative features. In this method, global features are extracted from the whole face images by keeping the low-frequency coefficients of Fourier transform, which we believe encodes the holistic facial information, such as facial contour. For local feature extraction, Gabor wavelets are exploited considering their biological relevance. After that, Fisher's linear discriminant (FLD) is separately applied to the global Fourier features and each local patch of Gabor features. Thus, multiple FLD classifiers are obtained, each embodying different facial evidences for face recognition. Finally, all these classifiers are combined to form a hierarchical ensemble classifier. We evaluate the proposed method using two large-scale face databases: FERET and FRGC version 2.0. Experiments show that the results of our method are impressively better than the best known results with the same evaluation protocol.

The PLOS ONE Synthetic Biology Collection: Six Years and Counting

PubMed Central

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

The PLOS ONE synthetic biology collection: six years and counting.

PubMed

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.

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

PubMed

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.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

AN OVERVIEW OF COMPUTATIONAL LIFE SCIENCE DATABASES & EXCHANGE FORMATS OF RELEVANCE TO CHEMICAL BIOLOGY RESEARCH

PubMed Central

Hall, Aaron Smalter; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2016-01-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities. PMID:22934944

Biosimilars in inflammatory bowel disease: A review of post-marketing experience.

PubMed

Deiana, Simona; Gabbani, Tommaso; Annese, Vito

2017-01-14

Biologic compounds are obtained from living organisms or cell cultures by means of biotechnology methods. A similar biologic drug, commonly called biosimilar, is a product copied by a native approved biologic drug whose license has expired. Biosimilar drugs usually are marketed at a lower price and provide important financial savings for public healthcare systems. Some differences between biosimilars and original biologic drugs might exist but they are acceptable if they fall within defined "boundaries of tolerance": differences in some features between the two molecules are considered important only if clinical relevant. Considering that the efficacy of the innovator biologic drug has already been established, the clinical studies required for approval of a biosimilar could be reduced compared with those required for the approval of the originator. In this review, real life data available in inflammatory bowel disease patients treated with biosimilars are reported, documenting in general satisfactory outcomes, sustained efficacy and no sign of increased immunogenicity, although, further controlled data are awaited.

An overview of computational life science databases & exchange formats of relevance to chemical biology research.

PubMed

Smalter Hall, Aaron; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2013-03-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

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

PubMed

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.

Dentin Hypersensitivity: Etiology, Diagnosis and Treatment; A Literature Review

PubMed Central

Davari, AR; Ataei, E; Assarzadeh, H

2013-01-01

The objective of this review is to inform practitioners about dentin hypersensitivity (DH); to provide a brief overview of the diagnosis, etiology and clinical management of dentin hypersensitivity and to discuss technical approaches to relieve sensitivity. This clinical information is described in the context of the underlying biology. The author used PUBMED to find relevant English-language literature published in the period 1999 to 2010. The author used combinations of the search terms “dentin*”, “tooth”, “teeth”, “hypersensit*”, “desensitiz*”. Abstracts and also full text articles to identify studies describing etiology, prevalence, clinical features, controlled clinical trials of treatments and relevant laboratory research on mechanisms of action were used. PMID:24724135

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

PubMed

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

2005-06-01

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

Low Frequency Variants, Collapsed Based on Biological Knowledge, Uncover Complexity of Population Stratification in 1000 Genomes Project Data

PubMed Central

Moore, Carrie B.; Wallace, John R.; Wolfe, Daniel J.; Frase, Alex T.; Pendergrass, Sarah A.; Weiss, Kenneth M.; Ritchie, Marylyn D.

2013-01-01

Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project. Our flexible collapsing tool utilizes expert biological knowledge from multiple publicly available database sources to direct feature selection. Variants were collapsed according to genetically driven features, such as evolutionary conserved regions, regulatory regions genes, and pathways. We have conducted an extensive comparison of low frequency variant burden differences (MAF<0.03) between populations from 1000 Genomes Project Phase I data. We found that on average 26.87% of gene bins, 35.47% of intergenic bins, 42.85% of pathway bins, 14.86% of ORegAnno regulatory bins, and 5.97% of evolutionary conserved regions show statistically significant differences in low frequency variant burden across populations from the 1000 Genomes Project. The proportion of bins with significant differences in low frequency burden depends on the ancestral similarity of the two populations compared and types of features tested. Even closely related populations had notable differences in low frequency burden, but fewer differences than populations from different continents. Furthermore, conserved or functionally relevant regions had fewer significant differences in low frequency burden than regions under less evolutionary constraint. This degree of low frequency variant differentiation across diverse populations and feature elements highlights the critical importance of considering population stratification in the new era of DNA sequencing and low frequency variant genomic analyses. PMID:24385916

Mining the modular structure of protein interaction networks.

PubMed

Berenstein, Ariel José; Piñero, Janet; Furlong, Laura Inés; Chernomoretz, Ariel

2015-01-01

Cluster-based descriptions of biological networks have received much attention in recent years fostered by accumulated evidence of the existence of meaningful correlations between topological network clusters and biological functional modules. Several well-performing clustering algorithms exist to infer topological network partitions. However, due to respective technical idiosyncrasies they might produce dissimilar modular decompositions of a given network. In this contribution, we aimed to analyze how alternative modular descriptions could condition the outcome of follow-up network biology analysis. We considered a human protein interaction network and two paradigmatic cluster recognition algorithms, namely: the Clauset-Newman-Moore and the infomap procedures. We analyzed to what extent both methodologies yielded different results in terms of granularity and biological congruency. In addition, taking into account Guimera's cartographic role characterization of network nodes, we explored how the adoption of a given clustering methodology impinged on the ability to highlight relevant network meso-scale connectivity patterns. As a case study we considered a set of aging related proteins and showed that only the high-resolution modular description provided by infomap, could unveil statistically significant associations between them and inter/intra modular cartographic features. Besides reporting novel biological insights that could be gained from the discovered associations, our contribution warns against possible technical concerns that might affect the tools used to mine for interaction patterns in network biology studies. In particular our results suggested that sub-optimal partitions from the strict point of view of their modularity levels might still be worth being analyzed when meso-scale features were to be explored in connection with external source of biological knowledge.

LS-SNP/PDB: annotated non-synonymous SNPs mapped to Protein Data Bank structures.

PubMed

Ryan, Michael; Diekhans, Mark; Lien, Stephanie; Liu, Yun; Karchin, Rachel

2009-06-01

LS-SNP/PDB is a new WWW resource for genome-wide annotation of human non-synonymous (amino acid changing) SNPs. It serves high-quality protein graphics rendered with UCSF Chimera molecular visualization software. The system is kept up-to-date by an automated, high-throughput build pipeline that systematically maps human nsSNPs onto Protein Data Bank structures and annotates several biologically relevant features. LS-SNP/PDB is available at (http://ls-snp.icm.jhu.edu/ls-snp-pdb) and via links from protein data bank (PDB) biology and chemistry tabs, UCSC Genome Browser Gene Details and SNP Details pages and PharmGKB Gene Variants Downloads/Cross-References pages.

Practical Radiobiology for Proton Therapy Planning

NASA Astrophysics Data System (ADS)

Jones, Bleddyn

2017-12-01

Practical Radiobiology for Proton Therapy Planning covers the principles, advantages and potential pitfalls that occur in proton therapy, especially its radiobiological modelling applications. This book is intended to educate, inform and to stimulate further research questions. Additionally, it will help proton therapy centres when designing new treatments or when unintended errors or delays occur. The clear descriptions of useful equations for high LET particle beam applications, worked examples of many important clinical situations, and discussion of how proton therapy may be optimized are all important features of the text. This important book blends the relevant physics, biology and medical aspects of this multidisciplinary subject. Part of Series in Physics and Engineering in Medicine and Biology.

Using cell structures to develop functional nanomaterials and nanostructures--case studies of actin filaments and microtubules.

PubMed

Wu, Kevin Chia-Wen; Yang, Chung-Yao; Cheng, Chao-Min

2014-04-25

This article is based on the continued development of biologically relevant elements (i.e., actin filaments and microtubules in living cells) as building blocks to create functional nanomaterials and nanostructures that can then be used to manufacture nature-inspired small-scale devices or systems. Here, we summarize current progress in the field and focus specifically on processes characterized by (1) robustness and ease of use, (2) inexpensiveness, and (3) potential expandability to mass production. This article, we believe, will provide scientists and engineers with a more comprehensive understanding of how to mine biological materials and natural design features to construct functional materials and devices.

Biological and functional relevance of CASP predictions

PubMed Central

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

2017-01-01

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

A visualization tool to support decision making in environmental and biological planning

USGS Publications Warehouse

Romañach, Stephanie S.; McKelvy, James M.; Conzelmann, Craig; Suir, Kevin J.

2014-01-01

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

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

PubMed

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-term experience shapes this adaptive process wherein the top-down connections provide selective gating of inputs to both cortical and subcortical structures to enhance neural responses to specific behaviorally-relevant attributes of the stimulus. A theoretical framework for a neural network is proposed involving coordination between local, feedforward, and feedback components that can account for experience-dependent enhancement of pitch representations at multiple levels of the auditory pathway. The ability to record brainstem and cortical pitch relevant responses concurrently may provide a new window to evaluate the online interplay between feedback, feedforward, and local intrinsic components in the hierarchical processing of pitch relevant information.

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

PubMed Central

Krishnan, Ananthanarayan; Gandour, Jackson T.

2015-01-01

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-term experience shapes this adaptive process wherein the top-down connections provide selective gating of inputs to both cortical and subcortical structures to enhance neural responses to specific behaviorally-relevant attributes of the stimulus. A theoretical framework for a neural network is proposed involving coordination between local, feedforward, and feedback components that can account for experience-dependent enhancement of pitch representations at multiple levels of the auditory pathway. The ability to record brainstem and cortical pitch relevant responses concurrently may provide a new window to evaluate the online interplay between feedback, feedforward, and local intrinsic components in the hierarchical processing of pitch relevant information. PMID:25838636

USSR Space Life Sciences Digest, issue 6

NASA Technical Reports Server (NTRS)

Hooke, L. R. (Editor); Radtke, M. (Editor); Teeter, R. (Editor); Rowe, J. E. (Editor)

1986-01-01

This is the sixth issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 54 papers recently published in Russian language periodicals and bound collections and of 10 new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. Additional features include a table of Soviet EVAs and information about English translations of Soviet materials available to readers. The topics covered in this issue have been identified as relevant to 26 areas of aerospace medicine and space biology. These areas are adaptation, biospherics, body fluids, botany, cardiovascular and respiratory systems, developmental biology, endocrinology, enzymology, exobiology, genetics, habitability and environment effects, health and medical treatment, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism., microbiology, morphology and cytology, musculoskeletal system, neurophysiology, nutrition, perception, personnel selection, psychology, radiobiology, reproductive biology, and space medicine.

Predicting clinical outcome of neuroblastoma patients using an integrative network-based approach.

PubMed

Tranchevent, Léon-Charles; Nazarov, Petr V; Kaoma, Tony; Schmartz, Georges P; Muller, Arnaud; Kim, Sang-Yoon; Rajapakse, Jagath C; Azuaje, Francisco

2018-06-07

One of the main current challenges in computational biology is to make sense of the huge amounts of multidimensional experimental data that are being produced. For instance, large cohorts of patients are often screened using different high-throughput technologies, effectively producing multiple patient-specific molecular profiles for hundreds or thousands of patients. We propose and implement a network-based method that integrates such patient omics data into Patient Similarity Networks. Topological features derived from these networks were then used to predict relevant clinical features. As part of the 2017 CAMDA challenge, we have successfully applied this strategy to a neuroblastoma dataset, consisting of genomic and transcriptomic data. In particular, we observe that models built on our network-based approach perform at least as well as state of the art models. We furthermore explore the effectiveness of various topological features and observe, for instance, that redundant centrality metrics can be combined to build more powerful models. We demonstrate that the networks inferred from omics data contain clinically relevant information and that patient clinical outcomes can be predicted using only network topological data. This article was reviewed by Yang-Yu Liu, Tomislav Smuc and Isabel Nepomuceno.

Learning to attend: modeling the shaping of selectivity in infero-temporal cortex in a categorization task.

PubMed

Szabo, Miruna; Deco, Gustavo; Fusi, Stefano; Del Giudice, Paolo; Mattia, Maurizio; Stetter, Martin

2006-05-01

Recent experiments on behaving monkeys have shown that learning a visual categorization task makes the neurons in infero-temporal cortex (ITC) more selective to the task-relevant features of the stimuli (Sigala and Logothetis in Nature 415 318-320, 2002). We hypothesize that such a selectivity modulation emerges from the interaction between ITC and other cortical area, presumably the prefrontal cortex (PFC), where the previously learned stimulus categories are encoded. We propose a biologically inspired model of excitatory and inhibitory spiking neurons with plastic synapses, modified according to a reward based Hebbian learning rule, to explain the experimental results and test the validity of our hypothesis. We assume that the ITC neurons, receiving feature selective inputs, form stronger connections with the category specific neurons to which they are consistently associated in rewarded trials. After learning, the top-down influence of PFC neurons enhances the selectivity of the ITC neurons encoding the behaviorally relevant features of the stimuli, as observed in the experiments. We conclude that the perceptual representation in visual areas like ITC can be strongly affected by the interaction with other areas which are devoted to higher cognitive functions.

CCProf: exploring conformational change profile of proteins

PubMed Central

Chang, Che-Wei; Chou, Chai-Wei; Chang, Darby Tien-Hao

2016-01-01

In many biological processes, proteins have important interactions with various molecules such as proteins, ions or ligands. Many proteins undergo conformational changes upon these interactions, where regions with large conformational changes are critical to the interactions. This work presents the CCProf platform, which provides conformational changes of entire proteins, named conformational change profile (CCP) in the context. CCProf aims to be a platform where users can study potential causes of novel conformational changes. It provides 10 biological features, including conformational change, potential binding target site, secondary structure, conservation, disorder propensity, hydropathy propensity, sequence domain, structural domain, phosphorylation site and catalytic site. All these information are integrated into a well-aligned view, so that researchers can capture important relevance between different biological features visually. The CCProf contains 986 187 protein structure pairs for 3123 proteins. In addition, CCProf provides a 3D view in which users can see the protein structures before and after conformational changes as well as binding targets that induce conformational changes. All information (e.g. CCP, binding targets and protein structures) shown in CCProf, including intermediate data are available for download to expedite further analyses. Database URL: http://zoro.ee.ncku.edu.tw/ccprof/ PMID:27016699

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

PubMed Central

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

2010-01-01

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

An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

PubMed

Nandi, Sutanu; Subramanian, Abhishek; Sarkar, Ram Rup

2017-07-25

Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.

Biomarker-driven phenotyping in Parkinson disease: a translational missing link in disease-modifying clinical trials

PubMed Central

Espay, Alberto J.; Schwarzschild, Michael A.; Tanner, Caroline M.; Fernandez, Hubert H; Simon, David K.; Leverenz, James B.; Merola, Aristide; Chen-Plotkin, Alice; Brundin, Patrik; Kauffman, Marcelo A.; Erro, Roberto; Kieburtz, Karl; Woo, Daniel; Macklin, Eric A.; Standaert, David G.; Lang, Anthony E.

2016-01-01

Past clinical trials of putative neuroprotective therapies have targeted Parkinson disease (PD) as a single pathogenic disease entity. From an Oslerian clinico-pathologic perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: a single-mechanism therapy can affect most of those sharing the classic pathologic hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers) rather than clinical definitions are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller but well-defined subsets of PD amenable to successful neuroprotection. PMID:28233927

Tracking tumor biology with radiomics: A systematic review utilizing a radiomics quality score.

PubMed

Sanduleanu, Sebastian; Woodruff, Henry C; de Jong, Evelyn E C; van Timmeren, Janna E; Jochems, Arthur; Dubois, Ludwig; Lambin, Philippe

2018-05-18

In this review we describe recent developments in the field of radiomics along with current relevant literature linking it to tumor biology. We furthermore explore the methodologic quality of these studies with our in-house radiomics quality scoring (RQS) tool. Finally, we offer our vision on necessary future steps for the development of stable radiomic features and their links to tumor biology. Two authors (S.S. and H.W.) independently performed a thorough systematic literature search and outcome extraction to identify relevant studies published in MEDLINE/PubMed (National Center for Biotechnology Information, NCBI), EMBASE (Ovid) and Web of Science (WoS). Two authors (S.S, H.W) separately and two authors (J.v.T and E.d.J) concordantly scored the articles for their methodology and analyses according to the previously published radiomics quality score (RQS). In summary, a total of 655 records were identified till 25-09-2017 based on the previously specified search terms, from which n = 236 in MEDLINE/PubMed, n = 215 in EMBASE and n = 204 from Web of Science. After determining full article availability and reading the available articles, a total of n = 41 studies were included in the systematic review. The RQS scoring resulted in some discrepancies between the reviewers, e.g. reviewer H.W scored 4 studies ≥50%, reviewer S.S scored 3 studies ≥50% while reviewers J.v.T and E.d.J scored 1 study ≥50%. Up to nine studies were given a quality score of 0%. The majority of studies were scored below 50%. In this study, we performed a systematic literature search linking radiomics to tumor biology. All but two studies (n = 39) revealed that radiomic features derived from ultrasound, CT, PET and/or MR are significantly associated with one or several specific tumor biologic substrates, from somatic mutation status to tumor histopathologic grading and metabolism. Considerable inter-observer differences were found with regard to RQS scoring, while important questions were raised concerning the interpretability of the outcome of such scores. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.

How causal analysis can reveal autonomy in models of biological systems

NASA Astrophysics Data System (ADS)

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'.

USSR Space Life Sciences Digest, issue 8

NASA Technical Reports Server (NTRS)

Hooke, L. R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor)

1985-01-01

This is the eighth issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 48 papers recently published in Russian language periodicals and bound collections and of 10 new Soviet monographs. Selected abstracts are illustrated with figures and tables. Additional features include reviews of two Russian books on radiobiology and a description of the latest meeting of an international working group on remote sensing of the Earth. Information about English translations of Soviet materials available to readers is provided. The topics covered in this issue have been identified as relevant to 33 areas of aerospace medicine and space biology. These areas are: adaptation, biological rhythms, biospherics, body fluids, botany, cardiovascular and respiratory systems, cosmonaut training, cytology, endocrinology, enzymology, equipment and instrumentation, exobiology, gastrointestinal system, genetics, group dynamics, habitability and environment effects, hematology, human performance, immunology, life support systems, man-machine systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, personnel selection, psychology, reproductive biology, and space biology and medicine.

Assessing the relevance of ecotoxicological studies for regulatory decision making.

PubMed

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 aspects also need to be considered by scientists when designing, performing, and reporting ecotoxicological studies to facilitate their use in ERA. Integr Environ Assess Manag 2017;13:652-663. © 2016 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2016 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Relevance of and New Developments in Serology for Toxoplasmosis.

PubMed

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.

Mechanical Properties and Failure of Biopolymers: Atomistic Reactions to Macroscale Response

PubMed Central

Jung, GangSeob; Qin, Zhao

2017-01-01

The behavior of chemical bonding under various mechanical loadings is an intriguing mechanochemical property of biological materials, and the property plays a critical role in determining their deformation and failure mechanisms. Because of their astonishing mechanical properties and roles in constituting the basis of a variety of physiologically relevant materials, biological protein materials have been intensively studied. Understanding the relation between chemical bond networks (structures) and their mechanical properties offers great possibilities to enable new materials design in nanotechnology and new medical treatments for human diseases. Here we focus on how the chemical bonds in biological systems affect mechanical properties and how they change during mechanical deformation and failure. Three representative cases of biomaterials related to the human diseases are discussed in case studies, including: amyloids, intermediate filaments, and collagen, each describing mechanochemical features and how they relate to the pathological conditions at multiple scales. PMID:26108895

Utilizing population variation, vaccination, and systems biology to study human immunology

PubMed Central

Tsang, John S.

2016-01-01

The move toward precision medicine has highlighted the importance of understanding biological variability within and across individuals in the human population. In particular, given the prevalent involvement of the immune system in diverse pathologies, an important question is how much and what information about the state of the immune system is required to enable accurate prediction of future health and response to medical interventions. Towards addressing this question, recent studies using vaccination as a model perturbation and systems-biology approaches are beginning to provide a glimpse of how natural population variation together with multiplexed, high-throughput measurement and computational analysis can be used to uncover predictors of immune response quality in humans. Here I discuss recent developments in this emerging field, with emphasis on baseline correlates of vaccination responses, sources of immune-state variability, as well as relevant features of study design, data generation, and computational analysis. PMID:26187853

USSR Space Life Sciences Digest, issue 11

NASA Technical Reports Server (NTRS)

Hooke, Lydia Razran (Editor); Radtke, Mike (Editor); Radtke, Mike (Editor); Radtke, Mike (Editor); Radtke, Mike (Editor); Radtke, Mike (Editor)

1987-01-01

This is the eleventh issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 54 papers recently published in Russian language periodicals and bound collections and of four new Soviet monographs. Selected abstracts are illustrated. Additional features include the translation of a paper presented in Russian to the United Nations, a review of a book on space ecology, and report of a conference on evaluating human functional capacities and predicting health. Current Soviet Life Sciences titles available in English are cited. The materials included in this issue have been identified as relevant to 30 areas of aerospace medicine and space biology. These areas are: adaptation, aviation physiology, biological rhythms, biospherics, body fluids, botany, cardiovascular and respiratory systems, cosmonaut training, developmental biology, endocrinology, enzymology, equipment and instrumentation, gastrointestinal systems, group dynamics, genetics, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception, personnel selection, psychology, and radiobiology.

Impaired visual recognition of biological motion in schizophrenia.

PubMed

Kim, Jejoong; Doop, Mikisha L; Blake, Randolph; Park, Sohee

2005-09-15

Motion perception deficits have been suggested to be an important feature of schizophrenia but the behavioral consequences of such deficits are unknown. Biological motion refers to the movements generated by living beings. The human visual system rapidly and effortlessly detects and extracts socially relevant information from biological motion. A deficit in biological motion perception may have significant consequences for detecting and interpreting social information. Schizophrenia patients and matched healthy controls were tested on two visual tasks: recognition of human activity portrayed in point-light animations (biological motion task) and a perceptual control task involving detection of a grouped figure against the background noise (global-form task). Both tasks required detection of a global form against background noise but only the biological motion task required the extraction of motion-related information. Schizophrenia patients performed as well as the controls in the global-form task, but were significantly impaired on the biological motion task. In addition, deficits in biological motion perception correlated with impaired social functioning as measured by the Zigler social competence scale [Zigler, E., Levine, J. (1981). Premorbid competence in schizophrenia: what is being measured? Journal of Consulting and Clinical Psychology, 49, 96-105.]. The deficit in biological motion processing, which may be related to the previously documented deficit in global motion processing, could contribute to abnormal social functioning in schizophrenia.

DNA Repair in Prostate Cancer: Biology and Clinical Implications.

PubMed

Mateo, Joaquin; Boysen, Gunther; Barbieri, Christopher E; Bryant, Helen E; Castro, Elena; Nelson, Pete S; Olmos, David; Pritchard, Colin C; Rubin, Mark A; de Bono, Johann S

2017-03-01

For more precise, personalized care in prostate cancer (PC), a new classification based on molecular features relevant for prognostication and treatment stratification is needed. Genomic aberrations in the DNA damage repair pathway are common in PC, particularly in late-stage disease, and may be relevant for treatment stratification. To review current knowledge on the prevalence and clinical significance of aberrations in DNA repair genes in PC, particularly in metastatic disease. A literature search up to July 2016 was conducted, including clinical trials and preclinical basic research studies. Keywords included DNA repair, BRCA, ATM, CRPC, prostate cancer, PARP, platinum, predictive biomarkers, and hereditary cancer. We review how the DNA repair pathway is relevant to prostate carcinogenesis and progression. Data on how this may be relevant to hereditary cancer and genetic counseling are included, as well as data from clinical trials of PARP inhibitors and platinum therapeutics in PC. Relevant studies have identified genomic defects in DNA repair in PCs in 20-30% of advanced castration-resistant PC cases, a proportion of which are germline aberrations and heritable. Phase 1/2 clinical trial data, and other supporting clinical data, support the development of PARP inhibitors and DNA-damaging agents in this molecularly defined subgroup of PC following success in other cancer types. These studies may be an opportunity to improve patient care with personalized therapeutic strategies. Key literature on how genomic defects in the DNA damage repair pathway are relevant for prostate cancer biology and clinical management is reviewed. Potential implications for future changes in patient care are discussed. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

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

PubMed

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.

Infrared microspectroscopy of live cells in microfluidic devices (MD-IRMS): toward a powerful label-free cell-based assay.

PubMed

Vaccari, L; Birarda, G; Businaro, L; Pacor, S; Grenci, G

2012-06-05

Until nowadays most infrared microspectroscopy (IRMS) experiments on biological specimens (i.e., tissues or cells) have been routinely carried out on fixed or dried samples in order to circumvent water absorption problems. In this paper, we demonstrate the possibility to widen the range of in-vitro IRMS experiments to vibrational analysis of live cellular samples, thanks to the development of novel biocompatible IR-visible transparent microfluidic devices (MD). In order to highlight the biological relevance of IRMS in MD (MD-IRMS), we performed a systematic exploration of the biochemical alterations induced by different fixation protocols, ethanol 70% and formaldehyde solution 4%, as well as air-drying on U937 leukemic monocytes by comparing their IR vibrational features with the live U937 counterpart. Both fixation and air-drying procedures affected lipid composition and order as well as protein structure at a different extent while they both induced structural alterations in nucleic acids. Therefore, only IRMS of live cells can provide reliable information on both DNA and RNA structure and on their cellular dynamic. In summary, we show that MD-IRMS of live cells is feasible, reliable, and biologically relevant to be recognized as a label-free cell-based assay.

The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013.

PubMed

Hastings, Janna; de Matos, Paula; Dekker, Adriano; Ennis, Marcus; Harsha, Bhavana; Kale, Namrata; Muthukrishnan, Venkatesh; Owen, Gareth; Turner, Steve; Williams, Mark; Steinbeck, Christoph

2013-01-01

ChEBI (http://www.ebi.ac.uk/chebi) is a database and ontology of chemical entities of biological interest. Over the past few years, ChEBI has continued to grow steadily in content, and has added several new features. In addition to incorporating all user-requested compounds, our annotation efforts have emphasized immunology, natural products and metabolites in many species. All database entries are now 'is_a' classified within the ontology, meaning that all of the chemicals are available to semantic reasoning tools that harness the classification hierarchy. We have completely aligned the ontology with the Open Biomedical Ontologies (OBO) Foundry-recommended upper level Basic Formal Ontology. Furthermore, we have aligned our chemical classification with the classification of chemical-involving processes in the Gene Ontology (GO), and as a result of this effort, the majority of chemical-involving processes in GO are now defined in terms of the ChEBI entities that participate in them. This effort necessitated incorporating many additional biologically relevant compounds. We have incorporated additional data types including reference citations, and the species and component for metabolites. Finally, our website and web services have had several enhancements, most notably the provision of a dynamic new interactive graph-based ontology visualization.

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

PubMed

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.

Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course.

PubMed

Jaswal, Sheila S; O'Hara, Patricia B; Williamson, Patrick L; Springer, Amy L

2013-01-01

Because understanding the structure of biological macromolecules is critical to understanding their function, students of biochemistry should become familiar not only with viewing, but also with generating and manipulating structural representations. We report a strategy from a one-semester undergraduate biochemistry course to integrate use of structural representation tools into both laboratory and homework activities. First, early in the course we introduce the use of readily available open-source software for visualizing protein structure, coincident with modules on amino acid and peptide bond properties. Second, we use these same software tools in lectures and incorporate images and other structure representations in homework tasks. Third, we require a capstone project in which teams of students examine a protein-nucleic acid complex and then use the software tools to illustrate for their classmates the salient features of the structure, relating how the structure helps explain biological function. To ensure engagement with a range of software and database features, we generated a detailed template file that can be used to explore any structure, and that guides students through specific applications of many of the software tools. In presentations, students demonstrate that they are successfully interpreting structural information, and using representations to illustrate particular points relevant to function. Thus, over the semester students integrate information about structural features of biological macromolecules into the larger discussion of the chemical basis of function. Together these assignments provide an accessible introduction to structural representation tools, allowing students to add these methods to their biochemical toolboxes early in their scientific development. © 2013 by The International Union of Biochemistry and Molecular Biology.

Potential of proton-pumping rhodopsins: engineering photosystems into microorganisms.

PubMed

Claassens, Nico J; Volpers, Michael; dos Santos, Vitor A P Martins; van der Oost, John; de Vos, Willem M

2013-11-01

A wide range of proton-pumping rhodopsins (PPRs) have been discovered in recent years. Using a synthetic biology approach, PPR photosystems with different features can be easily introduced in nonphotosynthetic microbial hosts. PPRs can provide hosts with the ability to harvest light and drive the sustainable production of biochemicals or biofuels. PPRs use light energy to generate an outward proton flux, and the resulting proton motive force can subsequently power cellular processes. Recently, the introduction of PPRs in microbial production hosts has successfully led to light-driven biotechnological conversions. In this review, we discuss relevant features of natural PPRs, evaluate reported biotechnological applications of microbial production hosts equipped with PPRs, and provide an outlook on future developments. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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.

Student perception of relevance of biology content to everyday life: A study in higher education biology courses

NASA Astrophysics Data System (ADS)

Himschoot, Agnes Rose

The purpose of this mixed method case study was to examine the effects of methods of instruction on students' perception of relevance in higher education non-biology majors' courses. Nearly ninety percent of all students in a liberal arts college are required to take a general biology course. It is proposed that for many of those students, this is the last science course they will take for life. General biology courses are suspected of discouraging student interest in biology with large enrollment, didactic instruction, covering a huge amount of content in one semester, and are charged with promoting student disengagement with biology by the end of the course. Previous research has been aimed at increasing student motivation and interest in biology as measured by surveys and test results. Various methods of instruction have been tested and show evidence of improved learning gains. This study focused on students' perception of relevance of biology content to everyday life and the methods of instruction that increase it. A quantitative survey was administered to assess perception of relevance pre and post instruction over three topics typically taught in a general biology course. A second quantitative survey of student experiences during instruction was administered to identify methods of instruction used in the course lecture and lab. While perception of relevance dropped in the study, qualitative focus groups provided insight into the surprising results by identifying topics that are more relevant than the ones chosen for the study, conveying the affects of the instructor's personal and instructional skills on student engagement, explanation of how active engagement during instruction promotes understanding of relevance, the roll of laboratory in promoting students' understanding of relevance as well as identifying external factors that affect student engagement. The study also investigated the extent to which gender affected changes in students' perception of relevance. The results of this study will inform instructors' pedagogical and logistical choices in the design and implementation of higher education biology courses for non-biology majors. Recommendations for future research will include refining the study to train instructors in methods of instruction that promote student engagement as well as to identify biology topics that are more relevant to students enrolled in non-major biology courses.

Biological and functional relevance of CASP predictions.

PubMed

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

2018-03-01

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

Features: Real-Time Adaptive Feature and Document Learning for Web Search.

ERIC Educational Resources Information Center

Chen, Zhixiang; Meng, Xiannong; Fowler, Richard H.; Zhu, Binhai

2001-01-01

Describes Features, an intelligent Web search engine that is able to perform real-time adaptive feature (i.e., keyword) and document learning. Explains how Features learns from users' document relevance feedback and automatically extracts and suggests indexing keywords relevant to a search query, and learns from users' keyword relevance feedback…

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

PubMed

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.

Structural features that predict real-value fluctuations of globular proteins

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-01-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics trajectories of non-homologous 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. It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in molecular dynamics trajectories. Moreover, support vector regression 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 for the prediction by the Gaussian network model. An advantage of the developed method over the Gaussian network models 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. PMID:22328193

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

PubMed Central

Gao, She-Gan; Liu, Rui-Min; Zhao, Yun-Gang; Wang, Pei; Ward, Douglas G.; Wang, Guang-Chao; Guo, Xiang-Qian; Gu, Juan; Niu, Wan-Bin; Zhang, Tian; Martin, Ashley; Guo, Zhi-Peng; Feng, Xiao-Shan; Qi, Yi-Jun; Ma, Yuan-Fang

2016-01-01

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC. PMID:26898710

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

PubMed Central

Bray, Mark-Anthony; Singh, Shantanu; Han, Han; Davis, Chadwick T.; Borgeson, Blake; Hartland, Cathy; Kost-Alimova, Maria; Gustafsdottir, Sigrun M.; Gibson, Christopher C.; Carpenter, Anne E.

2016-01-01

In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, a morphological profiling assay multiplexing six fluorescent dyes imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multi-well plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Then, automated image analysis software identifies individual cells and measures ~1,500 morphological features (various measures of size, shape, texture, intensity, etc.) to produce a rich profile suitable for detecting subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes two weeks; feature extraction and data analysis take an additional 1-2 weeks. PMID:27560178

Droplet-based microtumor model to assess cell-ECM interactions and drug resistance of gastric cancer cells.

PubMed

Jang, Minjeong; Koh, Ilkyoo; Lee, Seok Jae; Cheong, Jae-Ho; Kim, Pilnam

2017-01-27

Gastric cancer (GC) is a common aggressive malignant tumor with high incidence and mortality worldwide. GC is classified into intestinal and diffuse types according to the histo-morphological features. Because of distinctly different clinico-pathological features, new cancer therapy strategies and in vitro preclinical models for the two pathological variants of GC is necessary. Since extracellular matrix (ECM) influence the biological behavior of tumor cells, we hypothesized that GC might be more similarly modeled in 3D with matrix rather than in 2D. Herein, we developed a microfluidic-based a three-dimensional (3D) in vitro gastric cancer model, with subsequent drug resistance assay. AGS (intestinal type) and Hs746T (diffuse type) gastric cancer cell lines were encapsulated in collagen beads with high cellular viability. AGS exhibited an aggregation pattern with expansive growth, whereas Hs746T showed single-cell-level infiltration. Importantly, in microtumor models, epithelial-mesenchymal transition (EMT) and metastatic genes were upregulated, whereas E-cadherin was downregulated. Expression of ß-catenin was decreased in drug-resistant cells, and chemosensitivity toward the anticancer drug (5-FU) was observed in microtumors. These results suggest that in vitro microtumor models may represent a biologically relevant platform for studying gastric cancer cell biology and tumorigenesis, and for accelerating the development of novel therapeutic targets.

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

PubMed Central

Tusé, Daniel; 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. PMID:24977145

Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems.

PubMed

Adams, Alyssa; Zenil, Hector; Davies, Paul C W; Walker, Sara Imari

2017-04-20

Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) where the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.

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

PubMed

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.

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

PubMed

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.

A beginner's guide to atomic force microscopy probing for cell mechanics

PubMed Central

2016-01-01

Abstract Atomic Force microscopy (AFM) is becoming a prevalent tool in cell biology and biomedical studies, especially those focusing on the mechanical properties of cells and tissues. The newest generation of bio‐AFMs combine ease of use and seamless integration with live‐cell epifluorescence or more advanced optical microscopies. As a unique feature with respect to other bionanotools, AFM provides nanometer‐resolution maps for cell topography, stiffness, viscoelasticity, and adhesion, often overlaid with matching optical images of the probed cells. This review is intended for those about to embark in the use of bio‐AFMs, and aims to assist them in designing an experiment to measure the mechanical properties of adherent cells. In addition to describing the main steps in a typical cell mechanics protocol and explaining how data is analysed, this review will also discuss some of the relevant contact mechanics models available and how they have been used to characterize specific features of cellular and biological samples. Microsc. Res. Tech. 80:75–84, 2017. © 2016 Wiley Periodicals, Inc. PMID:27676584

Prediction of Protein-Protein Interaction Sites by Random Forest Algorithm with mRMR and IFS

PubMed Central

Li, Bi-Qing; Feng, Kai-Yan; Chen, Lei; Huang, Tao; Cai, Yu-Dong

2012-01-01

Prediction of protein-protein interaction (PPI) sites is one of the most challenging problems in computational biology. Although great progress has been made by employing various machine learning approaches with numerous characteristic features, the problem is still far from being solved. In this study, we developed a novel predictor based on Random Forest (RF) algorithm with the Minimum Redundancy Maximal Relevance (mRMR) method followed by incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility. We also included five 3D structural features to predict protein-protein interaction sites and achieved an overall accuracy of 0.672997 and MCC of 0.347977. Feature analysis showed that 3D structural features such as Depth Index (DPX) and surface curvature (SC) contributed most to the prediction of protein-protein interaction sites. It was also shown via site-specific feature analysis that the features of individual residues from PPI sites contribute most to the determination of protein-protein interaction sites. It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction. PMID:22937126

Silk-polypyrrole biocompatible actuator performance under biologically relevant conditions

NASA Astrophysics Data System (ADS)

Hagler, Jo'elen; Peterson, Ben; Murphy, Amanda; Leger, Janelle

Biocompatible actuators that are capable of controlled movement and can function under biologically relevant conditions are of significant interest in biomedical fields. Previously, we have demonstrated that a composite material of silk biopolymer and the conducting polymer polypyrrole (PPy) can be formed into a bilayer device that can bend under applied voltage. Further, these silk-PPy composites can generate forces comparable to human muscle (>0.1 MPa) making them ideal candidates for interfacing with biological tissues. Here silk-PPy composite films are tested for performance under biologically relevant conditions including exposure to a complex protein serum and biologically relevant temperatures. Free-end bending actuation performance, current response, force generation and, mass degradation were investigated . Preliminary results show that when exposed to proteins and biologically relevant temperatures, these silk-PPy composites show minimal degradation and are able to generate forces and conduct currents comparable to devices tested under standard conditions. NSF.

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

PubMed

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.

Discriminative prediction of mammalian enhancers from DNA sequence

PubMed Central

Lee, Dongwon; Karchin, Rachel; Beer, Michael A.

2011-01-01

Accurately predicting regulatory sequences and enhancers in entire genomes is an important but difficult problem, especially in large vertebrate genomes. With the advent of ChIP-seq technology, experimental detection of genome-wide EP300/CREBBP bound regions provides a powerful platform to develop predictive tools for regulatory sequences and to study their sequence properties. Here, we develop a support vector machine (SVM) framework which can accurately identify EP300-bound enhancers using only genomic sequence and an unbiased set of general sequence features. Moreover, we find that the predictive sequence features identified by the SVM classifier reveal biologically relevant sequence elements enriched in the enhancers, but we also identify other features that are significantly depleted in enhancers. The predictive sequence features are evolutionarily conserved and spatially clustered, providing further support of their functional significance. Although our SVM is trained on experimental data, we also predict novel enhancers and show that these putative enhancers are significantly enriched in both ChIP-seq signal and DNase I hypersensitivity signal in the mouse brain and are located near relevant genes. Finally, we present results of comparisons between other EP300/CREBBP data sets using our SVM and uncover sequence elements enriched and/or depleted in the different classes of enhancers. Many of these sequence features play a role in specifying tissue-specific or developmental-stage-specific enhancer activity, but our results indicate that some features operate in a general or tissue-independent manner. In addition to providing a high confidence list of enhancer targets for subsequent experimental investigation, these results contribute to our understanding of the general sequence structure of vertebrate enhancers. PMID:21875935

Characterizing Cancer Drug Response and Biological Correlates: A Geometric Network Approach.

PubMed

Pouryahya, Maryam; Oh, Jung Hun; Mathews, James C; Deasy, Joseph O; Tannenbaum, Allen R

2018-04-23

In the present work, we apply a geometric network approach to study common biological features of anticancer drug response. We use for this purpose the panel of 60 human cell lines (NCI-60) provided by the National Cancer Institute. Our study suggests that mathematical tools for network-based analysis can provide novel insights into drug response and cancer biology. We adopted a discrete notion of Ricci curvature to measure, via a link between Ricci curvature and network robustness established by the theory of optimal mass transport, the robustness of biological networks constructed with a pre-treatment gene expression dataset and coupled the results with the GI50 response of the cell lines to the drugs. Based on the resulting drug response ranking, we assessed the impact of genes that are likely associated with individual drug response. For genes identified as important, we performed a gene ontology enrichment analysis using a curated bioinformatics database which resulted in biological processes associated with drug response across cell lines and tissue types which are plausible from the point of view of the biological literature. These results demonstrate the potential of using the mathematical network analysis in assessing drug response and in identifying relevant genomic biomarkers and biological processes for precision medicine.

Feature generation and representations for protein-protein interaction classification.

PubMed

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.

Generic Transport Mechanisms for Molecular Traffic in Cellular Protrusions

NASA Astrophysics Data System (ADS)

Graf, Isabella R.; Frey, Erwin

2017-03-01

Transport of molecular motors along protein filaments in a half-closed geometry is a common feature of biologically relevant processes in cellular protrusions. Using a lattice-gas model we study how the interplay between active and diffusive transport and mass conservation leads to localized domain walls and tip localization of the motors. We identify a mechanism for task sharing between the active motors (maintaining a gradient) and the diffusive motion (transport to the tip), which ensures that energy consumption is low and motor exchange mostly happens at the tip. These features are attributed to strong nearest-neighbor correlations that lead to a strong reduction of active currents, which we calculate analytically using an exact moment identity, and might prove useful for the understanding of correlations and active transport also in more elaborate systems.

Text-based Analytics for Biosurveillance

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

Charles, Lauren E.; Smith, William P.; Rounds, Jeremiah

The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related tomore » biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when). The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related to biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when).« less

Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states.

PubMed

Li, Wei Vivian; Razaee, Zahra S; Li, Jingyi Jessica

2016-01-11

The dynamics of epigenomic marks in their relevant chromatin states regulate distinct gene expression patterns, biological functions and phenotypic variations in biological processes. The availability of high-throughput epigenomic data generated by next-generation sequencing technologies allows a data-driven approach to evaluate the similarities and differences of diverse tissue and cell types in terms of epigenomic features. While ChromImpute has allowed for the imputation of large-scale epigenomic information to yield more robust data to capture meaningful relationships between biological samples, widely used methods such as hierarchical clustering and correlation analysis cannot adequately utilize epigenomic data to accurately reveal the distinction and grouping of different tissue and cell types. We utilize a three-step testing procedure-ANOVA, t test and overlap test to identify tissue/cell-type- associated enhancers and promoters and to calculate a newly defined Epigenomic Overlap Measure (EPOM). EPOM results in a clear correspondence map of biological samples from different tissue and cell types through comparison of epigenomic marks evaluated in their relevant chromatin states. Correspondence maps by EPOM show strong capability in distinguishing and grouping different tissue and cell types and reveal biologically meaningful similarities between Heart and Muscle, Blood & T-cell and HSC & B-cell, Brain and Neurosphere, etc. The gene ontology enrichment analysis both supports and explains the discoveries made by EPOM and suggests that the associated enhancers and promoters demonstrate distinguishable functions across tissue and cell types. Moreover, the tissue/cell-type-associated enhancers and promoters show enrichment in the disease-related SNPs that are also associated with the corresponding tissue or cell types. This agreement suggests the potential of identifying causal genetic variants relevant to cell-type-specific diseases from our identified associated enhancers and promoters. The proposed EPOM measure demonstrates superior capability in grouping and finding a clear correspondence map of biological samples from different tissue and cell types. The identified associated enhancers and promoters provide a comprehensive catalog to study distinct biological processes and disease variants in different tissue and cell types. Our results also find that the associated promoters exhibit more cell-type-specific functions than the associated enhancers do, suggesting that the non-associated promoters have more housekeeping functions than the non-associated enhancers.

Strawberry tannins inhibit IL-8 secretion in a cell model of gastric inflammation.

PubMed

Fumagalli, Marco; Sangiovanni, Enrico; Vrhovsek, Urska; Piazza, Stefano; Colombo, Elisa; Gasperotti, Mattia; Mattivi, Fulvio; De Fabiani, Emma; Dell'Agli, Mario

2016-09-01

In the present study we chemically profiled tannin-enriched extracts from strawberries and tested their biological properties in a cell model of gastric inflammation. The chemical and biological features of strawberry tannins after in vitro simulated gastric digestion were investigated as well. The anti-inflammatory activities of pure strawberry tannins were assayed to get mechanistic insights. Tannin-enriched extracts from strawberries inhibit IL-8 secretion in TNFα-treated human gastric epithelial cells by dampening the NF-κB signaling. In vitro simulated gastric digestion slightly affected the chemical composition and the biological properties of strawberry tannins. By using pure compounds, we found that casuarictin may act as a pure NF-κB inhibitor while agrimoniin inhibits IL-8 secretion also acting on other biological targets; in our system procyanidin B1 prevents the TNFα-induced effects without interfering with the NF-κB pathway. We conclude that strawberry tannins, even after in vitro simulated gastric digestion, exert anti-inflammatory activities at nutritionally relevant concentrations. Copyright © 2016 Elsevier Ltd. All rights reserved.

A nanoscale Zr-based fluorescent metal-organic framework for selective and sensitive detection of hydrogen sulfide

NASA Astrophysics Data System (ADS)

Li, Yanping; Zhang, Xin; Zhang, Ling; Jiang, Ke; Cui, Yuanjing; Yang, Yu; Qian, Guodong

2017-11-01

Hydrogen sulfide (H2S) has been commonly viewed as a gas signaling molecule in various physiological and pathological processes. However, the highly efficient H2S detection still remains challenging. Herein, we designed a new robust nano metal-organic framework (MOF) UiO-66-CH=CH2 as a fluorescent probe for rapid, sensitive and selective detection of biological H2S. UiO-66-CH=CH2 was prepared by heating ZrCl4 and 2-vinylterephthalic acid via a simple method. UiO-66-CH=CH2 displayed fluorescence quenching to H2S and kept excellent selectivity in the presence of biological relevant analytes especially the cysteine and glutathione. This MOF-based probe also exhibited fast response (10 s) and high sensitivity with a detection limit of 6.46 μM which was within the concentration range of biological H2S in living system. Moreover, this constructed MOF featured water-stability, nanoscale (20-30 nm) and low toxicity, which made it a promising candidate for biological H2S sensing.

The HepaRG cell line: biological properties and relevance as a tool for cell biology, drug metabolism, and virology studies.

PubMed

Marion, Marie-Jeanne; Hantz, Olivier; Durantel, David

2010-01-01

Liver progenitor cells may play an important role in carcinogenesis in vivo and represent therefore useful cellular materials for in vitro studies. The HepaRG cell line, which is a human bipotent progenitor cell line capable to differentiate toward two different cell phenotypes (i.e., biliary-like and hepatocyte-like cells), has been established from a liver tumor associated with chronic hepatitis C. This cell line represents a valuable alternative to ex vivo cultivated primary human hepatocytes (PHH), as HepaRG cells share some features and properties with adult hepatocytes. The cell line is particularly useful to evaluate drugs and perform drug metabolism studies, as many detoxifying enzymes are expressed and functional. It is also an interesting tool to study some aspect of progenitor biology (e.g., differentiation process), carcinogenesis, and the infection by some pathogens for which the cell line is permissive (e.g., HBV infection). Overall, this chapter gives a concise overview of the biological properties and potential applications of this cell line.

Paranemic Crossover DNA: There and Back Again.

PubMed

Wang, Xing; Chandrasekaran, Arun Richard; Shen, Zhiyong; Ohayon, Yoel P; Wang, Tong; Kizer, Megan E; Sha, Ruojie; Mao, Chengde; Yan, Hao; Zhang, Xiaoping; Liao, Shiping; Ding, Baoquan; Chakraborty, Banani; Jonoska, Natasha; Niu, Dong; Gu, Hongzhou; Chao, Jie; Gao, Xiang; Li, Yuhang; Ciengshin, Tanashaya; Seeman, Nadrian C

2018-06-18

Over the past 35 years, DNA has been used to produce various nanometer-scale constructs, nanomechanical devices, and walkers. Construction of complex DNA nanostructures relies on the creation of rigid DNA motifs. Paranemic crossover (PX) DNA is one such motif that has played many roles in DNA nanotechnology. Specifically, PX cohesion has been used to connect topologically closed molecules, to assemble a three-dimensional object, and to create two-dimensional DNA crystals. Additionally, a sequence-dependent nanodevice based on conformational change between PX and its topoisomer, JX 2 , has been used in robust nanoscale assembly lines, as a key component in a DNA transducer, and to dictate polymer assembly. Furthermore, the PX motif has recently found a new role directly in basic biology, by possibly serving as the molecular structure for double-stranded DNA homology recognition, a prominent feature of molecular biology and essential for many crucial biological processes. This review discusses the many attributes and usages of PX-DNA-its design, characteristics, applications, and potential biological relevance-and aims to accelerate the understanding of PX-DNA motif in its many roles and manifestations.

Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis.

PubMed

Ferrari, Raffaele; Forabosco, Paola; Vandrovcova, Jana; Botía, Juan A; Guelfi, Sebastian; Warren, Jason D; Momeni, Parastoo; Weale, Michael E; Ryten, Mina; Hardy, John

2016-02-24

In frontotemporal dementia (FTD) there is a critical lack in the understanding of biological and molecular mechanisms involved in disease pathogenesis. The heterogeneous genetic features associated with FTD suggest that multiple disease-mechanisms are likely to contribute to the development of this neurodegenerative condition. We here present a systems biology approach with the scope of i) shedding light on the biological processes potentially implicated in the pathogenesis of FTD and ii) identifying novel potential risk factors for FTD. We performed a gene co-expression network analysis of microarray expression data from 101 individuals without neurodegenerative diseases to explore regional-specific co-expression patterns in the frontal and temporal cortices for 12 genes (MAPT, GRN, CHMP2B, CTSC, HLA-DRA, TMEM106B, C9orf72, VCP, UBQLN2, OPTN, TARDBP and FUS) associated with FTD and we then carried out gene set enrichment and pathway analyses, and investigated known protein-protein interactors (PPIs) of FTD-genes products. Gene co-expression networks revealed that several FTD-genes (such as MAPT and GRN, CTSC and HLA-DRA, TMEM106B, and C9orf72, VCP, UBQLN2 and OPTN) were clustering in modules of relevance in the frontal and temporal cortices. Functional annotation and pathway analyses of such modules indicated enrichment for: i) DNA metabolism, i.e. transcription regulation, DNA protection and chromatin remodelling (MAPT and GRN modules); ii) immune and lysosomal processes (CTSC and HLA-DRA modules), and; iii) protein meta/catabolism (C9orf72, VCP, UBQLN2 and OPTN, and TMEM106B modules). PPI analysis supported the results of the functional annotation and pathway analyses. This work further characterizes known FTD-genes and elaborates on their biological relevance to disease: not only do we indicate likely impacted regional-specific biological processes driven by FTD-genes containing modules, but also do we suggest novel potential risk factors among the FTD-genes interactors as targets for further mechanistic characterization in hypothesis driven cell biology work.

Hidden treasures in "ancient" microarrays: gene-expression portrays biology and potential resistance pathways of major lung cancer subtypes and normal tissue.

PubMed

Kerkentzes, Konstantinos; Lagani, Vincenzo; Tsamardinos, Ioannis; Vyberg, Mogens; Røe, Oluf Dimitri

2014-01-01

Novel statistical methods and increasingly more accurate gene annotations can transform "old" biological data into a renewed source of knowledge with potential clinical relevance. Here, we provide an in silico proof-of-concept by extracting novel information from a high-quality mRNA expression dataset, originally published in 2001, using state-of-the-art bioinformatics approaches. The dataset consists of histologically defined cases of lung adenocarcinoma (AD), squamous (SQ) cell carcinoma, small-cell lung cancer, carcinoid, metastasis (breast and colon AD), and normal lung specimens (203 samples in total). A battery of statistical tests was used for identifying differential gene expressions, diagnostic and prognostic genes, enriched gene ontologies, and signaling pathways. Our results showed that gene expressions faithfully recapitulate immunohistochemical subtype markers, as chromogranin A in carcinoids, cytokeratin 5, p63 in SQ, and TTF1 in non-squamous types. Moreover, biological information with putative clinical relevance was revealed as potentially novel diagnostic genes for each subtype with specificity 93-100% (AUC = 0.93-1.00). Cancer subtypes were characterized by (a) differential expression of treatment target genes as TYMS, HER2, and HER3 and (b) overrepresentation of treatment-related pathways like cell cycle, DNA repair, and ERBB pathways. The vascular smooth muscle contraction, leukocyte trans-endothelial migration, and actin cytoskeleton pathways were overexpressed in normal tissue. Reanalysis of this public dataset displayed the known biological features of lung cancer subtypes and revealed novel pathways of potentially clinical importance. The findings also support our hypothesis that even old omics data of high quality can be a source of significant biological information when appropriate bioinformatics methods are used.

Detection of Lipid and Amphiphilic Biomarkers for Disease Diagnostics

PubMed Central

Vu, Dung M.; Mendez, Heather M.; Jakhar, Shailja; Mukundan, Harshini

2017-01-01

Rapid diagnosis is crucial to effectively treating any disease. Biological markers, or biomarkers, have been widely used to diagnose a variety of infectious and non-infectious diseases. The detection of biomarkers in patient samples can also provide valuable information regarding progression and prognosis. Interestingly, many such biomarkers are composed of lipids, and are amphiphilic in biochemistry, which leads them to be often sequestered by host carriers. Such sequestration enhances the difficulty of developing sensitive and accurate sensors for these targets. Many of the physiologically relevant molecules involved in pathogenesis and disease are indeed amphiphilic. This chemical property is likely essential for their biological function, but also makes them challenging to detect and quantify in vitro. In order to understand pathogenesis and disease progression while developing effective diagnostics, it is important to account for the biochemistry of lipid and amphiphilic biomarkers when creating novel techniques for the quantitative measurement of these targets. Here, we review techniques and methods used to detect lipid and amphiphilic biomarkers associated with disease, as well as their feasibility for use as diagnostic targets, highlighting the significance of their biochemical properties in the design and execution of laboratory and diagnostic strategies. The biochemistry of biological molecules is clearly relevant to their physiological function, and calling out the need for consideration of this feature in their study, and use as vaccine, diagnostic and therapeutic targets is the overarching motivation for this review. PMID:28677660

Hormesis as a biological hypothesis.

PubMed Central

Calabrese, E J; Baldwin, L A

1998-01-01

A comprehensive effort was undertaken to identify articles demonstrating chemical hormesis. Nearly 4000 potentially relevant articles were retrieved from preliminary computer database searches by using various key word descriptors and extensive cross-referencing. A priori evaluation criteria were established including study design features (e.g., number of doses, dose range), statistical analysis, and reproducibility of results. Evidence of chemical hormesis was judged to have occurred in approximately 350 of the 4000 studies evaluated. Chemical hormesis was observed in a wide range of taxonomic groups and involved agents representing highly diverse chemical classes, many of potential environmental relevance. Numerous biological end points were assessed; growth responses were the most prevalent, followed by metabolic effects, longevity, reproductive responses, and survival. Hormetic responses were generally observed to be of limited magnitude. The average low-dose maximum stimulation was approximately 50% greater than controls. The hormetic dose-response range was generally limited to about one order of magnitude, with the upper end of the hormetic curve approaching the estimated no observable effect level for the particular end point. Based on the evaluation criteria, high to moderate evidence of hormesis was observed in studies comprised of > 6 doses; with > 3 doses in the hormetic zone. The present analysis suggests that chemical hormesis is a reproducible and relatively common biological phenomenon. A quantitative scheme is presented for future application to the database. PMID:9539030

Identifying Epigenetic Biomarkers using Maximal Relevance and Minimal Redundancy Based Feature Selection for Multi-Omics Data.

PubMed

Mallik, Saurav; Bhadra, Tapas; Maulik, Ujjwal

2017-01-01

Epigenetic Biomarker discovery is an important task in bioinformatics. In this article, we develop a new framework of identifying statistically significant epigenetic biomarkers using maximal-relevance and minimal-redundancy criterion based feature (gene) selection for multi-omics dataset. Firstly, we determine the genes that have both expression as well as methylation values, and follow normal distribution. Similarly, we identify the genes which consist of both expression and methylation values, but do not follow normal distribution. For each case, we utilize a gene-selection method that provides maximal-relevant, but variable-weighted minimum-redundant genes as top ranked genes. For statistical validation, we apply t-test on both the expression and methylation data consisting of only the normally distributed top ranked genes to determine how many of them are both differentially expressed andmethylated. Similarly, we utilize Limma package for performing non-parametric Empirical Bayes test on both expression and methylation data comprising only the non-normally distributed top ranked genes to identify how many of them are both differentially expressed and methylated. We finally report the top-ranking significant gene-markerswith biological validation. Moreover, our framework improves positive predictive rate and reduces false positive rate in marker identification. In addition, we provide a comparative analysis of our gene-selection method as well as othermethods based on classificationperformances obtained using several well-known classifiers.

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

PubMed

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.

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

PubMed Central

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. PMID:29300763

Utilizing population variation, vaccination, and systems biology to study human immunology.

PubMed

Tsang, John S

2015-08-01

The move toward precision medicine has highlighted the importance of understanding biological variability within and across individuals in the human population. In particular, given the prevalent involvement of the immune system in diverse pathologies, an important question is how much and what information about the state of the immune system is required to enable accurate prediction of future health and response to medical interventions. Towards addressing this question, recent studies using vaccination as a model perturbation and systems-biology approaches are beginning to provide a glimpse of how natural population variation together with multiplexed, high-throughput measurement and computational analysis can be used to uncover predictors of immune response quality in humans. Here I discuss recent developments in this emerging field, with emphasis on baseline correlates of vaccination responses, sources of immune-state variability, as well as relevant features of study design, data generation, and computational analysis. Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.

Cellular and Molecular Actions of Methylene Blue in the Nervous System

PubMed Central

Oz, Murat; Lorke, Dietrich E.; Hasan, Mohammed; Petroianu, George A.

2010-01-01

Methylene Blue (MB), following its introduction to biology in the 19th century by Ehrlich, has found uses in various areas of medicine and biology. At present, MB is the first line of treatment in methemoglobinemias, is used frequently in the treatment of ifosfamide-induced encephalopathy, and is routinely employed as a diagnostic tool in surgical procedures. Furthermore, recent studies suggest that MB has beneficial effects in Alzheimer's disease and memory improvement. Although the modulation of the cGMP pathway is considered the most significant effect of MB, mediating its pharmacological actions, recent studies indicate that it has multiple cellular and molecular targets. In the majority of cases, biological effects and clinical applications of MB are dictated by its unique physicochemical properties including its planar structure, redox chemistry, ionic charges, and light spectrum characteristics. In this review article, these physicochemical features and the actions of MB on multiple cellular and molecular targets are discussed with regard to their relevance to the nervous system. PMID:19760660

Next-generation libraries for robust RNA interference-based genome-wide screens

PubMed Central

Kampmann, Martin; Horlbeck, Max A.; Chen, Yuwen; Tsai, Jordan C.; Bassik, Michael C.; Gilbert, Luke A.; Villalta, Jacqueline E.; Kwon, S. Chul; Chang, Hyeshik; Kim, V. Narry; Weissman, Jonathan S.

2015-01-01

Genetic screening based on loss-of-function phenotypes is a powerful discovery tool in biology. Although the recent development of clustered regularly interspaced short palindromic repeats (CRISPR)-based screening approaches in mammalian cell culture has enormous potential, RNA interference (RNAi)-based screening remains the method of choice in several biological contexts. We previously demonstrated that ultracomplex pooled short-hairpin RNA (shRNA) libraries can largely overcome the problem of RNAi off-target effects in genome-wide screens. Here, we systematically optimize several aspects of our shRNA library, including the promoter and microRNA context for shRNA expression, selection of guide strands, and features relevant for postscreen sample preparation for deep sequencing. We present next-generation high-complexity libraries targeting human and mouse protein-coding genes, which we grouped into 12 sublibraries based on biological function. A pilot screen suggests that our next-generation RNAi library performs comparably to current CRISPR interference (CRISPRi)-based approaches and can yield complementary results with high sensitivity and high specificity. PMID:26080438

Pyramidal neurovision architecture for vision machines

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1993-08-01

The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks

PubMed Central

Miconi, Thomas

2017-01-01

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior. DOI: http://dx.doi.org/10.7554/eLife.20899.001 PMID:28230528

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks.

PubMed

Miconi, Thomas

2017-02-23

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior.

Higher order visual input to the mushroom bodies in the bee, Bombus impatiens.

PubMed

Paulk, Angelique C; Gronenberg, Wulfila

2008-11-01

To produce appropriate behaviors based on biologically relevant associations, sensory pathways conveying different modalities are integrated by higher-order central brain structures, such as insect mushroom bodies. To address this function of sensory integration, we characterized the structure and response of optic lobe (OL) neurons projecting to the calyces of the mushroom bodies in bees. Bees are well known for their visual learning and memory capabilities and their brains possess major direct visual input from the optic lobes to the mushroom bodies. To functionally characterize these visual inputs to the mushroom bodies, we recorded intracellularly from neurons in bumblebees (Apidae: Bombus impatiens) and a single neuron in a honeybee (Apidae: Apis mellifera) while presenting color and motion stimuli. All of the mushroom body input neurons were color sensitive while a subset was motion sensitive. Additionally, most of the mushroom body input neurons would respond to the first, but not to subsequent, presentations of repeated stimuli. In general, the medulla or lobula neurons projecting to the calyx signaled specific chromatic, temporal, and motion features of the visual world to the mushroom bodies, which included sensory information required for the biologically relevant associations bees form during foraging tasks.

Marine microbial L-asparaginase: Biochemistry, molecular approaches and applications in tumor therapy and in food industry.

PubMed

Izadpanah Qeshmi, Fatemeh; Homaei, Ahmad; Fernandes, Pedro; Javadpour, Sedigheh

2018-03-01

The marine environment is a rich source of biological and chemical diversity. It covers more than 70% of the Earth's surface and features a wide diversity of habitats, often displaying extreme conditions, where marine organisms thrive, offering a vast pool for microorganisms and enzymes. Given the dissimilarity between marine and terrestrial habitats, enzymes and microorganisms, either novel or with different and appealing features as compared to terrestrial counterparts, may be identified and isolated. L-asparaginase (E.C. 3.5.1.1), is among the relevant enzymes that can be obtained from marine sources. This amidohydrolase acts on L-asparagine and produce L-aspartate and ammonia, accordingly it has an acknowledged chemotherapeutic application, namely in acute lymphoblastic leukemia. Moreover, L-asparaginase is also of interest in the food industry as it prevents acrylamide formation. Terrestrial organisms have been largely tapped for L-asparaginases, but most failed to comply with criteria for practical applications, whereas marine sources have only been marginally screened. This work provides an overview on the relevant features of this enzyme and the framework for its application, with a clear emphasis on the use of L-asparaginase from marine sources. The review envisages to highlight the unique properties of marine L-asparaginases that could make them good candidates for medical applications and industries, especially in food safety. Copyright © 2018 Elsevier GmbH. All rights reserved.

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

PubMed Central

McDougall, Carmel; Woodcroft, Ben J.

2016-01-01

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 construction of biological materials with diverse morphologies. The SilkSlider predictor software developed here is available at https://github.com/wwood/SilkSlider. PMID:27415783

Patient-derived xenografts as preclinical neuroblastoma models.

PubMed

Braekeveldt, Noémie; Bexell, Daniel

2018-05-01

The prognosis for children with high-risk neuroblastoma is often poor and survivors can suffer from severe side effects. Predictive preclinical models and novel therapeutic strategies for high-risk disease are therefore a clinical imperative. However, conventional cancer cell line-derived xenografts can deviate substantially from patient tumors in terms of their molecular and phenotypic features. Patient-derived xenografts (PDXs) recapitulate many biologically and clinically relevant features of human cancers. Importantly, PDXs can closely parallel clinical features and outcome and serve as excellent models for biomarker and preclinical drug development. Here, we review progress in and applications of neuroblastoma PDX models. Neuroblastoma orthotopic PDXs share the molecular characteristics, neuroblastoma markers, invasive properties and tumor stroma of aggressive patient tumors and retain spontaneous metastatic capacity to distant organs including bone marrow. The recent identification of genomic changes in relapsed neuroblastomas opens up opportunities to target treatment-resistant tumors in well-characterized neuroblastoma PDXs. We highlight and discuss the features and various sources of neuroblastoma PDXs, methodological considerations when establishing neuroblastoma PDXs, in vitro 3D models, current limitations of PDX models and their application to preclinical drug testing.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

BIOREL: the benchmark resource to estimate the relevance of the gene networks.

PubMed

Antonov, Alexey V; Mewes, Hans W

2006-02-06

The progress of high-throughput methodologies in functional genomics has lead to the development of statistical procedures to infer gene networks from various types of high-throughput data. However, due to the lack of common standards, the biological significance of the results of the different studies is hard to compare. To overcome this problem we propose a benchmark procedure and have developed a web resource (BIOREL), which is useful for estimating the biological relevance of any genetic network by integrating different sources of biological information. The associations of each gene from the network are classified as biologically relevant or not. The proportion of genes in the network classified as "relevant" is used as the overall network relevance score. Employing synthetic data we demonstrated that such a score ranks the networks fairly in respect to the relevance level. Using BIOREL as the benchmark resource we compared the quality of experimental and theoretically predicted protein interaction data.

Characterization of dynamic physiology of the bladder by optical coherence tomography

NASA Astrophysics Data System (ADS)

Yuan, Zhijia; Keng, Kerri; Pan, Rubin; Ren, Hugang; Du, Congwu; Kim, Jason; Pan, Yingtian

2012-03-01

Because of its high spatial resolution and noninvasive imaging capabilities, optical coherence tomography has been used to characterize the morphological details of various biological tissues including urinary bladder and to diagnose their alternations (e.g., cancers). In addition to static morphology, the dynamic features of tissue morphology can provide important information that can be used to diagnose the physiological and functional characteristics of biological tissues. Here, we present the imaging studies based on optical coherence tomography to characterize motion related physiology and functions of rat bladder detrusor muscles and compared the results with traditional biomechanical measurements. Our results suggest that optical coherence tomography is capable of providing quantitative evaluation of contractile functions of intact bladder (without removing bladder epithelium and connective tissue), which is potentially of more clinical relevance for future clinical diagnosis - if incorporated with cystoscopic optical coherence tomography.

Biology and medicine of soccer: an update.

PubMed

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.

Understanding Kidney Disease: Toward the Integration of Regulatory Networks Across Species

PubMed Central

Ju, Wenjun; Brosius, Frank C.

2010-01-01

Animal models have long been useful in investigating both normal and abnormal human physiology. Systems biology provides a relatively new set of approaches to identify similarities and differences between animal models and humans that may lead to a more comprehensive understanding of human kidney pathophysiology. In this review, we briefly describe how genome-wide analyses of mouse models have helped elucidate features of human kidney diseases, discuss strategies to achieve effective network integration, and summarize currently available web-based tools that may facilitate integration of data across species. The rapid progress in systems biology and orthology, as well as the advent of web-based tools to facilitate these processes, now make it possible to take advantage of knowledge from distant animal species in targeted identification of regulatory networks that may have clinical relevance for human kidney diseases. PMID:21044762

Innovation: an emerging focus from cells to societies.

PubMed

Hochberg, Michael E; Marquet, Pablo A; Boyd, Robert; Wagner, Andreas

2017-12-05

Innovations are generally unexpected, often spectacular changes in phenotypes and ecological functions. The contributions to this theme issue are the latest conceptual, theoretical and experimental developments, addressing how ecology, environment, ontogeny and evolution are central to understanding the complexity of the processes underlying innovations. Here, we set the stage by introducing and defining key terms relating to innovation and discuss their relevance to biological, cultural and technological change. Discovering how the generation and transmission of novel biological information, environmental interactions and selective evolutionary processes contribute to innovation as an ecosystem will shed light on how the dominant features across life come to be, generalize to social, cultural and technological evolution, and have applications in the health sciences and sustainability.This article is part of the theme issue 'Process and pattern in innovations from cells to societies'. © 2017 The Author(s).

Innovation: an emerging focus from cells to societies

PubMed Central

Boyd, Robert

2017-01-01

Innovations are generally unexpected, often spectacular changes in phenotypes and ecological functions. The contributions to this theme issue are the latest conceptual, theoretical and experimental developments, addressing how ecology, environment, ontogeny and evolution are central to understanding the complexity of the processes underlying innovations. Here, we set the stage by introducing and defining key terms relating to innovation and discuss their relevance to biological, cultural and technological change. Discovering how the generation and transmission of novel biological information, environmental interactions and selective evolutionary processes contribute to innovation as an ecosystem will shed light on how the dominant features across life come to be, generalize to social, cultural and technological evolution, and have applications in the health sciences and sustainability. This article is part of the theme issue ‘Process and pattern in innovations from cells to societies’. PMID:29061887

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Perceptual learning: toward a comprehensive theory.

PubMed

Watanabe, Takeo; Sasaki, Yuka

2015-01-03

Visual perceptual learning (VPL) is long-term performance increase resulting from visual perceptual experience. Task-relevant VPL of a feature results from training of a task on the feature relevant to the task. Task-irrelevant VPL arises as a result of exposure to the feature irrelevant to the trained task. At least two serious problems exist. First, there is the controversy over which stage of information processing is changed in association with task-relevant VPL. Second, no model has ever explained both task-relevant and task-irrelevant VPL. Here we propose a dual plasticity model in which feature-based plasticity is a change in a representation of the learned feature, and task-based plasticity is a change in processing of the trained task. Although the two types of plasticity underlie task-relevant VPL, only feature-based plasticity underlies task-irrelevant VPL. This model provides a new comprehensive framework in which apparently contradictory results could be explained.

Stress-driven buckling patterns in spheroidal core/shell structures.

PubMed

Yin, Jie; Cao, Zexian; Li, Chaorong; Sheinman, Izhak; Chen, Xi

2008-12-09

Many natural fruits and vegetables adopt an approximately spheroidal shape and are characterized by their distinct undulating topologies. We demonstrate that various global pattern features can be reproduced by anisotropic stress-driven buckles on spheroidal core/shell systems, which implies that the relevant mechanical forces might provide a template underpinning the topological conformation in some fruits and plants. Three dimensionless parameters, the ratio of effective size/thickness, the ratio of equatorial/polar radii, and the ratio of core/shell moduli, primarily govern the initiation and formation of the patterns. A distinct morphological feature occurs only when these parameters fall within certain ranges: In a prolate spheroid, reticular buckles take over longitudinal ridged patterns when one or more parameters become large. Our results demonstrate that some universal features of fruit/vegetable patterns (e.g., those observed in Korean melons, silk gourds, ribbed pumpkins, striped cavern tomatoes, and cantaloupes, etc.) may be related to the spontaneous buckling from mechanical perspectives, although the more complex biological or biochemical processes are involved at deep levels.

Human Parvoviruses

PubMed Central

Söderlund-Venermo, Maria; Young, Neal S.

2016-01-01

SUMMARY Parvovirus B19 (B19V) and human bocavirus 1 (HBoV1), members of the large Parvoviridae family, are human pathogens responsible for a variety of diseases. For B19V in particular, host features determine disease manifestations. These viruses are prevalent worldwide and are culturable in vitro, and serological and molecular assays are available but require careful interpretation of results. Additional human parvoviruses, including HBoV2 to -4, human parvovirus 4 (PARV4), and human bufavirus (BuV) are also reviewed. The full spectrum of parvovirus disease in humans has yet to be established. Candidate recombinant B19V vaccines have been developed but may not be commercially feasible. We review relevant features of the molecular and cellular biology of these viruses, and the human immune response that they elicit, which have allowed a deep understanding of pathophysiology. PMID:27806994

Protein sectors: evolutionary units of three-dimensional structure

PubMed Central

Halabi, Najeeb; Rivoire, Olivier; Leibler, Stanislas; Ranganathan, Rama

2011-01-01

Proteins display a hierarchy of structural features at primary, secondary, tertiary, and higher-order levels, an organization that guides our current understanding of their biological properties and evolutionary origins. Here, we reveal a structural organization distinct from this traditional hierarchy by statistical analysis of correlated evolution between amino acids. Applied to the S1A serine proteases, the analysis indicates a decomposition of the protein into three quasi-independent groups of correlated amino acids that we term “protein sectors”. Each sector is physically connected in the tertiary structure, has a distinct functional role, and constitutes an independent mode of sequence divergence in the protein family. Functionally relevant sectors are evident in other protein families as well, suggesting that they may be general features of proteins. We propose that sectors represent a structural organization of proteins that reflects their evolutionary histories. PMID:19703402

Joint principal trend analysis for longitudinal high-dimensional data.

PubMed

Zhang, Yuping; Ouyang, Zhengqing

2018-06-01

We consider a research scenario motivated by integrating multiple sources of information for better knowledge discovery in diverse dynamic biological processes. Given two longitudinal high-dimensional datasets for a group of subjects, we want to extract shared latent trends and identify relevant features. To solve this problem, we present a new statistical method named as joint principal trend analysis (JPTA). We demonstrate the utility of JPTA through simulations and applications to gene expression data of the mammalian cell cycle and longitudinal transcriptional profiling data in response to influenza viral infections. © 2017, The International Biometric Society.

Alaska Science Center: Providing Timely, Relevant, and Impartial Study of the Landscape, Natural Resources, and Natural Hazards for Alaska and Our Nation

USGS Publications Warehouse

,

2007-01-01

The U.S. Geological Survey (USGS), the Nation's largest water, earth, and biological science and civilian mapping agency, has studied the natural features of Alaska since its earliest geologic expeditions in the 1800s. The USGS Alaska Science Center (ASC), with headquarters in Anchorage, Alaska, studies the complex natural science phenomena of Alaska to provide scientific products and results to a wide variety of partners. The complexity of Alaska's unique landscapes and ecosystems requires USGS expertise from many science disciplines to conduct thorough, integrated research.

Cell growth, division, and death in cohesive tissues: A thermodynamic approach

NASA Astrophysics Data System (ADS)

Yabunaka, Shunsuke; Marcq, Philippe

2017-08-01

Cell growth, division, and death are defining features of biological tissues that contribute to morphogenesis. In hydrodynamic descriptions of cohesive tissues, their occurrence implies a nonzero rate of variation of cell density. We show how linear nonequilibrium thermodynamics allows us to express this rate as a combination of relevant thermodynamic forces: chemical potential, velocity divergence, and activity. We illustrate the resulting effects of the nonconservation of cell density on simple examples inspired by recent experiments on cell monolayers, considering first the velocity of a spreading front, and second an instability leading to mechanical waves.

Cholesterol - a biological compound as a building block in bionanotechnology

NASA Astrophysics Data System (ADS)

Hosta-Rigau, Leticia; Zhang, Yan; Teo, Boon M.; Postma, Almar; Städler, Brigitte

2012-12-01

Cholesterol is a molecule with many tasks in nature but also a long history in science. This feature article highlights the contribution of this small compound to bionanotechnology. We discuss relevant chemical aspects in this context followed by an overview of its self-assembly capabilities both as a free molecule and when conjugated to a polymer. Further, cholesterol in the context of liposomes is reviewed and its impact ranging from biosensing to drug delivery is outlined. Cholesterol is and will be an indispensable player in bionanotechnology, contributing to the progress of this potent field of research.

Fundamentals and advances in magnetic hyperthermia

NASA Astrophysics Data System (ADS)

Périgo, E. A.; Hemery, G.; Sandre, O.; Ortega, D.; Garaio, E.; Plazaola, F.; Teran, F. J.

2015-12-01

Nowadays, magnetic hyperthermia constitutes a complementary approach to cancer treatment. The use of magnetic particles as heating mediators, proposed in the 1950s, provides a novel strategy for improving tumor treatment and, consequently, patient's quality of life. This review reports a broad overview about several aspects of magnetic hyperthermia addressing new perspectives and the progress on relevant features such as the ad hoc preparation of magnetic nanoparticles, physical modeling of magnetic heating, methods to determine the heat dissipation power of magnetic colloids including the development of experimental apparatus and the influence of biological matrices on the heating efficiency.

Oculomotor selection underlies feature retention in visual working memory.

PubMed

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.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

BASiNET-BiologicAl Sequences NETwork: a case study on coding and non-coding RNAs identification.

PubMed

Ito, Eric Augusto; Katahira, Isaque; Vicente, Fábio Fernandes da Rocha; Pereira, Luiz Filipe Protasio; Lopes, Fabrício Martins

2018-06-05

With the emergence of Next Generation Sequencing (NGS) technologies, a large volume of sequence data in particular de novo sequencing was rapidly produced at relatively low costs. In this context, computational tools are increasingly important to assist in the identification of relevant information to understand the functioning of organisms. This work introduces BASiNET, an alignment-free tool for classifying biological sequences based on the feature extraction from complex network measurements. The method initially transform the sequences and represents them as complex networks. Then it extracts topological measures and constructs a feature vector that is used to classify the sequences. The method was evaluated in the classification of coding and non-coding RNAs of 13 species and compared to the CNCI, PLEK and CPC2 methods. BASiNET outperformed all compared methods in all adopted organisms and datasets. BASiNET have classified sequences in all organisms with high accuracy and low standard deviation, showing that the method is robust and non-biased by the organism. The proposed methodology is implemented in open source in R language and freely available for download at https://cran.r-project.org/package=BASiNET.

Task-relevant perceptual features can define categories in visual memory too.

PubMed

Antonelli, Karla B; Williams, Carrick C

2017-11-01

Although Konkle, Brady, Alvarez, and Oliva (2010, Journal of Experimental Psychology: General, 139(3), 558) claim that visual long-term memory (VLTM) is organized on underlying conceptual, not perceptual, information, visual memory results from visual search tasks are not well explained by this theory. We hypothesized that when viewing an object, any task-relevant visual information is critical to the organizational structure of VLTM. In two experiments, we examined the organization of VLTM by measuring the amount of retroactive interference created by objects possessing different combinations of task-relevant features. Based on task instructions, only the conceptual category was task relevant or both the conceptual category and a perceptual object feature were task relevant. Findings indicated that when made task relevant, perceptual object feature information, along with conceptual category information, could affect memory organization for objects in VLTM. However, when perceptual object feature information was task irrelevant, it did not contribute to memory organization; instead, memory defaulted to being organized around conceptual category information. These findings support the theory that a task-defined organizational structure is created in VLTM based on the relevance of particular object features and information.

Development of the biology card sorting task to measure conceptual expertise in biology.

PubMed

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.

Discriminative and informative features for biomolecular text mining with ensemble feature selection.

PubMed

Van Landeghem, Sofie; Abeel, Thomas; Saeys, Yvan; Van de Peer, Yves

2010-09-15

In the field of biomolecular text mining, black box behavior of machine learning systems currently limits understanding of the true nature of the predictions. However, feature selection (FS) is capable of identifying the most relevant features in any supervised learning setting, providing insight into the specific properties of the classification algorithm. This allows us to build more accurate classifiers while at the same time bridging the gap between the black box behavior and the end-user who has to interpret the results. We show that our FS methodology successfully discards a large fraction of machine-generated features, improving classification performance of state-of-the-art text mining algorithms. Furthermore, we illustrate how FS can be applied to gain understanding in the predictions of a framework for biomolecular event extraction from text. We include numerous examples of highly discriminative features that model either biological reality or common linguistic constructs. Finally, we discuss a number of insights from our FS analyses that will provide the opportunity to considerably improve upon current text mining tools. The FS algorithms and classifiers are available in Java-ML (http://java-ml.sf.net). The datasets are publicly available from the BioNLP'09 Shared Task web site (http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA/SharedTask/).

Why the impact of mechanical stimuli on stem cells remains a challenge.

PubMed

Goetzke, Roman; Sechi, Antonio; De Laporte, Laura; Neuss, Sabine; Wagner, Wolfgang

2018-05-04

Mechanical stimulation affects growth and differentiation of stem cells. This may be used to guide lineage-specific cell fate decisions and therefore opens fascinating opportunities for stem cell biology and regenerative medicine. Several studies demonstrated functional and molecular effects of mechanical stimulation but on first sight these results often appear to be inconsistent. Comparison of such studies is hampered by a multitude of relevant parameters that act in concert. There are notorious differences between species, cell types, and culture conditions. Furthermore, the utilized culture substrates have complex features, such as surface chemistry, elasticity, and topography. Cell culture substrates can vary from simple, flat materials to complex 3D scaffolds. Last but not least, mechanical forces can be applied with different frequency, amplitude, and strength. It is therefore a prerequisite to take all these parameters into consideration when ascribing their specific functional relevance-and to only modulate one parameter at the time if the relevance of this parameter is addressed. Such research questions can only be investigated by interdisciplinary cooperation. In this review, we focus particularly on mesenchymal stem cells and pluripotent stem cells to discuss relevant parameters that contribute to the kaleidoscope of mechanical stimulation of stem cells.

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks

PubMed Central

Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.

2015-01-01

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003

Dorsal hippocampus is necessary for visual categorization in rats.

PubMed

Kim, Jangjin; Castro, Leyre; Wasserman, Edward A; Freeman, John H

2018-02-23

The hippocampus may play a role in categorization because of the need to differentiate stimulus categories (pattern separation) and to recognize category membership of stimuli from partial information (pattern completion). We hypothesized that the hippocampus would be more crucial for categorization of low-density (few relevant features) stimuli-due to the higher demand on pattern separation and pattern completion-than for categorization of high-density (many relevant features) stimuli. Using a touchscreen apparatus, rats were trained to categorize multiple abstract stimuli into two different categories. Each stimulus was a pentagonal configuration of five visual features; some of the visual features were relevant for defining the category whereas others were irrelevant. Two groups of rats were trained with either a high (dense, n = 8) or low (sparse, n = 8) number of category-relevant features. Upon reaching criterion discrimination (≥75% correct, on 2 consecutive days), bilateral cannulas were implanted in the dorsal hippocampus. The rats were then given either vehicle or muscimol infusions into the hippocampus just prior to various testing sessions. They were tested with: the previously trained stimuli (trained), novel stimuli involving new irrelevant features (novel), stimuli involving relocated features (relocation), and a single relevant feature (singleton). In training, the dense group reached criterion faster than the sparse group, indicating that the sparse task was more difficult than the dense task. In testing, accuracy of both groups was equally high for trained and novel stimuli. However, both groups showed impaired accuracy in the relocation and singleton conditions, with a greater deficit in the sparse group. The testing data indicate that rats encode both the relevant features and the spatial locations of the features. Hippocampal inactivation impaired visual categorization regardless of the density of the category-relevant features for the trained, novel, relocation, and singleton stimuli. Hippocampus-mediated pattern completion and pattern separation mechanisms may be necessary for visual categorization involving overlapping irrelevant features. © 2018 Wiley Periodicals, Inc.

Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness.

PubMed

Balcarras, Matthew; Ardid, Salva; Kaping, Daniel; Everling, Stefan; Womelsdorf, Thilo

2016-02-01

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

Flow-Based Network Analysis of the Caenorhabditis elegans Connectome

PubMed Central

Bacik, Karol A.; Schaub, Michael T.; Billeh, Yazan N.; Barahona, Mauricio

2016-01-01

We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios. PMID:27494178

Topological dimension tunes activity patterns in hierarchical modular networks

NASA Astrophysics Data System (ADS)

Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.

2017-11-01

Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.

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

PubMed Central

Mao, Wei B.; An, Shu; Yang, Xiao F.

2017-01-01

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. PMID:28790943

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

PubMed

Mao, Wei B; An, Shu; Yang, Xiao F

2017-01-01

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.

Detection of Lipid and Amphiphilic Biomarkers for Disease Diagnostics

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

Kubicek-Sutherland, Jessica Z.; Vu, Dung M.; Mendez, Heather M.

Rapid diagnosis is crucial to effectively treating any disease. Biological markers, or biomarkers, have been widely used to diagnose a variety of infectious and non-infectious diseases. The detection of biomarkers in patient samples can also provide valuable information regarding progression and prognosis. Interestingly, many such biomarkers are composed of lipids, and are amphiphilic in biochemistry, which leads them to be often sequestered by host carriers. Such sequestration enhances the difficulty of developing sensitive and accurate sensors for these targets. Many of the physiologically relevant molecules involved in pathogenesis and disease are indeed amphiphilic. This chemical property is likely essential formore » their biological function, but also makes them challenging to detect and quantify in vitro. In order to understand pathogenesis and disease progression while developing effective diagnostics, it is important to account for the biochemistry of lipid and amphiphilic biomarkers when creating novel techniques for the quantitative measurement of these targets. Here, we review techniques and methods used to detect lipid and amphiphilic biomarkers associated with disease, as well as their feasibility for use as diagnostic targets, highlighting the significance of their biochemical properties in the design and execution of laboratory and diagnostic strategies. Furthermore, the biochemistry of biological molecules is clearly relevant to their physiological function, and calling out the need for consideration of this feature in their study, and use as vaccine, diagnostic and therapeutic targets is the overarching motivation for this review.« less

Muscle dysfunction in chronic obstructive pulmonary disease: update on causes and biological findings

PubMed Central

Pascual, Sergi; Casadevall, Carme; Orozco-Levi, Mauricio; Barreiro, Esther

2015-01-01

Respiratory and/or limb muscle dysfunction, which are frequently observed in chronic obstructive pulmonary disease (COPD) patients, contribute to their disease prognosis irrespective of the lung function. Muscle dysfunction is caused by the interaction of local and systemic factors. The key deleterious etiologic factors are pulmonary hyperinflation for the respiratory muscles and deconditioning secondary to reduced physical activity for limb muscles. Nonetheless, cigarette smoke, systemic inflammation, nutritional abnormalities, exercise, exacerbations, anabolic insufficiency, drugs and comorbidities also seem to play a relevant role. All these factors modify the phenotype of the muscles, through the induction of several biological phenomena in patients with COPD. While respiratory muscles improve their aerobic phenotype (percentage of oxidative fibers, capillarization, mitochondrial density, enzyme activity in the aerobic pathways, etc.), limb muscles exhibit the opposite phenotype. In addition, both muscle groups show oxidative stress, signs of damage and epigenetic changes. However, fiber atrophy, increased number of inflammatory cells, altered regenerative capacity; signs of apoptosis and autophagy, and an imbalance between protein synthesis and breakdown are rather characteristic features of the limb muscles, mostly in patients with reduced body weight. Despite that significant progress has been achieved in the last decades, full elucidation of the specific roles of the target biological mechanisms involved in COPD muscle dysfunction is still required. Such an achievement will be crucial to adequately tackle with this relevant clinical problem of COPD patients in the near-future. PMID:26623119

Detection of Lipid and Amphiphilic Biomarkers for Disease Diagnostics

DOE PAGES

Kubicek-Sutherland, Jessica Z.; Vu, Dung M.; Mendez, Heather M.; ...

2017-07-04

Rapid diagnosis is crucial to effectively treating any disease. Biological markers, or biomarkers, have been widely used to diagnose a variety of infectious and non-infectious diseases. The detection of biomarkers in patient samples can also provide valuable information regarding progression and prognosis. Interestingly, many such biomarkers are composed of lipids, and are amphiphilic in biochemistry, which leads them to be often sequestered by host carriers. Such sequestration enhances the difficulty of developing sensitive and accurate sensors for these targets. Many of the physiologically relevant molecules involved in pathogenesis and disease are indeed amphiphilic. This chemical property is likely essential formore » their biological function, but also makes them challenging to detect and quantify in vitro. In order to understand pathogenesis and disease progression while developing effective diagnostics, it is important to account for the biochemistry of lipid and amphiphilic biomarkers when creating novel techniques for the quantitative measurement of these targets. Here, we review techniques and methods used to detect lipid and amphiphilic biomarkers associated with disease, as well as their feasibility for use as diagnostic targets, highlighting the significance of their biochemical properties in the design and execution of laboratory and diagnostic strategies. Furthermore, the biochemistry of biological molecules is clearly relevant to their physiological function, and calling out the need for consideration of this feature in their study, and use as vaccine, diagnostic and therapeutic targets is the overarching motivation for this review.« less

Characterization of 2,3-diarylxanthones by electrospray mass spectrometry: gas-phase chemistry versus known antioxidant activity properties.

PubMed

Silva, Eduarda M P; Barros, Cristina M R F; Santos, Clementina M M; Barros, António S; Domingues, M Rosário M; Silva, Artur M S

2016-10-30

Xanthones (XH) are a class of heterocyclic compounds widely distributed in nature that hold numerous noteworthy biological and antioxidant activities. Therefore, it is of utmost importance to achieve relevant detailed structural information to understand and assist prediction of their biological properties. The potential relationship between radical-mediated xanthone chemistry in the gas phase and their promising antioxidant activities has not been previously explored. Protonated xanthones XH1-9 were generated in the gas phase by electrospray ionization (ESI) and the main fragmentation pathways of the protonated XH1-9 formed due to collision-induced dissociation (CID) were investigated. In the CID-MS/MS spectra of [M+H](+) ions of XH1, XH2 and XH4 the product ions formed due to H2 O elimination corresponding to the base peak of the spectra. For the remaining six xanthones (XH3, XH5-9), showing the most promising biological profile, the product ion produced with the highest relative abundance (RA) corresponded to the one formed through concomitant loss of H2 O plus CO. Indicative of an inexistent or lower biological activity is the combined loss of CO plus O unique to the CID-MS/MS spectra of XH1, XH2, XH4, and XH5. The product ion formed by loss of 64 Da (concomitant loss of two molecules of H2 O plus CO) is only observed for xanthones containing a catechol unit (XH3 and XH6-9). This product ion has the highest RA for the most potent scavenger of reactive oxygen and nitrogen species XH9 that contains two of these catechol moieties. A strong relationship between some of the biological activities of the studied 2,3-diarylxanthones and their ESI-MS/MS fragmentation spectra was found. The multivariate statistical analysis results suggest that the selected MS features are related to the important biological features. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

PubMed

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 advantage to organisms? Is the magic ascribed to the number 7 of relevance? We hypothesize the 7 d time structure of human beings is endogenous in origin - a hypothesis that is affirmed by a wide array of evidence - and synchronized by sociocultural factors linked to the Saturday (Hebrews) or Sunday (Christian) holy day of rest. We also hypothesize they are representative, at least in part, of the biological requirement for rest and repair 1 d each 7 d, just as the circadian time structure is representative, in part, of the biological need for rest and repair each 24 h.

Making Plant Biology Curricula Relevant.

ERIC Educational Resources Information Center

Hershey, David R.

1992-01-01

Reviews rationale, purposes, challenges, and relevance of hands-on, plant biology curricula that have been developed in response to the limited use of plants in biology education. Discusses methods to maintain both instructional rigor and student interest in the following topics: cut flowers, container-growing media, fertilizers, hydroponics,…

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

PubMed

Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

PubMed Central

Chen, Yi-An; Tripathi, Lokesh P.; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org PMID:26989145

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

PubMed

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.

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

PubMed Central

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

2016-01-01

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. PMID:27792168

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM.

PubMed

Allen Li, X; Alber, Markus; Deasy, Joseph O; Jackson, Andrew; Ken Jee, Kyung-Wook; Marks, Lawrence B; Martel, Mary K; Mayo, Charles; Moiseenko, Vitali; Nahum, Alan E; Niemierko, Andrzej; Semenenko, Vladimir A; Yorke, Ellen D

2012-03-01

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

USSR Space Life Sciences Digest, issue 7

NASA Technical Reports Server (NTRS)

Hooke, L. R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor); Teeter, R. (Editor)

1986-01-01

This is the seventh issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 29 papers recently published in Russian language periodicals and bound collections and of 8 new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. Additional features include two interviews with the Soviet Union's cosmonaut physicians and others knowledgable of the Soviet space program. The topics discussed at a Soviet conference on problems in space psychology are summarized. Information about English translations of Soviet materials available to readers is provided. The topics covered in this issue have been identified as relevant to 29 areas of aerospace medicine and space biology. These areas are adaptation, biospherics, body fluids, botany, cardiovascular and respiratory systems, developmental biology, endocrinology, enzymology, exobiology, genetics, habitability and environment effects, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism, microbiology, morphology and cytology, musculoskeletal system, neurophysiology, nutrition, perception, personnel selection, psychology, radiobiology, and space medicine.

In vitro DNA SCRaMbLE.

PubMed

Wu, Yi; Zhu, Rui-Ying; Mitchell, Leslie A; Ma, Lu; Liu, Rui; Zhao, Meng; Jia, Bin; Xu, Hui; Li, Yun-Xiang; Yang, Zu-Ming; Ma, Yuan; Li, Xia; Liu, Hong; Liu, Duo; Xiao, Wen-Hai; Zhou, Xiao; Li, Bing-Zhi; Yuan, Ying-Jin; Boeke, Jef D

2018-05-22

The power of synthetic biology has enabled the expression of heterologous pathways in cells, as well as genome-scale synthesis projects. The complexity of biological networks makes rational de novo design a grand challenge. Introducing features that confer genetic flexibility is a powerful strategy for downstream engineering. Here we develop an in vitro method of DNA library construction based on structural variation to accomplish this goal. The "in vitro SCRaMbLE system" uses Cre recombinase mixed in a test tube with purified DNA encoding multiple loxPsym sites. Using a β-carotene pathway designed for expression in yeast as an example, we demonstrate top-down and bottom-up in vitro SCRaMbLE, enabling optimization of biosynthetic pathway flux via the rearrangement of relevant transcription units. We show that our system provides a straightforward way to correlate phenotype and genotype and is potentially amenable to biochemical optimization in ways that the in vivo system cannot achieve.

Indoors forensic entomology: colonization of human remains in closed environments by specific species of sarcosaprophagous flies.

PubMed

Pohjoismäki, Jaakko L O; Karhunen, Pekka J; Goebeler, Sirkka; Saukko, Pekka; Sääksjärvi, Ilari E

2010-06-15

Fly species that are commonly recovered on human corpses concealed in houses or other dwellings are often dependent on human created environments and might have special features in their biology that allow them to colonize indoor cadavers. In this study we describe nine typical cases involving forensically relevant flies on human remains found indoors in southern Finland. Eggs, larvae and puparia were reared to adult stage and determined to species. Of the five species found the most common were Lucilia sericata Meigen, Calliphora vicina Robineau-Desvoidy and Protophormia terraenovae Robineau-Desvoidy. The flesh fly Sarcophaga caerulescens Zetterstedt is reported for the first time to colonize human cadavers inside houses and a COI gene sequence based DNA barcode is provided for it to help facilitate identification in the future. Fly biology, colonization speed and the significance of indoors forensic entomological evidence are discussed. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Natural products as an inspiration in the diversity-oriented synthesis of bioactive compound libraries

PubMed Central

Cordier, Christopher; Morton, Daniel; Murrison, Sarah; O'Leary-Steele, Catherine

2008-01-01

The purpose of diversity-oriented synthesis is to drive the discovery of small molecules with previously unknown biological functions. Natural products necessarily populate biologically relevant chemical space, since they bind both their biosynthetic enzymes and their target macromolecules. Natural product families are, therefore, libraries of pre-validated, functionally diverse structures in which individual compounds selectively modulate unrelated macromolecular targets. This review describes examples of diversity-oriented syntheses which have, to some extent, been inspired by the structures of natural products. Particular emphasis is placed on innovations that allow the synthesis of compound libraries that, like natural products, are skeletally diverse. Mimicking the broad structural features of natural products may allow the discovery of compounds that modulate the functions of macromolecules for which ligands are not known. The ability of innovations in diversity-oriented synthesis to deliver such compounds is critically assessed. PMID:18663392

Whole genome DNA methylation: beyond genes silencing.

PubMed

Tirado-Magallanes, Roberto; Rebbani, Khadija; Lim, Ricky; Pradhan, Sriharsa; Benoukraf, Touati

2017-01-17

The combination of DNA bisulfite treatment with high-throughput sequencing technologies has enabled investigation of genome-wide DNA methylation at near base pair level resolution, far beyond that of the kilobase-long canonical CpG islands that initially revealed the biological relevance of this covalent DNA modification. The latest high-resolution studies have revealed a role for very punctual DNA methylation in chromatin plasticity, gene regulation and splicing. Here, we aim to outline the major biological consequences of DNA methylation recently discovered. We also discuss the necessity of tuning DNA methylation resolution into an adequate scale to ease the integration of the methylome information with other chromatin features and transcription events such as gene expression, nucleosome positioning, transcription factors binding dynamic, gene splicing and genomic imprinting. Finally, our review sheds light on DNA methylation heterogeneity in cell population and the different approaches used for its assessment, including the contribution of single cell DNA analysis technology.

Whole genome DNA methylation: beyond genes silencing

PubMed Central

Tirado-Magallanes, Roberto; Rebbani, Khadija; Lim, Ricky; Pradhan, Sriharsa; Benoukraf, Touati

2017-01-01

The combination of DNA bisulfite treatment with high-throughput sequencing technologies has enabled investigation of genome-wide DNA methylation at near base pair level resolution, far beyond that of the kilobase-long canonical CpG islands that initially revealed the biological relevance of this covalent DNA modification. The latest high-resolution studies have revealed a role for very punctual DNA methylation in chromatin plasticity, gene regulation and splicing. Here, we aim to outline the major biological consequences of DNA methylation recently discovered. We also discuss the necessity of tuning DNA methylation resolution into an adequate scale to ease the integration of the methylome information with other chromatin features and transcription events such as gene expression, nucleosome positioning, transcription factors binding dynamic, gene splicing and genomic imprinting. Finally, our review sheds light on DNA methylation heterogeneity in cell population and the different approaches used for its assessment, including the contribution of single cell DNA analysis technology. PMID:27895318

Life is physics and chemistry and communication.

PubMed

Witzany, Guenther

2015-04-01

Manfred Eigen extended Erwin Schroedinger's concept of "life is physics and chemistry" through the introduction of information theory and cybernetic systems theory into "life is physics and chemistry and information." Based on this assumption, Eigen developed the concepts of quasispecies and hypercycles, which have been dominant in molecular biology and virology ever since. He insisted that the genetic code is not just used metaphorically: it represents a real natural language. However, the basics of scientific knowledge changed dramatically within the second half of the 20th century. Unfortunately, Eigen ignored the results of the philosophy of science discourse on essential features of natural languages and codes: a natural language or code emerges from populations of living agents that communicate. This contribution will look at some of the highlights of this historical development and the results relevant for biological theories about life. © 2014 New York Academy of Sciences.

Epigenetic Regulation in Prostate Cancer Progression.

PubMed

Ruggero, Katia; Farran-Matas, Sonia; Martinez-Tebar, Adrian; Aytes, Alvaro

2018-01-01

An important number of newly identified molecular alterations in prostate cancer affect gene encoding master regulators of chromatin biology epigenetic regulation. This review will provide an updated view of the key epigenetic mechanisms underlying prostate cancer progression, therapy resistance, and potential actionable mechanisms and biomarkers. Key players in chromatin biology and epigenetic master regulators has been recently described to be crucially altered in metastatic CRPC and tumors that progress to AR independency. As such, epigenetic dysregulation represents a driving mechanism in the reprograming of prostate cancer cells as they lose AR-imposed identity. Chromatin integrity and accessibility for transcriptional regulation are key features altered in cancer progression, and particularly relevant in nuclear hormone receptor-driven tumors like prostate cancer. Understanding how chromatin remodeling dictates prostate development and how its deregulation contributes to prostate cancer onset and progression may improve risk stratification and treatment selection for prostate cancer patients.

Auditory-visual object recognition time suggests specific processing for animal sounds.

PubMed

Suied, Clara; Viaud-Delmon, Isabelle

2009-01-01

Recognizing an object requires binding together several cues, which may be distributed across different sensory modalities, and ignoring competing information originating from other objects. In addition, knowledge of the semantic category of an object is fundamental to determine how we should react to it. Here we investigate the role of semantic categories in the processing of auditory-visual objects. We used an auditory-visual object-recognition task (go/no-go paradigm). We compared recognition times for two categories: a biologically relevant one (animals) and a non-biologically relevant one (means of transport). Participants were asked to react as fast as possible to target objects, presented in the visual and/or the auditory modality, and to withhold their response for distractor objects. A first main finding was that, when participants were presented with unimodal or bimodal congruent stimuli (an image and a sound from the same object), similar reaction times were observed for all object categories. Thus, there was no advantage in the speed of recognition for biologically relevant compared to non-biologically relevant objects. A second finding was that, in the presence of a biologically relevant auditory distractor, the processing of a target object was slowed down, whether or not it was itself biologically relevant. It seems impossible to effectively ignore an animal sound, even when it is irrelevant to the task. These results suggest a specific and mandatory processing of animal sounds, possibly due to phylogenetic memory and consistent with the idea that hearing is particularly efficient as an alerting sense. They also highlight the importance of taking into account the auditory modality when investigating the way object concepts of biologically relevant categories are stored and retrieved.

Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

PubMed Central

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

Background 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. Methodology/Principal Findings 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 () and latency of the optimized engineered gene networks. Conclusions/Significance 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. PMID:21850228

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

PubMed

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.

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

PubMed Central

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

Ecological relevance of current water quality assessment unit designations in impaired rivers

USGS Publications Warehouse

Layhee, Megan J.; Sepulveda, Adam; Ray, Andrew; Mladenka, Greg; Van Every, Lynn

2016-01-01

Managers often nest sections of water bodies together into assessment units (AUs) to monitor and assess water quality criteria. Ideally, AUs represent an extent of waters with similar ecological, watershed, habitat and land-use conditions and no overlapping characteristics with other waters. In the United States, AUs are typically based on political or hydrologic boundaries rather than on ecologically relevant features, so it can be difficult to detect changes in impairment status. Our goals were to evaluate if current AU designation criteria of an impaired water body in southeastern Idaho, USA that, like many U.S. waters, has three-quarters of its mainstem length divided into two AUs. We focused our evaluation in southeastern Idaho's Portneuf River, an impaired river and three-quarters of the river is divided into two AUs. We described biological and environmental conditions at multiple reaches within each AU. We used these data to (1) test if variability at the reach-scale is greater within or among AUs and, (2) to evaluate alternate AU boundaries based on multivariate analyses of reach-scale data. We found that some biological conditions had greater variability within an AU than between AUs. Multivariate analyses identified alternative, 2- and 3-group, AUs that reduced this variability. Our results suggest that the current AU designations in the mainstem Portneuf River contain ecologically distinct sections of river and that the existing AU boundaries should be reconsidered in light of the ecological conditions measured at the reach scale. Variation in biological integrity within designated AUs may complicate water quality and biological assessments, influence management decisions or affect where monitoring or mitigation resources are directed.

Irrelevant reward and selection histories have different influences on task-relevant attentional selection.

PubMed

MacLean, Mary H; Giesbrecht, Barry

2015-07-01

Task-relevant and physically salient features influence visual selective attention. In the present study, we investigated the influence of task-irrelevant and physically nonsalient reward-associated features on visual selective attention. Two hypotheses were tested: One predicts that the effects of target-defining task-relevant and task-irrelevant features interact to modulate visual selection; the other predicts that visual selection is determined by the independent combination of relevant and irrelevant feature effects. These alternatives were tested using a visual search task that contained multiple targets, placing a high demand on the need for selectivity, and that was data-limited and required unspeeded responses, emphasizing early perceptual selection processes. One week prior to the visual search task, participants completed a training task in which they learned to associate particular colors with a specific reward value. In the search task, the reward-associated colors were presented surrounding targets and distractors, but were neither physically salient nor task-relevant. In two experiments, the irrelevant reward-associated features influenced performance, but only when they were presented in a task-relevant location. The costs induced by the irrelevant reward-associated features were greater when they oriented attention to a target than to a distractor. In a third experiment, we examined the effects of selection history in the absence of reward history and found that the interaction between task relevance and selection history differed, relative to when the features had previously been associated with reward. The results indicate that under conditions that demand highly efficient perceptual selection, physically nonsalient task-irrelevant and task-relevant factors interact to influence visual selective attention.

Intentional attention switching in dichotic listening: exploring the efficiency of nonspatial and spatial selection.

PubMed

Lawo, Vera; Fels, Janina; Oberem, Josefa; Koch, Iring

2014-10-01

Using an auditory variant of task switching, we examined the ability to intentionally switch attention in a dichotic-listening task. In our study, participants responded selectively to one of two simultaneously presented auditory number words (spoken by a female and a male, one for each ear) by categorizing its numerical magnitude. The mapping of gender (female vs. male) and ear (left vs. right) was unpredictable. The to-be-attended feature for gender or ear, respectively, was indicated by a visual selection cue prior to auditory stimulus onset. In Experiment 1, explicitly cued switches of the relevant feature dimension (e.g., from gender to ear) and switches of the relevant feature within a dimension (e.g., from male to female) occurred in an unpredictable manner. We found large performance costs when the relevant feature switched, but switches of the relevant feature dimension incurred only small additional costs. The feature-switch costs were larger in ear-relevant than in gender-relevant trials. In Experiment 2, we replicated these findings using a simplified design (i.e., only within-dimension switches with blocked dimensions). In Experiment 3, we examined preparation effects by manipulating the cueing interval and found a preparation benefit only when ear was cued. Together, our data suggest that the large part of attentional switch costs arises from reconfiguration at the level of relevant auditory features (e.g., left vs. right) rather than feature dimensions (ear vs. gender). Additionally, our findings suggest that ear-based target selection benefits more from preparation time (i.e., time to direct attention to one ear) than gender-based target selection.

Development of a two-stage gene selection method that incorporates a novel hybrid approach using the cuckoo optimization algorithm and harmony search for cancer classification.

PubMed

Elyasigomari, V; Lee, D A; Screen, H R C; Shaheed, M H

2017-03-01

For each cancer type, only a few genes are informative. Due to the so-called 'curse of dimensionality' problem, the gene selection task remains a challenge. To overcome this problem, we propose a two-stage gene selection method called MRMR-COA-HS. In the first stage, the minimum redundancy and maximum relevance (MRMR) feature selection is used to select a subset of relevant genes. The selected genes are then fed into a wrapper setup that combines a new algorithm, COA-HS, using the support vector machine as a classifier. The method was applied to four microarray datasets, and the performance was assessed by the leave one out cross-validation method. Comparative performance assessment of the proposed method with other evolutionary algorithms suggested that the proposed algorithm significantly outperforms other methods in selecting a fewer number of genes while maintaining the highest classification accuracy. The functions of the selected genes were further investigated, and it was confirmed that the selected genes are biologically relevant to each cancer type. Copyright © 2017. Published by Elsevier Inc.

A three-dimensional comparison of a morphometric and conventional cephalometric midsagittal planes for craniofacial asymmetry.

PubMed

Damstra, Janalt; Fourie, Zacharias; De Wit, Marnix; Ren, Yijin

2012-02-01

Morphometric methods are used in biology to study object symmetry in living organisms and to determine the true plane of symmetry. The aim of this study was to determine if there are clinical differences between three-dimensional (3D) cephalometric midsagittal planes used to describe craniofacial asymmetry and a true symmetry plane derived from a morphometric method based on visible facial features. The sample consisted of 14 dry skulls (9 symmetric and 5 asymmetric) with metallic markers which were imaged with cone-beam computed tomography. An error study and statistical analysis were performed to validate the morphometric method. The morphometric and conventional cephalometric planes were constructed and compared. The 3D cephalometric planes constructed as perpendiculars to the Frankfort horizontal plane resembled the morphometric plane the most in both the symmetric and asymmetric groups with mean differences of less than 1.00 mm for most variables. However, the standard deviations were often large and clinically significant for these variables. There were clinically relevant differences (>1.00 mm) between the different 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features. The difference between 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features were clinically relevant. Care has to be taken using cephalometric midsagittal planes for diagnosis and treatment planning of craniofacial asymmetry as they might differ from the true plane of symmetry as determined by morphometrics.

Desktop Nanofabrication with Massively Multiplexed Beam Pen Lithography

PubMed Central

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

2013-01-01

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

Network-induced oscillatory behavior in material flow networks and irregular business cycles

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Lämmer, Stefen; Witt, Ulrich; Brenner, Thomas

2004-11-01

Network theory is rapidly changing our understanding of complex systems, but the relevance of topological features for the dynamic behavior of metabolic networks, food webs, production systems, information networks, or cascade failures of power grids remains to be explored. Based on a simple model of supply networks, we offer an interpretation of instabilities and oscillations observed in biological, ecological, economic, and engineering systems. We find that most supply networks display damped oscillations, even when their units—and linear chains of these units—behave in a nonoscillatory way. Moreover, networks of damped oscillators tend to produce growing oscillations. This surprising behavior offers, for example, a different interpretation of business cycles and of oscillating or pulsating processes. The network structure of material flows itself turns out to be a source of instability, and cyclical variations are an inherent feature of decentralized adjustments.

Desktop nanofabrication with massively multiplexed beam pen lithography.

PubMed

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

2013-01-01

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

78 FR 16828 - Endangered and Threatened Wildlife and Plants; Status Review of the West Coast Distinct...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-19

...; biology and ecology; and habitat selection. (2) Information on the effects of potential threat factors... particular physical or biological features that are essential to the conservation of the species and where such physical or biological features are found; (c) Whether any of these features may require special...

Cell Biology of the Caenorhabditis elegans Nucleus

PubMed Central

Cohen-Fix, Orna; Askjaer, Peter

2017-01-01

Studies on the Caenorhabditis elegans nucleus have provided fascinating insight to the organization and activities of eukaryotic cells. Being the organelle that holds the genetic blueprint of the cell, the nucleus is critical for basically every aspect of cell biology. The stereotypical development of C. elegans from a one cell-stage embryo to a fertile hermaphrodite with 959 somatic nuclei has allowed the identification of mutants with specific alterations in gene expression programs, nuclear morphology, or nuclear positioning. Moreover, the early C. elegans embryo is an excellent model to dissect the mitotic processes of nuclear disassembly and reformation with high spatiotemporal resolution. We review here several features of the C. elegans nucleus, including its composition, structure, and dynamics. We also discuss the spatial organization of chromatin and regulation of gene expression and how this depends on tight control of nucleocytoplasmic transport. Finally, the extensive connections of the nucleus with the cytoskeleton and their implications during development are described. Most processes of the C. elegans nucleus are evolutionarily conserved, highlighting the relevance of this powerful and versatile model organism to human biology. PMID:28049702

An optimal transportation approach for nuclear structure-based pathology.

PubMed

Wang, Wei; Ozolek, John A; Slepčev, Dejan; Lee, Ann B; Chen, Cheng; Rohde, Gustavo K

2011-03-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g., normal versus cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers.

Ensemble transcript interaction networks: a case study on Alzheimer's disease.

PubMed

Armañanzas, Rubén; Larrañaga, Pedro; Bielza, Concha

2012-10-01

Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

An optimal transportation approach for nuclear structure-based pathology

PubMed Central

Wang, Wei; Ozolek, John A.; Slepčev, Dejan; Lee, Ann B.; Chen, Cheng; Rohde, Gustavo K.

2012-01-01

Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue lesions. Precise quantitative information about nuclear structure and morphology, however, is currently not available for many diagnostic challenges. This is due, in part, to the lack of methods to quantify these differences from image data. We describe a method to characterize and contrast the distribution of nuclear structure in different tissue classes (normal, benign, cancer, etc.). The approach is based on quantifying chromatin morphology in different groups of cells using the optimal transportation (Kantorovich-Wasserstein) metric in combination with the Fisher discriminant analysis and multidimensional scaling techniques. We show that the optimal transportation metric is able to measure relevant biological information as it enables automatic determination of the class (e.g. normal vs. cancer) of a set of nuclei. We show that the classification accuracies obtained using this metric are, on average, as good or better than those obtained utilizing a set of previously described numerical features. We apply our methods to two diagnostic challenges for surgical pathology: one in the liver and one in the thyroid. Results automatically computed using this technique show potentially biologically relevant differences in nuclear structure in liver and thyroid cancers. PMID:20977984

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

PubMed

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.

ITALICS: an algorithm for normalization and DNA copy number calling for Affymetrix SNP arrays.

PubMed

Rigaill, Guillem; Hupé, Philippe; Almeida, Anna; La Rosa, Philippe; Meyniel, Jean-Philippe; Decraene, Charles; Barillot, Emmanuel

2008-03-15

Affymetrix SNP arrays can be used to determine the DNA copy number measurement of 11 000-500 000 SNPs along the genome. Their high density facilitates the precise localization of genomic alterations and makes them a powerful tool for studies of cancers and copy number polymorphism. Like other microarray technologies it is influenced by non-relevant sources of variation, requiring correction. Moreover, the amplitude of variation induced by non-relevant effects is similar or greater than the biologically relevant effect (i.e. true copy number), making it difficult to estimate non-relevant effects accurately without including the biologically relevant effect. We addressed this problem by developing ITALICS, a normalization method that estimates both biological and non-relevant effects in an alternate, iterative manner, accurately eliminating irrelevant effects. We compared our normalization method with other existing and available methods, and found that ITALICS outperformed these methods for several in-house datasets and one public dataset. These results were validated biologically by quantitative PCR. The R package ITALICS (ITerative and Alternative normaLIzation and Copy number calling for affymetrix Snp arrays) has been submitted to Bioconductor.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

DOE PAGES

Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken; ...

2016-11-29

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

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

Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

Evolving Relevance of Neuroproteomics in Alzheimer's Disease.

PubMed

Lista, Simone; Zetterberg, Henrik; O'Bryant, Sid E; Blennow, Kaj; Hampel, Harald

2017-01-01

Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.

Modeling anaplastic thyroid carcinoma in the mouse.

PubMed

Champa, Devora; Di Cristofano, Antonio

2015-02-01

Anaplastic thyroid carcinoma is the least common form of thyroid cancer; however, it accounts for the majority of deaths associated with this family of malignancies. A number of genetically engineered immunocompetent mouse models recapitulating the genetic and histological features of anaplastic thyroid cancer have been very recently generated and represent an invaluable tool to dissect the mechanisms involved in the progression from indolent, well-differentiated tumors to aggressive, undifferentiated carcinomas and to identify novel therapeutic targets. In this review, we focus on the relevant characteristics associated with these models and on what we have learned in terms of anaplastic thyroid cancer biology, genetics, and response to targeted therapy.

Modeling anaplastic thyroid carcinoma in the mouse

PubMed Central

Champa, Devora; Di Cristofano, Antonio

2014-01-01

Anaplastic thyroid carcinoma is the least common form of thyroid cancer; however, it accounts for the majority of deaths associated with this family of malignancies. A number of genetically engineered immunocompetent mouse models recapitulating the genetic and histological features of anaplastic thyroid cancer have been very recently generated and represent an invaluable tool to dissect the mechanisms involved in the progression from indolent, well differentiated tumors to aggressive, undifferentiated carcinomas, and to identify novel therapeutic targets. In this review, we focus on the relevant characteristics associated with these models and on what we have learned in terms of anaplastic thyroid cancer biology, genetics, and response to targeted therapy. PMID:25420535

Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models

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

Esposito, Emilio Xavier, E-mail: emilio@exeResearch.com; The Chem21 Group, Inc., 1780 Wilson Drive, Lake Forest, IL 60045; Hopfinger, Anton J., E-mail: hopfingr@gmail.com

2015-10-01

Carbon nanotubes have become widely used in a variety of applications including biosensors and drug carriers. Therefore, the issue of carbon nanotube toxicity is increasingly an area of focus and concern. While previous studies have focused on the gross mechanisms of action relating to nanomaterials interacting with biological entities, this study proposes detailed mechanisms of action, relating to nanotoxicity, for a series of decorated (functionalized) carbon nanotube complexes based on previously reported QSAR models. Possible mechanisms of nanotoxicity for six endpoints (bovine serum albumin, carbonic anhydrase, chymotrypsin, hemoglobin along with cell viability and nitrogen oxide production) have been extracted frommore » the corresponding optimized QSAR models. The molecular features relevant to each of the endpoint respective mechanism of action for the decorated nanotubes are also discussed. Based on the molecular information contained within the optimal QSAR models for each nanotoxicity endpoint, either the decorator attached to the nanotube is directly responsible for the expression of a particular activity, irrespective of the decorator's 3D-geometry and independent of the nanotube, or those decorators having structures that place the functional groups of the decorators as far as possible from the nanotube surface most strongly influence the biological activity. These molecular descriptors are further used to hypothesize specific interactions involved in the expression of each of the six biological endpoints. - Highlights: • Proposed toxicity mechanism of action for decorated nanotubes complexes • Discussion of the key molecular features for each endpoint's mechanism of action • Unique mechanisms of action for each of the six biological systems • Hypothesized mechanisms of action based on QSAR/QNAR predictive models.« less

A Novel Multi-Class Ensemble Model for Classifying Imbalanced Biomedical Datasets

NASA Astrophysics Data System (ADS)

Bikku, Thulasi; Sambasiva Rao, N., Dr; Rao, Akepogu Ananda, Dr

2017-08-01

This paper mainly focuseson developing aHadoop based framework for feature selection and classification models to classify high dimensionality data in heterogeneous biomedical databases. Wide research has been performing in the fields of Machine learning, Big data and Data mining for identifying patterns. The main challenge is extracting useful features generated from diverse biological systems. The proposed model can be used for predicting diseases in various applications and identifying the features relevant to particular diseases. There is an exponential growth of biomedical repositories such as PubMed and Medline, an accurate predictive model is essential for knowledge discovery in Hadoop environment. Extracting key features from unstructured documents often lead to uncertain results due to outliers and missing values. In this paper, we proposed a two phase map-reduce framework with text preprocessor and classification model. In the first phase, mapper based preprocessing method was designed to eliminate irrelevant features, missing values and outliers from the biomedical data. In the second phase, a Map-Reduce based multi-class ensemble decision tree model was designed and implemented in the preprocessed mapper data to improve the true positive rate and computational time. The experimental results on the complex biomedical datasets show that the performance of our proposed Hadoop based multi-class ensemble model significantly outperforms state-of-the-art baselines.

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

PubMed Central

Alvarez-Meza, Andres M.; Orozco-Gutierrez, Alvaro; Castellanos-Dominguez, German

2017-01-01

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. PMID:29056897

FSR: feature set reduction for scalable and accurate multi-class cancer subtype classification based on copy number.

PubMed

Wong, Gerard; Leckie, Christopher; Kowalczyk, Adam

2012-01-15

Feature selection is a key concept in machine learning for microarray datasets, where features represented by probesets are typically several orders of magnitude larger than the available sample size. Computational tractability is a key challenge for feature selection algorithms in handling very high-dimensional datasets beyond a hundred thousand features, such as in datasets produced on single nucleotide polymorphism microarrays. In this article, we present a novel feature set reduction approach that enables scalable feature selection on datasets with hundreds of thousands of features and beyond. Our approach enables more efficient handling of higher resolution datasets to achieve better disease subtype classification of samples for potentially more accurate diagnosis and prognosis, which allows clinicians to make more informed decisions in regards to patient treatment options. We applied our feature set reduction approach to several publicly available cancer single nucleotide polymorphism (SNP) array datasets and evaluated its performance in terms of its multiclass predictive classification accuracy over different cancer subtypes, its speedup in execution as well as its scalability with respect to sample size and array resolution. Feature Set Reduction (FSR) was able to reduce the dimensions of an SNP array dataset by more than two orders of magnitude while achieving at least equal, and in most cases superior predictive classification performance over that achieved on features selected by existing feature selection methods alone. An examination of the biological relevance of frequently selected features from FSR-reduced feature sets revealed strong enrichment in association with cancer. FSR was implemented in MATLAB R2010b and is available at http://ww2.cs.mu.oz.au/~gwong/FSR.

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data. PMID:16438716

A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

PubMed

Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

2014-03-21

This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

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

PubMed

Lange, Matthias; Spies, Karl; Colmsee, Christian; Flemming, Steffen; Klapperstück, Matthias; Scholz, Uwe

2010-03-25

Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

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

PubMed

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.).

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

SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well representedmore » by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.« less

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

PubMed

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

Spectra-first feature analysis in clinical proteomics - A case study in renal cancer.

PubMed

Goh, Wilson Wen Bin; Wong, Limsoon

2016-10-01

In proteomics, useful signal may be unobserved or lost due to the lack of confident peptide-spectral matches. Selection of differential spectra, followed by associative peptide/protein mapping may be a complementary strategy for improving sensitivity and comprehensiveness of analysis (spectra-first paradigm). This approach is complementary to the standard approach where functional analysis is performed only on the finalized protein list assembled from identified peptides from the spectra (protein-first paradigm). Based on a case study of renal cancer, we introduce a simple spectra-binning approach, MZ-bin. We demonstrate that differential spectra feature selection using MZ-bin is class-discriminative and can trace relevant proteins via spectra associative mapping. Moreover, proteins identified in this manner are more biologically coherent than those selected directly from the finalized protein list. Analysis of constituent peptides per protein reveals high expression inconsistency, suggesting that the measured protein expressions are in fact, poor approximations of true protein levels. Moreover, analysis at the level of constituent peptides may provide higher resolution insight into the underlying biology: Via MZ-bin, we identified for the first time differential splice forms for the known renal cancer marker MAPT. We conclude that the spectra-first analysis paradigm is a complementary strategy to the traditional protein-first paradigm and can provide deeper level insight.

Which Features Make Illustrations in Multimedia Learning Interesting?

ERIC Educational Resources Information Center

Magner, Ulrike Irmgard Elisabeth; Glogger, Inga; Renkl, Alexander

2016-01-01

How can illustrations motivate learners in multimedia learning? Which features make illustrations interesting? Beside the theoretical relevance of addressing these questions, these issues are practically relevant when instructional designers are to decide which features of illustrations can trigger situational interest irrespective of individual…

Probing the Xenopus laevis inner ear transcriptome for biological function

PubMed Central

2012-01-01

Background The senses of hearing and balance depend upon mechanoreception, a process that originates in the inner ear and shares features across species. Amphibians have been widely used for physiological studies of mechanotransduction by sensory hair cells. In contrast, much less is known of the genetic basis of auditory and vestibular function in this class of animals. Among amphibians, the genus Xenopus is a well-characterized genetic and developmental model that offers unique opportunities for inner ear research because of the amphibian capacity for tissue and organ regeneration. For these reasons, we implemented a functional genomics approach as a means to undertake a large-scale analysis of the Xenopus laevis inner ear transcriptome through microarray analysis. Results Microarray analysis uncovered genes within the X. laevis inner ear transcriptome associated with inner ear function and impairment in other organisms, thereby supporting the inclusion of Xenopus in cross-species genetic studies of the inner ear. The use of gene categories (inner ear tissue; deafness; ion channels; ion transporters; transcription factors) facilitated the assignment of functional significance to probe set identifiers. We enhanced the biological relevance of our microarray data by using a variety of curation approaches to increase the annotation of the Affymetrix GeneChip® Xenopus laevis Genome array. In addition, annotation analysis revealed the prevalence of inner ear transcripts represented by probe set identifiers that lack functional characterization. Conclusions We identified an abundance of targets for genetic analysis of auditory and vestibular function. The orthologues to human genes with known inner ear function and the highly expressed transcripts that lack annotation are particularly interesting candidates for future analyses. We used informatics approaches to impart biologically relevant information to the Xenopus inner ear transcriptome, thereby addressing the impediment imposed by insufficient gene annotation. These findings heighten the relevance of Xenopus as a model organism for genetic investigations of inner ear organogenesis, morphogenesis, and regeneration. PMID:22676585

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

PubMed

Castro-Melchor, Marlene; Charaniya, Salim; Karypis, George; Takano, Eriko; Hu, Wei-Shou

2010-10-18

The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Rare cancers: a sea of opportunity.

PubMed

Boyd, Niki; Dancey, Janet E; Gilks, C Blake; Huntsman, David G

2016-02-01

Rare cancers, as a collective, account for around a quarter of all cancer diagnoses and deaths. Historically, they have been divided into two groups: cancers defined by their unusual histogenesis (cell of origin or differentiation state)--including chordomas or adult granulosa cell tumours--and histologically defined subtypes of common cancers. Most tumour types in the first group are still clinically and biologically relevant, and have been disproportionately important as sources of insight into cancer biology. By contrast, most of those in the second group have been shown to have neither defining molecular features nor clinical utility. Omics-based analyses have splintered common cancers into a myriad of molecularly, rather than histologically, defined subsets of common cancers, many of which have immediate clinical relevance. Now, almost all rare cancers are either histomolecular entities, which often have pathognomonic mutations, or molecularly defined subsets of more common cancers. The presence of specific genetic variants provides rationale for the testing of targeted drugs in rare cancers. However, in addition to molecular alterations, it is crucial to consider the contributions of both mutation and cell context in the development, biology, and behaviour of these cancers. Patients with rare cancers are disadvantaged because of the challenge of leading clinical trials in this setting due to poor accrual. However, the number of patients with rare cancers will only increase as more molecular subsets of common cancers are identified, necessitating a shift in the focus of clinical trials and research into these cancer types, which, by epidemiological definitions, will become rare tumours. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic Integration of Task-Relevant Visual Features in Posterior Parietal Cortex

PubMed Central

Freedman, David J.

2014-01-01

Summary The primate visual system consists of multiple hierarchically organized cortical areas, each specialized for processing distinct aspects of the visual scene. For example, color and form are encoded in ventral pathway areas such as V4 and inferior temporal cortex, while motion is preferentially processed in dorsal pathway areas such as the middle temporal area. Such representations often need to be integrated perceptually to solve tasks which depend on multiple features. We tested the hypothesis that the lateral intraparietal area (LIP) integrates disparate task-relevant visual features by recording from LIP neurons in monkeys trained to identify target stimuli composed of conjunctions of color and motion features. We show that LIP neurons exhibit integrative representations of both color and motion features when they are task relevant, and task-dependent shifts of both direction and color tuning. This suggests that LIP plays a role in flexibly integrating task-relevant sensory signals. PMID:25199703

Biological relevance of streamflow metrics: Regional and national perspectives

USGS Publications Warehouse

Carlisle, Daren M.; Grantham, Theodore E.; Eng, Kenny; Wolock, David M.

2017-01-01

Protecting the health of streams and rivers requires identifying ecologically significant attributes of the natural flow regime. Streamflow regimes are routinely quantified using a plethora of hydrologic metrics (HMs), most of which have unknown relevance to biological communities. At regional and national scales, we evaluated which of 509 commonly used HMs were associated with biological indicators of fish and invertebrate community integrity. We quantified alteration of each HM by using statistical models to predict site-specific natural baseline values for each of 728 sites across the USA where streamflow monitoring data were available concurrent with assessments of invertebrate or fish community integrity. We then ranked HMs according to their individual association with biological integrity based on random forest models that included HMs and other relevant covariates, such as land cover and stream chemistry. HMs were generally the most important predictors of biological integrity relative to the covariates. At a national scale, the most influential HMs were measures of depleted high flows, homogenization of flows, and erratic flows. Unique combinations of biologically relevant HMs were apparent among regions. We discuss the implications of our findings to the challenge of selecting HMs for streamflow research and management.

Statistical approach for selection of biologically informative genes.

PubMed

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 from high dimensional expression data for breeding and system biology studies. Published by Elsevier B.V.

Identifying Bottom-Up and Top-Down Components of Attentional Weight by Experimental Analysis and Computational Modeling

ERIC Educational Resources Information Center

Nordfang, Maria; Dyrholm, Mads; Bundesen, Claus

2013-01-01

The attentional weight of a visual object depends on the contrast of the features of the object to its local surroundings (feature contrast) and the relevance of the features to one's goals (feature relevance). We investigated the dependency in partial report experiments with briefly presented stimuli but unspeeded responses. The task was to…

Discovering the intelligence in molecular biology.

PubMed

Uberbacher, E

1995-12-01

The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.

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

DOE PAGES

Zawadowicz, Maria A.; Froyd, Karl D.; Murphy, Daniel M.; ...

2017-06-16

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. Here, 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 methodologymore » 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.« less

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

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

Zawadowicz, Maria A.; Froyd, Karl D.; Murphy, Daniel M.

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. Here, 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 methodologymore » 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.« less

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

NASA Astrophysics Data System (ADS)

Zawadowicz, Maria A.; Froyd, Karl D.; Murphy, Daniel M.; Cziczo, Daniel J.

2017-06-01

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.

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

PubMed

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.

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

PubMed

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.

Privileged structures: efficient chemical "navigators" toward unexplored biologically relevant chemical spaces.

PubMed

Kim, Jonghoon; Kim, Heejun; Park, Seung Bum

2014-10-22

In the search for new therapeutic agents for currently incurable diseases, attention has turned to traditionally "undruggable" targets, and collections of drug-like small molecules with high diversity and quality have become a prerequisite for new breakthroughs. To generate such collections, the diversity-oriented synthesis (DOS) strategy was developed, which aims to populate new chemical space with drug-like compounds containing a high degree of molecular diversity. The resulting DOS-derived libraries have been of great value for the discovery of various bioactive small molecules and therapeutic agents, and thus DOS has emerged as an essential tool in chemical biology and drug discovery. However, the key challenge has become how to design and synthesize drug-like small-molecule libraries with improved biological relevancy as well as maximum molecular diversity. This Perspective presents the development of privileged substructure-based DOS (pDOS), an efficient strategy for the construction of polyheterocyclic compound libraries with high biological relevancy. We envisioned the specific interaction of drug-like small molecules with certain biopolymers via the incorporation of privileged substructures into polyheterocyclic core skeletons. The importance of privileged substructures such as benzopyran, pyrimidine, and oxopiperazine in rigid skeletons was clearly demonstrated through the discovery of bioactive small molecules and the subsequent identification of appropriate target biomolecule using a method called "fluorescence difference in two-dimensional gel electrophoresis". Focusing on examples of pDOS-derived bioactive compounds with exceptional specificity, we discuss the capability of privileged structures to serve as chemical "navigators" toward biologically relevant chemical spaces. We also provide an outlook on chemical biology research and drug discovery using biologically relevant compound libraries constructed by pDOS, biology-oriented synthesis, or natural product-inspired DOS.

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

PubMed

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.

HUMAN BIOMONITORING TO LINK ENVIRONMENTAL EXPOSURE TO BIOLOGICALLY RELEVANT DOSE

EPA Science Inventory

The abstract and presentation on Human Biomonitoring to Link Environmental Exposure to Biologically Relevant Dose describes the use of biomarkers of exposure, biomarkers of current health state, and biomarker measurements. The abstract and presentation focuses on how biomarkers ...

Varying irrelevant phonetic features hinders learning of the feature being trained.

PubMed

Antoniou, Mark; Wong, Patrick C M

2016-01-01

Learning to distinguish nonnative words that differ in a critical phonetic feature can be difficult. Speech training studies typically employ methods that explicitly direct the learner's attention to the relevant nonnative feature to be learned. However, studies on vision have demonstrated that perceptual learning may occur implicitly, by exposing learners to stimulus features, even if they are irrelevant to the task, and it has recently been suggested that this task-irrelevant perceptual learning framework also applies to speech. In this study, subjects took part in a seven-day training regimen to learn to distinguish one of two nonnative features, namely, voice onset time or lexical tone, using explicit training methods consistent with most speech training studies. Critically, half of the subjects were exposed to stimuli that varied not only in the relevant feature, but in the irrelevant feature as well. The results showed that subjects who were trained with stimuli that varied in the relevant feature and held the irrelevant feature constant achieved the best learning outcomes. Varying both features hindered learning and generalization to new stimuli.

A Comprehensive Approach to Sequence-oriented IsomiR annotation (CASMIR): demonstration with IsomiR profiling in colorectal neoplasia.

PubMed

Wu, Chung Wah; Evans, Jared M; Huang, Shengbing; Mahoney, Douglas W; Dukek, Brian A; Taylor, William R; Yab, Tracy C; Smyrk, Thomas C; Jen, Jin; Kisiel, John B; Ahlquist, David A

2018-05-25

MicroRNA (miRNA) profiling is an important step in studying biological associations and identifying marker candidates. miRNA exists in isoforms, called isomiRs, which may exhibit distinct properties. With conventional profiling methods, limitations in assay and analysis platforms may compromise isomiR interrogation. We introduce a comprehensive approach to sequence-oriented isomiR annotation (CASMIR) to allow unbiased identification of global isomiRs from small RNA sequencing data. In this approach, small RNA reads are maintained as independent sequences instead of being summarized under miRNA names. IsomiR features are identified through step-wise local alignment against canonical forms and precursor sequences. Through customizing the reference database, CASMIR is applicable to isomiR annotation across species. To demonstrate its application, we investigated isomiR profiles in normal and neoplastic human colorectal epithelia. We also ran miRDeep2, a popular miRNA analysis algorithm to validate isomiRs annotated by CASMIR. With CASMIR, specific and biologically relevant isomiR patterns could be identified. We note that specific isomiRs are often more abundant than their canonical forms. We identify isomiRs that are commonly up-regulated in both colorectal cancer and advanced adenoma, and illustrate advantages in targeting isomiRs as potential biomarkers over canonical forms. Studying miRNAs at the isomiR level could reveal new insight into miRNA biology and inform assay design for specific isomiRs. CASMIR facilitates comprehensive annotation of isomiR features in small RNA sequencing data for isomiR profiling and differential expression analysis.

The Effect of Naturally Occurring Chronic Kidney Disease on the Micro-Structural and Mechanical Properties of Bone

PubMed Central

Meltzer, Hagar; Milrad, Moran; Brenner, Ori; Atkins, Ayelet; Shahar, Ron

2014-01-01

Chronic kidney disease (CKD) is a growing public health concern worldwide, and is associated with marked increase of bone fragility. Previous studies assessing the effect of CKD on bone quality were based on biopsies from human patients or on laboratory animal models. Such studies provide information of limited relevance due to the small size of the samples (biopsies) or the non-physiologic CKD syndrome studied (rodent models with artificially induced CKD). Furthermore, the type, architecture, structure and biology of the bone of rodents are remarkably different from human bones; therefore similar clinicopathologic circumstances may affect their bones differently. We describe the effects of naturally occurring CKD with features resembling human CKD on the skeleton of cats, whose bone biology, structure and composition are remarkably similar to those of humans. We show that CKD causes significant increase of resorption cavity density compared with healthy controls, as well as significantly lower cortical mineral density, cortical cross-sectional area and cortical cross-sectional thickness. Young's modulus, yield stress, and ultimate stress of the cortical bone material were all significantly decreased in the skeleton of CKD cats. Cancellous bone was also affected, having significantly lower trabecular thickness and bone volume over total volume in CKD cats compared with controls. This study shows that naturally occurring CKD has deleterious effects on bone quality and strength. Since many similarities exist between human and feline CKD patients, including the clinicopathologic features of the syndrome and bone microarchitecture and biology, these results contribute to better understanding of bone abnormalities associated with CKD. PMID:25333360

What causes the facing-the-viewer bias in biological motion?

PubMed

Weech, Séamas; McAdam, Matthew; Kenny, Sophie; Troje, Nikolaus F

2014-10-13

Orthographically projected biological motion point-light displays are generally ambiguous with respect to their orientation in depth, yet observers consistently prefer the facing-the-viewer interpretation. There has been discussion as to whether this bias can be attributed to the social relevance of biological motion stimuli or relates to local, low-level stimulus properties. In the present study we address this question. In Experiment 1, we compared the facing-the-viewer bias produced by a series of four stick figures and three human silhouettes that differed in posture, gender, and the presence versus absence of walking motion. Using a paradigm in which we asked observers to indicate the spinning direction of these figures, we found no bias when participants observed silhouettes, whereas a pronounced degree of bias was elicited by most stick figures. We hypothesized that the ambiguous surface normals on the lines and dots that comprise stick figures are prone to a visual bias that assumes surfaces to be convex. The local surface orientations of the occluding contours of silhouettes are unambiguous, and as such the convexity bias does not apply. In Experiment 2, we tested the role of local features in ambiguous surface perception by adding dots to the elbows and knees of silhouettes. We found biases consistent with the facing directions implied by a convex body surface. The results unify a number of findings regarding the facing-the-viewer bias. We conclude that the facing-the-viewer bias is established at the level of surface reconstruction from local image features rather than on a semantic level. © 2014 ARVO.

The Role of Feature Type and Causal Status in 4-5-Year-Old Children's Biological Categorizations

ERIC Educational Resources Information Center

Meunier, Benjamin; Cordier, Francoise

2009-01-01

The present study investigated the role of the causal status of features and feature type in biological categorizations by young children. Study 1 showed that 5-year-olds are more strongly influenced by causal features than effect features; 4-year-olds exhibit no such tendency. There therefore appears to be a conceptual change between the ages of…

Biologics in pediatric psoriasis - efficacy and safety.

PubMed

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 psoriasis in pediatric age group.

Quantum biology of the retina.

PubMed

Sia, Paul Ikgan; Luiten, André N; Stace, Thomas M; Wood, John Pm; Casson, Robert J

2014-08-01

The emerging field of quantum biology has led to a greater understanding of biological processes at the microscopic level. There is recent evidence to suggest that non-trivial quantum features such as entanglement, tunnelling and coherence have evolved in living systems. These quantum features are particularly evident in supersensitive light-harvesting systems such as in photosynthesis and photoreceptors. A biomimetic strategy utilizing biological quantum phenomena might allow new advances in the field of quantum engineering, particularly in quantum information systems. In addition, a better understanding of quantum biological features may lead to novel medical diagnostic and therapeutic developments. In the present review, we discuss the role of quantum physics in biological systems with an emphasis on the retina. © 2014 Royal Australian and New Zealand College of Ophthalmologists.

Terahertz Absorption and Circular Dichroism Spectroscopy of Solvated Biopolymers

NASA Astrophysics Data System (ADS)

Xu, Jing; Plaxco, Kevin; Allen, S. James

2006-03-01

Biopolymers are expected to exhibit broad spectral features in the terahertz frequency range, corresponding to their functionally relevant, global and sub-global collective vibrational modes with ˜ picosecond timescale. Recent advances in terahertz technology have stimulated researchers to employ terahertz absorption spectroscopy to directly probe these postulated collective modes. However, these pioneering studies have been limited to dry and, at best, moist samples. Successful isolation of low frequency vibrational activities of solvated biopolymers in their natural water environment has remained elusive, due to the overwhelming attenuation of the terahertz radiation by water. Here we have developed a terahertz absorption and circular dichroism spectrometer suitable for studying biopolymers in biologically relevant water solutions. We have precisely isolated, for the first time, the terahertz absorption of solvated prototypical proteins, Bovine Serum Albumin and Lysozyme, and made important direct comparison to the existing molecular dynamic simulations and normal mode calculations. We have also successfully demonstrated the magnetic circular dichroism in semiconductors, and placed upper bounds on the terahertz circular dichroism signatures of prototypical proteins in water solution.

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

PubMed

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.

Clinical metabolomics paves the way towards future healthcare strategies

PubMed Central

Collino, Sebastiano; Martin, François‐Pierre J.; Rezzi, Serge

2013-01-01

Metabolomics is recognized as a powerful top‐down system biological approach to understand genetic‐environment‐health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation. PMID:22348240

Clinico-Pathologic Relevance of Survivin Splice Variant Expression in Cancer

PubMed Central

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

2013-01-01

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

Galactic civilizations: Population dynamics and interstellar diffusion

NASA Technical Reports Server (NTRS)

Newman, W. I.; Sagan, C.

1978-01-01

The interstellar diffusion of galactic civilizations is reexamined by potential theory; both numerical and analytical solutions are derived for the nonlinear partial differential equations which specify a range of relevant models, drawn from blast wave physics, soil science, and, especially, population biology. An essential feature of these models is that, for all civilizations, population growth must be limited by the carrying capacity of the environment. Dispersal is fundamentally a diffusion process; a density-dependent diffusivity describes interstellar emigration. Two models are considered: the first describing zero population growth (ZPG), and the second which also includes local growth and saturation of a planetary population, and for which an asymptotic traveling wave solution is found.

Advanced alerting features: displaying new relevant data and retracting alerts.

PubMed Central

Kuperman, G. J.; Hiltz, F. L.; Teich, J. M.

1997-01-01

We added two advanced features to our automated alerting system. The first feature identifies and displays, at the time an alert is reviewed, relevant data filed between the login time of a specimen leading to an alerting result and the time the alert is reviewed. Relevant data is defined as data of the same kind as generated the alert. The other feature retracts alerts when the alerting value is edited and no longer satisfies the alerting criteria. We evaluated the two features for a 14-week period (new relevant data) and a 6-week period (retraction). Of a total of 1104 alerts in the 14-week evaluation, 286 (25.9%) had new relevant data displayed at alert review time. Of the 286, 75.2% were due to additions of comments to the original piece of alerting data; 24.1% were due to new or pending laboratory results of the same type that generated the alert. Two alerts (out of 490) were retracted in a 6 week period. We conclude that in our system, new clinically relevant data is often added between the time of specimen login and the time that an alerting result from that specimen is reviewed. Retractions occur rarely but are important to detect and communicate. PMID:9357625

Cascade detection for the extraction of localized sequence features; specificity results for HIV-1 protease and structure-function results for the Schellman loop.

PubMed

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.

Selection-for-action in visual search.

PubMed

Hannus, Aave; Cornelissen, Frans W; Lindemann, Oliver; Bekkering, Harold

2005-01-01

Grasping an object rather than pointing to it enhances processing of its orientation but not its color. Apparently, visual discrimination is selectively enhanced for a behaviorally relevant feature. In two experiments we investigated the limitations and targets of this bias. Specifically, in Experiment 1 we were interested to find out whether the effect is capacity demanding, therefore we manipulated the set-size of the display. The results indicated a clear cognitive processing capacity requirement, i.e. the magnitude of the effect decreased for a larger set size. Consequently, in Experiment 2, we investigated if the enhancement effect occurs only at the level of behaviorally relevant feature or at a level common to different features. Therefore we manipulated the discriminability of the behaviorally neutral feature (color). Again, results showed that this manipulation influenced the action enhancement of the behaviorally relevant feature. Particularly, the effect of the color manipulation on the action enhancement suggests that the action effect is more likely to bias the competition between different visual features rather than to enhance the processing of the relevant feature. We offer a theoretical account that integrates the action-intention effect within the biased competition model of visual selective attention.

In Vitro Modeling of Mechanics in Cancer Metastasis

PubMed Central

2017-01-01

In addition to a multitude of genetic and biochemical alterations, abnormal morphological, structural, and mechanical changes in cells and their extracellular environment are key features of tumor invasion and metastasis. Furthermore, it is now evident that mechanical cues alongside biochemical signals contribute to critical steps of cancer initiation, progression, and spread. Despite its importance, it is very challenging to study mechanics of different steps of metastasis in the clinic or even in animal models. While considerable progress has been made in developing advanced in vitro models for studying genetic and biological aspects of cancer, less attention has been paid to models that can capture both biological and mechanical factors realistically. This is mainly due to lack of appropriate models and measurement tools. After introducing the central role of mechanics in cancer metastasis, we provide an outlook on the emergence of novel in vitro assays and their combination with advanced measurement technologies to probe and recapitulate mechanics in conditions more relevant to the metastatic disease. PMID:29457129

The transcriptional landscape of age in human peripheral blood

PubMed Central

Peters, Marjolein J.; Joehanes, Roby; Pilling, Luke C.; Schurmann, Claudia; Conneely, Karen N.; Powell, Joseph; Reinmaa, Eva; Sutphin, George L.; Zhernakova, Alexandra; Schramm, Katharina; Wilson, Yana A.; Kobes, Sayuko; Tukiainen, Taru; Nalls, Michael A.; Hernandez, Dena G.; Cookson, Mark R.; Gibbs, Raphael J.; Hardy, John; Ramasamy, Adaikalavan; Zonderman, Alan B.; Dillman, Allissa; Traynor, Bryan; Smith, Colin; Longo, Dan L.; Trabzuni, Daniah; Troncoso, Juan; van der Brug, Marcel; Weale, Michael E.; O'Brien, Richard; Johnson, Robert; Walker, Robert; Zielke, Ronald H.; Arepalli, Sampath; Ryten, Mina; Singleton, Andrew B.; Ramos, Yolande F.; Göring, Harald H. H.; Fornage, Myriam; Liu, Yongmei; Gharib, Sina A.; Stranger, Barbara E.; De Jager, Philip L.; Aviv, Abraham; Levy, Daniel; Murabito, Joanne M.; Munson, Peter J.; Huan, Tianxiao; Hofman, Albert; Uitterlinden, André G.; Rivadeneira, Fernando; van Rooij, Jeroen; Stolk, Lisette; Broer, Linda; Verbiest, Michael M. P. J.; Jhamai, Mila; Arp, Pascal; Metspalu, Andres; Tserel, Liina; Milani, Lili; Samani, Nilesh J.; Peterson, Pärt; Kasela, Silva; Codd, Veryan; Peters, Annette; Ward-Caviness, Cavin K.; Herder, Christian; Waldenberger, Melanie; Roden, Michael; Singmann, Paula; Zeilinger, Sonja; Illig, Thomas; Homuth, Georg; Grabe, Hans-Jörgen; Völzke, Henry; Steil, Leif; Kocher, Thomas; Murray, Anna; Melzer, David; Yaghootkar, Hanieh; Bandinelli, Stefania; Moses, Eric K.; Kent, Jack W.; Curran, Joanne E.; Johnson, Matthew P.; Williams-Blangero, Sarah; Westra, Harm-Jan; McRae, Allan F.; Smith, Jennifer A.; Kardia, Sharon L. R.; Hovatta, Iiris; Perola, Markus; Ripatti, Samuli; Salomaa, Veikko; Henders, Anjali K.; Martin, Nicholas G.; Smith, Alicia K.; Mehta, Divya; Binder, Elisabeth B.; Nylocks, K Maria; Kennedy, Elizabeth M.; Klengel, Torsten; Ding, Jingzhong; Suchy-Dicey, Astrid M.; Enquobahrie, Daniel A.; Brody, Jennifer; Rotter, Jerome I.; Chen, Yii-Der I.; Houwing-Duistermaat, Jeanine; Kloppenburg, Margreet; Slagboom, P. Eline; Helmer, Quinta; den Hollander, Wouter; Bean, Shannon; Raj, Towfique; Bakhshi, Noman; Wang, Qiao Ping; Oyston, Lisa J.; Psaty, Bruce M.; Tracy, Russell P.; Montgomery, Grant W.; Turner, Stephen T.; Blangero, John; Meulenbelt, Ingrid; Ressler, Kerry J.; Yang, Jian; Franke, Lude; Kettunen, Johannes; Visscher, Peter M.; Neely, G. Gregory; Korstanje, Ron; Hanson, Robert L.; Prokisch, Holger; Ferrucci, Luigi; Esko, Tonu; Teumer, Alexander; van Meurs, Joyce B. J.; Johnson, Andrew D.

2015-01-01

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts. PMID:26490707

Basal-like Breast Cancers: From Pathology to Biology and Back Again.

PubMed

Gusterson, Barry; Eaves, Connie J

2018-06-05

Human breast cancers referred to as "basal-like" are of interest because they lack effective therapies and their biology is poorly understood. The term basal-like derives from studies demonstrating tumor gene expression profiles that include some transcripts characteristic of the basal cells of the normal adult human mammary gland and others associated with a subset of normal luminal cells. Elucidating the mechanisms responsible for the profiles of basal-like tumors is an active area of investigation. More refined molecular analysis of patients' samples and genetic strategies to produce breast cancers de novo from defined populations of normal mouse mammary cells have served as complementary approaches to identify relevant pathway alterations. However, both also have limitations. Here, we review some of the underlying reasons, including the unifying concept that some normal luminal cells have both luminal and basal features, as well as some emerging new avenues of investigation. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Emergent explosive synchronization in adaptive complex networks

NASA Astrophysics Data System (ADS)

Avalos-Gaytán, Vanesa; Almendral, Juan A.; Leyva, I.; Battiston, F.; Nicosia, V.; Latora, V.; Boccaletti, S.

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

Cross-platform comparison of nucleic acid hybridization: toward quantitative reference standards.

PubMed

Halvorsen, Ken; Agris, Paul F

2014-11-15

Measuring interactions between biological molecules is vitally important to both basic and applied research as well as development of pharmaceuticals. Although a wide and growing range of techniques is available to measure various kinetic and thermodynamic properties of interacting biomolecules, it can be difficult to compare data across techniques of different laboratories and personnel or even across different instruments using the same technique. Here we evaluate relevant biological interactions based on complementary DNA and RNA oligonucleotides that could be used as reference standards for many experimental systems. We measured thermodynamics of duplex formation using isothermal titration calorimetry, differential scanning calorimetry, and ultraviolet-visible (UV-vis) monitored denaturation/renaturation. These standards can be used to validate results, compare data from disparate techniques, act as a teaching tool for laboratory classes, or potentially to calibrate instruments. The RNA and DNA standards have many attractive features, including low cost, high purity, easily measurable concentrations, and minimal handling concerns, making them ideal for use as a reference material. Copyright © 2014 Elsevier Inc. All rights reserved.

Cross-platform comparison of nucleic acid hybridization: toward quantitative reference standardsa

PubMed Central

Halvorsen, Ken; Agris, Paul F.

2014-01-01

Measuring interactions between biological molecules is vitally important to both basic and applied research, as well as development of pharmaceuticals. While a wide and growing range of techniques are available to measure various kinetic and thermodynamic properties of interacting biomolecules, it can be difficult to compare data across techniques of different laboratories and personnel, or even across different instruments using the same technique. Here we evaluate relevant biological interactions based on complementary DNA and RNA oligonucleotides that could be used as reference standards for many experimental systems. We measured thermodynamics of duplex formation using Isothermal Titration Calorimetry, Differential Scanning Calorimetry, and UV-Vis monitored denaturation/renaturation. These standards can be used to validate results, compare data from disparate techniques, act as a teaching tool for laboratory classes, or potentially to calibrate instruments. The RNA and DNA standards have many attractive features including low cost, high purity, easily measureable concentrations, and minimal handling concerns, making them ideal for use as a reference material. PMID:25124363

Tetrahelical structural family adopted by AGCGA-rich regulatory DNA regions

NASA Astrophysics Data System (ADS)

Kocman, Vojč; Plavec, Janez

2017-05-01

Here we describe AGCGA-quadruplexes, an unexpected addition to the well-known tetrahelical families, G-quadruplexes and i-motifs, that have been a focus of intense research due to their potential biological impact in G- and C-rich DNA regions, respectively. High-resolution structures determined by solution-state nuclear magnetic resonance (NMR) spectroscopy demonstrate that AGCGA-quadruplexes comprise four 5'-AGCGA-3' tracts and are stabilized by G-A and G-C base pairs forming GAGA- and GCGC-quartets, respectively. Residues in the core of the structure are connected with edge-type loops. Sequences of alternating 5'-AGCGA-3' and 5'-GGG-3' repeats could be expected to form G-quadruplexes, but are shown herein to form AGCGA-quadruplexes instead. Unique structural features of AGCGA-quadruplexes together with lower sensitivity to cation and pH variation imply their potential biological relevance in regulatory regions of genes responsible for basic cellular processes that are related to neurological disorders, cancer and abnormalities in bone and cartilage development.

Emergent explosive synchronization in adaptive complex networks.

PubMed

Avalos-Gaytán, Vanesa; Almendral, Juan A; Leyva, I; Battiston, F; Nicosia, V; Latora, V; Boccaletti, S

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

The biological significance and clinical applications of exosomes in ovarian cancer

PubMed Central

Dorayappan, Kalpana Deepa Priya; Wallbillich, John J.; Cohn, David E.; Selvendiran, Karuppaiyah

2016-01-01

Exosomes are nano-sized (20–100 nm) 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. PMID:27058839

The biological significance and clinical applications of exosomes in ovarian cancer.

PubMed

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.

In crystallo optical spectroscopy (icOS) as a complementary tool on the macromolecular crystallography beamlines of the ESRF

PubMed Central

von Stetten, David; Giraud, Thierry; Carpentier, Philippe; Sever, Franc; Terrien, Maxime; Dobias, Fabien; Juers, Douglas H.; Flot, David; Mueller-Dieckmann, Christoph; Leonard, Gordon A.; de Sanctis, Daniele; Royant, Antoine

2015-01-01

The analysis of structural data obtained by X-ray crystallo­graphy benefits from information obtained from complementary techniques, especially as applied to the crystals themselves. As a consequence, optical spectroscopies in structural biology have become instrumental in assessing the relevance and context of many crystallographic results. Since the year 2000, it has been possible to record such data adjacent to, or directly on, the Structural Biology Group beamlines of the ESRF. A core laboratory featuring various spectrometers, named the Cryobench, is now in its third version and houses portable devices that can be directly mounted on beamlines. This paper reports the current status of the Cryobench, which is now located on the MAD beamline ID29 and is thus called the ID29S-Cryobench (where S stands for ‘spectroscopy’). It also reviews the diverse experiments that can be performed at the Cryobench, highlighting the various scientific questions that can be addressed. PMID:25615856

The Biological Categorizations Made by 4 and 5-Year-Old Children: The Role of Feature Type versus Their Causal Status

ERIC Educational Resources Information Center

Meunier, Benjamin; Cordier, Francoise

2008-01-01

The present study here investigated the role of the causal status of features and feature type in biological categorizations by young children. Study 1 showed that 5-year-olds are more strongly influenced by causal features than effect features. 4-year-olds exhibit no such tendency. There, therefore, appears to be a conceptual change between the…

Electrochemical Genosensing of Circulating Biomarkers

PubMed Central

Campuzano, Susana; Yáñez-Sedeño, Paloma; Pingarrón, José Manuel

2017-01-01

Management and prognosis of diseases requires the measurement in non- or minimally invasively collected samples of specific circulating biomarkers, consisting of any measurable or observable factors in patients that indicate normal or disease-related biological processes or responses to therapy. Therefore, on-site, fast and accurate determination of these low abundance circulating biomarkers in scarcely treated body fluids is of great interest for health monitoring and biological applications. In this field, electrochemical DNA sensors (or genosensors) have demonstrated to be interesting alternatives to more complex conventional strategies. Currently, electrochemical genosensors are considered very promising analytical tools for this purpose due to their fast response, low cost, high sensitivity, compatibility with microfabrication technology and simple operation mode which makes them compatible with point-of-care (POC) testing. In this review, the relevance and current challenges of the determination of circulating biomarkers related to relevant diseases (cancer, bacterial and viral infections and neurodegenerative diseases) are briefly discussed. An overview of the electrochemical nucleic acid–based strategies developed in the last five years for this purpose is given to show to both familiar and non-expert readers the great potential of these methodologies for circulating biomarker determination. After highlighting the main features of the reported electrochemical genosensing strategies through the critical discussion of selected examples, a conclusions section points out the still existing challenges and future directions in this field. PMID:28420103

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections

PubMed Central

Jaeger, Sébastien; Thieffry, Denis

2017-01-01

Abstract Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. PMID:28591841

Curcumin as a multifaceted compound against human papilloma virus infection and cervical cancers: A review of chemistry, cellular, molecular, and preclinical features.

PubMed

Teymouri, Manouchehr; Pirro, Matteo; Johnston, Thomas P; Sahebkar, Amirhosein

2017-05-06

Curcumin, the bioactive polyphenolic ingredient of turmeric, has been extensively studied for its effects on human papilloma virus (HPV) infection as well as primary and malignant squamous cervical cancers. HPV infections, especially those related to HPV 16 and 18 types, have been established as the leading cause of cervical cancer; however, there are also additional contributory factors involved in the etiopathogenesis of cervical cancers. Curcumin has emerged as having promising chemopreventive and anticancer effects against both HPV-related and nonrelated cervical cancers. In this review, we first discuss the biological relevance of curcumin and both its pharmacological effects and pharmaceutical considerations from a chemical point of view. Next, the signaling pathways that are modulated by curcumin and are relevant to the elimination of HPV infection and treatment of cervical cancer are discussed. We also present counter arguments regarding the effects of curcumin on signaling pathways and molecular markers dysregulated by benzo(a)pyrene (Bap), a carcinogen found in pathological cervical lesions of women who smoke frequently, and estradiol, as two important risk factors involved in persistent HPV-infection and cervical cancer. Finally, various strategies to enhance the pharmacological activity and pharmacokinetic characteristics of curcumin are discussed with examples of studies in experimental models of cervical cancer. © 2016 BioFactors, 43(3):331-346, 2017. © 2016 International Union of Biochemistry and Molecular Biology.

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

NASA Astrophysics Data System (ADS)

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.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes.

PubMed

Hadjithomas, Michalis; Chen, I-Min A; Chu, Ken; Huang, Jinghua; Ratner, Anna; Palaniappan, Krishna; Andersen, Evan; Markowitz, Victor; Kyrpides, Nikos C; Ivanova, Natalia N

2017-01-04

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Developmental palaeontology in synapsids: the fossil record of ontogeny in mammals and their closest relatives

PubMed Central

Sánchez-Villagra, Marcelo R.

2010-01-01

The study of fossilized ontogenies in mammals is mostly restricted to postnatal and late stages of growth, but nevertheless can deliver great insights into life history and evolutionary mechanisms affecting all aspects of development. Fossils provide evidence of developmental plasticity determined by ecological factors, as when allometric relations are modified in species which invaded a new space with a very different selection regime. This is the case of dwarfing and gigantism evolution in islands. Skeletochronological studies are restricted to the examination of growth marks mostly in the cement and dentine of teeth and can provide absolute age estimates. These, together with dental replacement data considered in a phylogenetic context, provide life-history information such as maturation time and longevity. Palaeohistology and dental replacement data document the more or less gradual but also convergent evolution of mammalian growth features during early synapsid evolution. Adult phenotypes of extinct mammals can inform developmental processes by showing a combination of features or levels of integration unrecorded in living species. Some adult features such as vertebral number, easily recorded in fossils, provide indirect information about somitogenesis and hox-gene expression boundaries. Developmental palaeontology is relevant for the discourse of ecological developmental biology, an area of research where features of growth and variation are fundamental and accessible among fossil mammals. PMID:20071389

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

NASA Astrophysics Data System (ADS)

Weinmann, M.; Jutzi, B.; Mallet, C.

2013-10-01

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.

Does the choice of display system influence perception and visibility of clinically relevant features in digital pathology images?

NASA Astrophysics Data System (ADS)

Kimpe, Tom; Rostang, Johan; Avanaki, Ali; Espig, Kathryn; Xthona, Albert; Cocuranu, Ioan; Parwani, Anil V.; Pantanowitz, Liron

2014-03-01

Digital pathology systems typically consist of a slide scanner, processing software, visualization software, and finally a workstation with display for visualization of the digital slide images. This paper studies whether digital pathology images can look different when presenting them on different display systems, and whether these visual differences can result in different perceived contrast of clinically relevant features. By analyzing a set of four digital pathology images of different subspecialties on three different display systems, it was concluded that pathology images look different when visualized on different display systems. The importance of these visual differences is elucidated when they are located in areas of the digital slide that contain clinically relevant features. Based on a calculation of dE2000 differences between background and clinically relevant features, it was clear that perceived contrast of clinically relevant features is influenced by the choice of display system. Furthermore, it seems that the specific calibration target chosen for the display system has an important effect on the perceived contrast of clinically relevant features. Preliminary results suggest that calibrating to DICOM GSDF calibration performed slightly worse than sRGB, while a new experimental calibration target CSDF performed better than both DICOM GSDF and sRGB. This result is promising as it suggests that further research work could lead to better definition of an optimized calibration target for digital pathology images resulting in a positive effect on clinical performance.

Determination of the Biologically Relevant Sampling Depth for Terrestrial and Aquatic Ecological Risk Assessments (Final Report)

EPA Science Inventory

The Ecological Risk Assessment Support Center (ERASC) announced the release of the final report, Determination of the Biologically Relevant Sampling Depth for Terrestrial and Aquatic Ecological Risk Assessments. This technical paper provides defensible approximations fo...

Numerical simulations of flying and swimming of biological systems with the viscous vortex particle method

NASA Astrophysics Data System (ADS)

Eldredge, Jeff

2005-11-01

Many biological mechanisms of locomotion involve the interaction of a fluid with a deformable surface undergoing large unsteady motion. Analysis of such problems poses a significant challenge to conventional grid-based computational approaches. Particularly in the moderate Reynolds number regime where many insects and fish function, viscous and inertial processes are both important, and vorticity serves a crucial role. In this work, the viscous vortex particle method is shown to provide an efficient, intuitive simulation approach for investigation of these biological systems. In contrast with a grid-based approach, the method solves the Navier--Stokes equations by tracking computational particles that carry smooth blobs of vorticity and exchange strength with one another to account for viscous diffusion. Thus, computational resources are focused on the physically relevant features of the flow, and there is no need for artificial boundary conditions. Building from previously-developed techniques for the creation of vorticity to enforce no-throughflow and no-slip conditions, the present method is extended to problems of coupled fluid--body dynamics by enforcement of global conservation of momenta. The application to several two-dimensional model problems is demonstrated, including single and multiple flapping wings and free swimming of a three-linkage fish.

[The enigma of the biological interpretation of the linear-quadratic model finally resolved? A summary for non-mathematicians].

PubMed

Bodgi, L; Canet, A; Granzotto, A; Britel, M; Puisieux, A; Bourguignon, M; Foray, N

2016-06-01

The linear-quadratic (LQ) model is the only mathematical formula linking cellular survival and radiation dose that is sufficiently consensual to help radiation oncologists and radiobiologists in describing the radiation-induced events. However, this formula proposed in the 1970s and α and β parameters on which it is based remained without relevant biological meaning. From a collection of cutaneous fibroblasts with different radiosensitivity, built over 12 years by more than 50 French radiation oncologists, we recently pointed out that the ATM protein, major actor of the radiation response, diffuses from the cytoplasm to the nucleus after irradiation. The evidence of this nuclear shuttling of ATM allowed us to provide a biological interpretation of the LQ model in its mathematical features, validated by a hundred of radiosensitive cases. A mechanistic explanation of the radiosensitivity of syndromes caused by the mutation of cytoplasmic proteins and of the hypersensitivity to low-dose phenomenon has been proposed, as well. In this review, we present our resolution of the LQ model in the most didactic way. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

MultiMiTar: a novel multi objective optimization based miRNA-target prediction method.

PubMed

Mitra, Ramkrishna; Bandyopadhyay, Sanghamitra

2011-01-01

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm.

Especially for High School Teachers

NASA Astrophysics Data System (ADS)

Howell, J. Emory

1999-05-01

Secondary School Feature Articles * An Elementary Outreach Program-Have Demo Will Travel, by James Swim, p 628 * Pressure and Stoichiometry, by Charles E. Roser and Catherine L. McCluskey, p 638 Making Connections vs Relevance: Chemistry and Biology For many years there has been a movement to make chemistry more relevant to learners, particularly in introductory chemistry courses. Sidebars describing chemical applications to real-world settings are sprinkled throughout textbooks. Consumer products are often used in place of reagent-grade chemicals, not only as a means of cost saving, but also in an attempt to make chemistry more relevant for the beginning learner. The Journal has published many articles dealing with the application of chemistry to other disciplines. As our understanding of the importance of constructivism in intellectual development has increased, the need to help students make connections between the knowledge they have constructed and their experiences in the classroom and laboratory has become more evident. The need is much deeper than simply recognizing familiar products or observing visible chemical changes. Relevance appears to be a helpful and perhaps necessary condition for learning, but it does not appear to be sufficient to ensure that connections are made between chemical concepts new to the learner and previously constructed knowledge. This month's JCE Classroom Activity "Soup or Salad? Investigating the Action of Enzymes in Fruit on Gelatin" (p 624A) is an example of an experiment that requires the student to use biological concepts to carry out a chemical investigation. The action of proteases from fresh or frozen pineapple and meat tenderizers on the proteins that provide the structure of gelatin is compared with the action of fruit that has been canned or heated in a microwave. Like other JCE Classroom Activities, references, additional information, and related activities are cited. The activity can be used in the classroom or assigned as a take-home activity. JCE Classroom Activity #15, "Liver and Onions: DNA Extraction from Animal and Plant Tissues" (p 400A, March 1999) also integrates chemical and biological concepts. The JCE Software videotape HIV-1 Protease: An Enzyme at Work is another useful resource. It can be used in any classroom where kinetics, catalysis, proteins, or enzymes are discussed. Information about JCE Software products can be found in recent issues of the Journal or by accessing JCE Online (http://jchemed.chem.wisc.edu). Because most high school students complete at least one year of biology before enrolling in chemistry, developing the connections between biology and chemistry can be especially productive. Connections between chemistry and biology often seem to be more real to students than do many of the phenomena we cite as applications. For example, students often are not able to make the connection between the excitation of electrons to produce electromagnetic radiation and anything that is personally relevant. The light given off by sodium or mercury vapor lights provides a common example of relating atomic emission to a useful process, but many students do not seem to find that particularly interesting. The need to make a connection between biology and chemistry becomes especially meaningful to students when the chemical change occurs within the human body. As an example, the interaction of emitted electromagnetic radiation with human cells to cause well-tanned skin seems more relevant to a greater number of students than the color of lights in a parking lot. This issue contains an article that describes a useful application of light to kill cancer cells through use of photosensitizers (p 592). The process of photodynamic therapy (PDT) provides another example that could help students make a connection between the emission of electromagnetic radiation and the challenge of killing cancer cells without harming healthy cells. Certainly this example is not a magic antidote to "why do we have to learn this stuff" and it doesn't directly relate atomic spectra to quantum theory. It does, however, deal with energy-matter interactions in a topic that is more relevant to students' daily lives. And in turn, the concept of electromagnetic radiation interacting with matter may be more important for most students to understand than is the quantum mechanical explanation of electronic configuration. This issue contains several other articles from which useful examples connecting chemistry and biology can be drawn. Most of these are not indicated in the table of contents with the high school mark (*) because they are written primarily for college biochemistry faculty members. However, many high school teachers who read this column have strong backgrounds in biology and can find useful information in some of these articles. A keyword search for "enzyme" using the online index (http://jchemed.chem.wisc.edu/Journal/Search/ ) yielded 75 articles published between January 1990 and the present, illustrating that a great deal about this topic alone has been published in this Journal. Other "biochemical" keywords that can be used to search the index include amino acids, biotechnology, hormones, lipids, metabolism, nucleic acids/DNA/RNA, and proteins/peptides. Other biological connections are evidenced through keywords such as drugs/pharmaceuticals, food science, medicinal chemistry, nutrition, and vitamins. Chemical Mysteries Revealed Online Ron DeLorenzo, editor of the Applications and Analogies feature, recently sent an email message describing a resource of interest to high school teachers. The Greenwich Science Education Center, Greenwich, Connecticut, is now displaying on their Web site (http://www.educationcenter.org) about 100 of DeLorenzo's interesting mystery articles. Anaheim and Boston To those readers who stopped by the JCE booth at the ACS National Meeting in Anaheim or at the NSTA convention Boston we wish to say thank you. Also, thank you to those with whom we spoke at the outstanding High School Program at Anaheim. Watch the June issue for more about these two outstanding conventions.

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

PubMed

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.

A Test of the Biogenicity Criteria Established for Microfossils and Stromatolites on Quaternary Tufa and Speleothem Materials Formed in the "Twilight Zone" at Caerwys, UK.

PubMed

Brasier, A T; Rogerson, M R; Mercedes-Martin, R; Vonhof, H B; Reijmer, J J G

2015-10-01

The ability to distinguish the features of a chemical sedimentary rock that can only be attributed to biology is a challenge relevant to both geobiology and astrobiology. This study aimed to test criteria for recognizing petrographically the biogenicity of microbially influenced fabrics and fossil microbes in complex Quaternary stalactitic carbonate rocks from Caerwys, UK. We found that the presence of carbonaceous microfossils, fabrics produced by the calcification of microbial filaments, and the asymmetrical development of tufa fabrics due to the more rapid growth of microbially influenced laminations could be recognized as biogenic features. Petrographic evidence also indicates that the development of "speleothem-like" laminae was related to episodes of growth interrupted by intervals of nondeposition and erosion. The lack of any biogenic characteristics in these laminae is consistent with their development as a result of variation in the physicochemical parameters that drive calcite precipitation from meteoric waters in such environmental settings.

Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases

NASA Astrophysics Data System (ADS)

Belik, Vitaly; Geisel, Theo; Brockmann, Dirk

2011-08-01

We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.

Evolution of Biological Image Stabilization.

PubMed

Hardcastle, Ben J; Krapp, Holger G

2016-10-24

The use of vision to coordinate behavior requires an efficient control design that stabilizes the world on the retina or directs the gaze towards salient features in the surroundings. With a level gaze, visual processing tasks are simplified and behaviorally relevant features from the visual environment can be extracted. No matter how simple or sophisticated the eye design, mechanisms have evolved across phyla to stabilize gaze. In this review, we describe functional similarities in eyes and gaze stabilization reflexes, emphasizing their fundamental role in transforming sensory information into motor commands that support postural and locomotor control. We then focus on gaze stabilization design in flying insects and detail some of the underlying principles. Systems analysis reveals that gaze stabilization often involves several sensory modalities, including vision itself, and makes use of feedback as well as feedforward signals. Independent of phylogenetic distance, the physical interaction between an animal and its natural environment - its available senses and how it moves - appears to shape the adaptation of all aspects of gaze stabilization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Independent evolution of genomic characters during major metazoan transitions.

PubMed

Simakov, Oleg; Kawashima, Takeshi

2017-07-15

Metazoan evolution encompasses a vast evolutionary time scale spanning over 600 million years. Our ability to infer ancestral metazoan characters, both morphological and functional, is limited by our understanding of the nature and evolutionary dynamics of the underlying regulatory networks. Increasing coverage of metazoan genomes enables us to identify the evolutionary changes of the relevant genomic characters such as the loss or gain of coding sequences, gene duplications, micro- and macro-synteny, and non-coding element evolution in different lineages. In this review we describe recent advances in our understanding of ancestral metazoan coding and non-coding features, as deduced from genomic comparisons. Some genomic changes such as innovations in gene and linkage content occur at different rates across metazoan clades, suggesting some level of independence among genomic characters. While their contribution to biological innovation remains largely unclear, we review recent literature about certain genomic changes that do correlate with changes to specific developmental pathways and metazoan innovations. In particular, we discuss the origins of the recently described pharyngeal cluster which is conserved across deuterostome genomes, and highlight different genomic features that have contributed to the evolution of this group. We also assess our current capacity to infer ancestral metazoan states from gene models and comparative genomics tools and elaborate on the future directions of metazoan comparative genomics relevant to evo-devo studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Attention to Distinct Goal-relevant Features Differentially Guides Semantic Knowledge Retrieval.

PubMed

Hanson, Gavin K; Chrysikou, Evangelia G

2017-07-01

A critical aspect of conceptual knowledge is the selective activation of goal-relevant aspects of meaning. Although the contributions of ventrolateral prefrontal and posterior temporal areas to semantic cognition are well established, the precise role of posterior parietal cortex in semantic control remains unknown. Here, we examined whether this region modulates attention to goal-relevant features within semantic memory according to the same principles that determine the salience of task-relevant object properties during visual attention. Using multivoxel pattern analysis, we decoded attentional referents during a semantic judgment task, in which participants matched an object cue to a target according to concrete (i.e., color, shape) or abstract (i.e., function, thematic context) semantic features. The goal-relevant semantic feature participants attended to (e.g., color or shape, function or theme) could be decoded from task-associated cortical activity with above-chance accuracy, a pattern that held for both concrete and abstract semantic features. A Bayesian confusion matrix analysis further identified differential contributions to representing attentional demands toward specific object properties across lateral prefrontal, posterior temporal, and inferior parietal regions, with the dorsolateral pFC supporting distinctions between higher-order properties and the left intraparietal sulcus being the only region supporting distinctions across all semantic features. These results are the first to demonstrate that patterns of neural activity in the parietal cortex are sensitive to which features of a concept are attended to, thus supporting the contributions of posterior parietal cortex to semantic control.

Behavioral and Biological Effects of Housing Conditions and Stress in Male Rats - Relevance to Heart Disease

DTIC Science & Technology

2006-08-01

animals had higher corticosterone than Combined Enrichment/Not Stressed (CNS) animals (F [1, 22 ] = 6.78, p < 0.01). The greatest effects were in...biological effects of stress. In particular, plasma corticosterone levels have been reported to increase in response to stressors in different... effects of restraint stress on the biological and behavioral factors relevant to cardiovascular disease (e.g., plasma corticosterone levels

GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.

PubMed

Subhash, Santhilal; Kanduri, Chandrasekhar

2016-09-13

High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc. In this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies. GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.

Atypical behavior in the electron capture induced dissociation of biologically relevant transition metal ion complexes of the peptide hormone oxytocin

NASA Astrophysics Data System (ADS)

Kleinnijenhuis, Anne J.; Mihalca, Romulus; Heeren, Ron M. A.; Heck, Albert J. R.

2006-07-01

Doubly protonated ions of the disulfide bond containing nonapeptide hormone oxytocin and oxytocin complexes with different transition metal ions, that have biological relevance under physiological conditions, were subjected to electron capture dissociation (ECD) to probe their structural features in the gas phase. Although, all the ECD spectra were strikingly different, typical ECD behavior was observed for complexes of the nonapeptide hormone oxytocin with Ni2+, Co2+ and Zn2+, i.e., abundant c/z' and a'/y backbone cleavages and ECD characteristic S-S and S-C bond cleavages were observed. We propose that, although in the oxytocin-transition metal ion complexes the metal ions serve as the main initial capture site, the captured electron is transferred to other sites in the complex to form a hydrogen radical, which drives the subsequent typical ECD fragmentations. The complex of oxytocin with Cu2+ displayed noticeably different ECD behavior. The fragment ions were similar to fragment ions typically observed with low-energy collision induced dissociation (CID). We propose that the electrons captured by the oxytocin-Cu2+ complex might be favorably involved in reducing the Cu2+ metal ion to Cu+. Subsequent energy redistribution would explain the observed low-energy CID-type fragmentations. Electron capture resulted also in quite different specific cleavage sites for the complexes of oxytocin with Ni2+, Co2+ and Zn2+. This is an indication for structural differences in these complexes possibly linked to their significantly different biological effects on oxytocin-receptor binding, and suggests that ECD may be used to study subtle structural differences in transition metal ion-peptide complexes.

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

PubMed

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.

Automatic cell identification and visualization using digital holographic microscopy with head mounted augmented reality devices.

PubMed

O'Connor, Timothy; Rawat, Siddharth; Markman, Adam; Javidi, Bahram

2018-03-01

We propose a compact imaging system that integrates an augmented reality head mounted device with digital holographic microscopy for automated cell identification and visualization. A shearing interferometer is used to produce holograms of biological cells, which are recorded using customized smart glasses containing an external camera. After image acquisition, segmentation is performed to isolate regions of interest containing biological cells in the field-of-view, followed by digital reconstruction of the cells, which is used to generate a three-dimensional (3D) pseudocolor optical path length profile. Morphological features are extracted from the cell's optical path length map, including mean optical path length, coefficient of variation, optical volume, projected area, projected area to optical volume ratio, cell skewness, and cell kurtosis. Classification is performed using the random forest classifier, support vector machines, and K-nearest neighbor, and the results are compared. Finally, the augmented reality device displays the cell's pseudocolor 3D rendering of its optical path length profile, extracted features, and the identified cell's type or class. The proposed system could allow a healthcare worker to quickly visualize cells using augmented reality smart glasses and extract the relevant information for rapid diagnosis. To the best of our knowledge, this is the first report on the integration of digital holographic microscopy with augmented reality devices for automated cell identification and visualization.

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

PubMed

Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

2016-12-01

The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

Joint Concept Correlation and Feature-Concept Relevance Learning for Multilabel Classification.

PubMed

Zhao, Xiaowei; Ma, Zhigang; Li, Zhi; Li, Zhihui

2018-02-01

In recent years, multilabel classification has attracted significant attention in multimedia annotation. However, most of the multilabel classification methods focus only on the inherent correlations existing among multiple labels and concepts and ignore the relevance between features and the target concepts. To obtain more robust multilabel classification results, we propose a new multilabel classification method aiming to capture the correlations among multiple concepts by leveraging hypergraph that is proved to be beneficial for relational learning. Moreover, we consider mining feature-concept relevance, which is often overlooked by many multilabel learning algorithms. To better show the feature-concept relevance, we impose a sparsity constraint on the proposed method. We compare the proposed method with several other multilabel classification methods and evaluate the classification performance by mean average precision on several data sets. The experimental results show that the proposed method outperforms the state-of-the-art methods.

Bioavailability of antioxidants in extruded products prepared from purple potato and dry pea flours

USDA-ARS?s Scientific Manuscript database

Measuring antioxidant activity using biological relevant assay is unique to understand the role of phytochemicals in vivo than common chemical assays. Cellular antioxidant activity assay could provide more biological relevant information on bioactive compounds in the raw as well as processed food pr...

Brachypodium as a model for the grasses: today and the future

USDA-ARS?s Scientific Manuscript database

Over the past several years, Brachypodium distachyon (Brachypodium) has emerged as a tractable model system to study biological questions relevant to the grasses. To place its relevance in the larger context of plant biology, we outline here the expanding adoption of Brachypodium as a model grass an...

IDENTIFICATION OF BIOLOGICALLY RELEVANT GENES USING A DATABASE OF RAT LIVER AND KIDNEY BASELINE GENE EXPRESSION

EPA Science Inventory

Microarray data from independent labs and studies can be compared to potentially identify toxicologically and biologically relevant genes. The Baseline Animal Database working group of HESI was formed to assess baseline gene expression from microarray data derived from control or...

Generalized query-based active learning to identify differentially methylated regions in DNA.

PubMed

Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J

2013-01-01

Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

A mixture model-based approach to the clustering of microarray expression data.

PubMed

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism

PubMed Central

Marković, Dimitrije; Gläscher, Jan; Bossaerts, Peter; O’Doherty, John; Kiebel, Stefan J.

2015-01-01

For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects’ behavior and found that attention-like features in the behavioral model are essential for explaining subjects’ responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects. PMID:26495984

TinkerCell: modular CAD tool for synthetic biology.

PubMed

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

2009-10-29

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. 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. 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 accept third-party algorithms, allowing it to serve as a platform for testing different methods relevant to synthetic biology.

TinkerCell: modular CAD tool for synthetic biology

PubMed Central

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 accept third-party algorithms, allowing it to serve as a platform for testing different methods relevant to synthetic biology. PMID:19874625

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

PubMed

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.

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

PubMed Central

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

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: a) biologically emotional images hold attention more strongly than socially emotional images, b) memory for biologically emotional images was enhanced even with limited cognitive resources, but c) 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 visual cortex and greater functional connectivity between 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 medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between amygdala and MPFC than biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity. PMID:21964552

A bootstrap based Neyman-Pearson test for identifying variable importance.

PubMed

Ditzler, Gregory; Polikar, Robi; Rosen, Gail

2015-04-01

Selection of most informative features that leads to a small loss on future data are arguably one of the most important steps in classification, data analysis and model selection. Several feature selection (FS) algorithms are available; however, due to noise present in any data set, FS algorithms are typically accompanied by an appropriate cross-validation scheme. In this brief, we propose a statistical hypothesis test derived from the Neyman-Pearson lemma for determining if a feature is statistically relevant. The proposed approach can be applied as a wrapper to any FS algorithm, regardless of the FS criteria used by that algorithm, to determine whether a feature belongs in the relevant set. Perhaps more importantly, this procedure efficiently determines the number of relevant features given an initial starting point. We provide freely available software implementations of the proposed methodology.

Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

NASA Astrophysics Data System (ADS)

Adi Putra, Januar

2018-04-01

In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

Selecting relevant 3D image features of margin sharpness and texture for lung nodule retrieval.

PubMed

Ferreira, José Raniery; de Azevedo-Marques, Paulo Mazzoncini; Oliveira, Marcelo Costa

2017-03-01

Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency. The goal of this paper is to perform the selection of 3D image features of margin sharpness and texture that can be relevant on the retrieval of similar cancerous and benign lung nodules. A total of 48 3D image attributes were extracted from the nodule volume. Border sharpness features were extracted from perpendicular lines drawn over the lesion boundary. Second-order texture features were extracted from a cooccurrence matrix. Relevant features were selected by a correlation-based method and a statistical significance analysis. Retrieval performance was assessed according to the nodule's potential malignancy on the 10 most similar cases and by the parameters of precision and recall. Statistical significant features reduced retrieval performance. Correlation-based method selected 2 margin sharpness attributes and 6 texture attributes and obtained higher precision compared to all 48 extracted features on similar nodule retrieval. Feature space dimensionality reduction of 83 % obtained higher retrieval performance and presented to be a computationaly low cost method of retrieving similar nodules for the diagnosis of lung cancer.

Evolutionary perspectives on learning: conceptual and methodological issues in the study of adaptive specializations.

PubMed

Krause, Mark A

2015-07-01

Inquiry into evolutionary adaptations has flourished since the modern synthesis of evolutionary biology. Comparative methods, genetic techniques, and various experimental and modeling approaches are used to test adaptive hypotheses. In psychology, the concept of adaptation is broadly applied and is central to comparative psychology and cognition. The concept of an adaptive specialization of learning is a proposed account for exceptions to general learning processes, as seen in studies of Pavlovian conditioning of taste aversions, sexual responses, and fear. The evidence generally consists of selective associations forming between biologically relevant conditioned and unconditioned stimuli, with conditioned responses differing in magnitude, persistence, or other measures relative to non-biologically relevant stimuli. Selective associations for biologically relevant stimuli may suggest adaptive specializations of learning, but do not necessarily confirm adaptive hypotheses as conceived of in evolutionary biology. Exceptions to general learning processes do not necessarily default to an adaptive specialization explanation, even if experimental results "make biological sense". This paper examines the degree to which hypotheses of adaptive specializations of learning in sexual and fear response systems have been tested using methodologies developed in evolutionary biology (e.g., comparative methods, quantitative and molecular genetics, survival experiments). A broader aim is to offer perspectives from evolutionary biology for testing adaptive hypotheses in psychological science.

The pangenome of (Antarctic) Pseudoalteromonas bacteria: evolutionary and functional insights.

PubMed

Bosi, Emanuele; Fondi, Marco; Orlandini, Valerio; Perrin, Elena; Maida, Isabel; de Pascale, Donatella; Tutino, Maria Luisa; Parrilli, Ermenegilda; Lo Giudice, Angelina; Filloux, Alain; Fani, Renato

2017-01-17

Pseudoalteromonas is a genus of ubiquitous marine bacteria used as model organisms to study the biological mechanisms involved in the adaptation to cold conditions. A remarkable feature shared by these bacteria is their ability to produce secondary metabolites with a strong antimicrobial and antitumor activity. Despite their biotechnological relevance, representatives of this genus are still lacking (with few exceptions) an extensive genomic characterization, including features involved in the evolution of secondary metabolites production. Indeed, biotechnological applications would greatly benefit from such analysis. Here, we analyzed the genomes of 38 strains belonging to different Pseudoalteromonas species and isolated from diverse ecological niches, including extreme ones (i.e. Antarctica). These sequences were used to reconstruct the largest Pseudoalteromonas pangenome computed so far, including also the two main groups of Pseudoalteromonas strains (pigmented and not pigmented strains). The downstream analyses were conducted to describe the genomic diversity, both at genus and group levels. This allowed highlighting a remarkable genomic heterogeneity, even for closely related strains. We drafted all the main evolutionary steps that led to the current structure and gene content of Pseudoalteromonas representatives. These, most likely, included an extensive genome reduction and a strong contribution of Horizontal Gene Transfer (HGT), which affected biotechnologically relevant gene sets and occurred in a strain-specific fashion. Furthermore, this study also identified the genomic determinants related to some of the most interesting features of the Pseudoalteromonas representatives, such as the production of secondary metabolites, the adaptation to cold temperatures and the resistance to abiotic compounds. This study poses the bases for a comprehensive understanding of the evolutionary trajectories followed in time by this peculiar bacterial genus and for a focused exploitation of their biotechnological potential.

Correlation between structure, retention, property, and activity of biologically relevant 1,7-bis(aminoalkyl)diazachrysene derivatives.

PubMed

Šegan, Sandra; Trifković, Jelena; Verbić, Tatjana; Opsenica, Dejan; Zlatović, Mario; Burnett, James; Šolaja, Bogdan; Milojković-Opsenica, Dušanka

2013-01-01

The physicochemical properties, retention parameters (R(M)(0)), partition coefficients (logP(OW)), and pK(a) values for a series of thirteen 1,7-bis(aminoalkyl) diazachrysene (1,7-DAAC) derivatives were determined in order to reveal the characteristics responsible for their biological behavior. The investigated compounds inhibit three unrelated pathogens (the Botulinum neurotoxin serotype A light chain (BoNT/A LC), Plasmodium falciparum malaria, and Ebola filovirus) via three different mechanisms of action. To determine the most influential factors governing the retention and activities of the investigated diazachrysenes, R(M)(0), logP(OW), and biological activity values were correlated with 2D and 3D molecular descriptors, using a partial least squares regression. The resulting quantitative structure-retention (property) relationships indicate the importance of descriptors related to the hydrophobicity of the molecules (e.g., predicted partition coefficients and hydrophobic surface area). Quantitative structure-activity relationship models for describing biological activity against the BoNT/A LC and malarial strains also include overall compound polarity, electron density distribution, and proton donor/acceptor potential. Furthermore, models for Ebola filovirus inhibition are presented qualitatively to provide insights into parameters that may contribute to the compounds' antiviral activities. Overall, the models form the basis for selecting structural features that significantly affect the compound's absorption, distribution, metabolism, excretion, and toxicity profiles. Copyright © 2012 Elsevier B.V. All rights reserved.

FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data.

PubMed

DeTomaso, David; Yosef, Nir

2016-08-23

A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene 'signatures') are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge.

Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

PubMed Central

Craddock, Travis J. A.; Fletcher, Mary Ann; Klimas, Nancy G.

2015-01-01

There is a growing appreciation for the network biology that regulates the coordinated expression of molecular and cellular markers however questions persist regarding the identifiability of these networks. Here we explore some of the issues relevant to recovering directed regulatory networks from time course data collected under experimental constraints typical of in vivo studies. NetSim simulations of sparsely connected biological networks were used to evaluate two simple feature selection techniques used in the construction of linear Ordinary Differential Equation (ODE) models, namely truncation of terms versus latent vector projection. Performance was compared with ODE-based Time Series Network Identification (TSNI) integral, and the information-theoretic Time-Delay ARACNE (TD-ARACNE). Projection-based techniques and TSNI integral outperformed truncation-based selection and TD-ARACNE on aggregate networks with edge densities of 10-30%, i.e. transcription factor, protein-protein cliques and immune signaling networks. All were more robust to noise than truncation-based feature selection. Performance was comparable on the in silico 10-node DREAM 3 network, a 5-node Yeast synthetic network designed for In vivo Reverse-engineering and Modeling Assessment (IRMA) and a 9-node human HeLa cell cycle network of similar size and edge density. Performance was more sensitive to the number of time courses than to sample frequency and extrapolated better to larger networks by grouping experiments. In all cases performance declined rapidly in larger networks with lower edge density. Limited recovery and high false positive rates obtained overall bring into question our ability to generate informative time course data rather than the design of any particular reverse engineering algorithm. PMID:25984725

Women's attractiveness is linked to expected age at menopause.

PubMed

Bovet, J; Barkat-Defradas, M; Durand, V; Faurie, C; Raymond, M

2018-02-01

A great number of studies have shown that features linked to immediate fertility explain a large part of the variance in female attractiveness. This is consistent with an evolutionary perspective, as men are expected to prefer females at the age at which fertility peaks (at least for short-term relationships) in order to increase their reproductive success. However, for long-term relationships, a high residual reproductive value (the expected future reproductive output, linked to age at menopause) becomes relevant as well. In that case, young age and late menopause are expected to be preferred by men. However, the extent to which facial features provide cues to the likely age at menopause has never been investigated so far. Here, we show that expected age at menopause is linked to facial attractiveness of young women. As age at menopause is heritable, we used the mother's age at menopause as a proxy for her daughter's expected age of menopause. We found that men judged faces of women with a later expected age at menopause as more attractive than those of women with an earlier expected age at menopause. This result holds when age, cues of immediate fertility and facial ageing were controlled for. Additionally, we found that the expected age at menopause was not correlated with any of the other variables considered (including immediate fertility cues and facial ageing). Our results show the existence of a new correlate of women's facial attractiveness, expected age at menopause, which is independent of immediate fertility cues and facial ageing. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

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

EPA Science Inventory

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...

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

PubMed Central

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

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

PubMed

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

2011-06-01

When spatial attention is directed toward 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 visual cortical 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 contrast of the grating 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.

Evolution of a strategy for preparing bioactive small molecules by sequential multicomponent assembly processes, cyclizations, and diversification.

PubMed

Sahn, James J; Granger, Brett A; Martin, Stephen F

2014-10-21

A strategy for generating diverse collections of small molecules has been developed that features a multicomponent assembly process (MCAP) to efficiently construct a variety of intermediates possessing an aryl aminomethyl subunit. These key compounds are then transformed via selective ring-forming reactions into heterocyclic scaffolds, each of which possesses suitable functional handles for further derivatizations and palladium-catalyzed cross coupling reactions. The modular nature of this approach enables the facile construction of libraries of polycyclic compounds bearing a broad range of substituents and substitution patterns for biological evaluation. Screening of several compound libraries thus produced has revealed a large subset of compounds that exhibit a broad spectrum of medicinally-relevant activities.

Neurological disorders and inflammatory bowel diseases

PubMed Central

Casella, Giovanni; Tontini, Gian Eugenio; Bassotti, Gabrio; Pastorelli, Luca; Villanacci, Vincenzo; Spina, Luisa; Baldini, Vittorio; Vecchi, Maurizio

2014-01-01

Extraintestinal manifestations occur in about one-third of patients living with inflammatory bowel disease (IBD) and may precede the onset of gastrointestinal symptoms by many years. Neurologic disorders associated with IBD are not frequent, being reported in 3% of patients, but they often represent an important cause of morbidity and a relevant diagnostic issue. In addition, the increasing use of immunosuppressant and biological therapies for IBD may also play a pivotal role in the development of neurological disorders of different type and pathogenesis. Hence, we provide a complete and profound review of the main features of neurological complications associated with IBD, with particular reference to those related to drugs and with a specific focus on their clinical presentation and possible pathophysiological mechanisms. PMID:25083051

Meditation and Hypnosis: Two Sides of the Same Coin?

PubMed

Facco, Enrico

2017-01-01

Hypnosis and meditation, as a whole, form a heterogeneous complex of psychosomatic techniques able to control mind and body regulation. Hypnosis has been pragmatically used for limited therapeutic targets, while Eastern meditation has much wider philosophical and existential implications, aiming for a radical liberation from all illusions, attachments, suffering and pain. The available data on the history, phenomenology, and neuropsychology of hypnosis and meditation show several common features, such as the following: (a) induction based on focused attention; (b) capability to reach an intentional control of both biologic-somatic activities and conscious-unconscious processes; (c) activation/deactivation of several brain areas and circuits (e.g., the default modality network and pain neuromatrix) with a relevant overlapping between the two.

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

ERIC Educational Resources Information Center

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…

Design control considerations for biologic-device combination products.

PubMed

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 development of innovative, safe and effective combination products. It remains the manufacturer's responsibility to comply with the relevant requirements and regulations, and develop good business practices that clearly describe how these practices comply with FDA's final rule (21 CFR Part 4) and aligns with the company's already established quality system. Copyright © 2017 Elsevier B.V. All rights reserved.

Spectroscopy of Isolated Prebiotic Nucleobases

NASA Technical Reports Server (NTRS)

Svadlenak, Nathan; Callahan, Michael P.; Ligare, Marshall; Gulian, Lisa; Gengeliczki, Zsolt; Nachtigallova, Dana; Hobza, Pavel; deVries, Mattanjah

2011-01-01

We use multiphoton ionization and double resonance spectroscopy to study the excited state dynamics of biologically relevant molecules as well as prebiotic nucleobases, isolated in the gas phase. Molecules that are biologically relevant to life today tend to exhibit short excited state lifetimes compared to similar but non-biologically relevant analogs. The mechanism is internal conversion, which may help protect the biologically active molecules from UV damage. This process is governed by conical intersections that depend very strongly on molecular structure. Therefore we have studied purines and pyrimidines with systematic variations of structure, including substitutions, tautomeric forms, and cluster structures that represent different base pair binding motifs. These structural variations also include possible alternate base pairs that may shed light on prebiotic chemistry. With this in mind we have begun to probe the ultrafast dynamics of molecules that exhibit very short excited states and search for evidence of internal conversions.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions.

PubMed

Tran, Tran T; Kulis, Christina; Long, Steven M; Bryant, Darryn; Adams, Peter; Smythe, Mark L

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions

NASA Astrophysics Data System (ADS)

Tran, Tran T.; Kulis, Christina; Long, Steven M.; Bryant, Darryn; Adams, Peter; Smythe, Mark L.

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

PubMed

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

Reliable classification of high explosive and chemical/biological artillery using acoustic sensors

NASA Astrophysics Data System (ADS)

Desai, Sachi V.; Hohil, Myron E.; Bass, Henry E.; Chambers, Jim

2005-05-01

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis are used to develop a robust classification algorithm that reliably discriminates between conventional and simulated chemical/biological artillery rounds via acoustic signals produced during detonation utilizing a generic acoustic sensor. Based on the transient properties of the signature blast distinct characteristics arise within the different acoustic signatures because high explosive warheads emphasize concussive and shrapnel effects, while chemical/biological warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. The ensuing blast waves are readily characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. Unique attributes can also be identified that depend upon the properties of the gun tube, projectile speed at the muzzle, and the explosive burn rates of the warhead. The algorithm enables robust classification of various airburst signatures using acoustics. It is capable of being integrated within an existing chemical/biological sensor, a stand-alone generic sensor, or a part of a disparate sensor suite. When emplaced in high-threat areas, this added capability would further provide field personal with advanced battlefield knowledge without the aide of so-called "sniffer" sensors that rely upon air particle information based on direct contact with possible contaminated air. In this work, the discrete wavelet transform is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 2km while maintaining temporal sequence of the data to keep relevance to the transient differences of the airburst signatures. Highly reliable discrimination is achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition the neural network then is capable of classifying new airburst signatures as Chemical/Biological or High Explosive.

Structure and Dynamics of Type III Secretion Effector Protein ExoU As determined by SDSL-EPR Spectroscopy in Conjunction with De Novo Protein Folding

PubMed Central

2017-01-01

ExoU is a 74 kDa cytotoxin that undergoes substantial conformational changes as part of its function, that is, it has multiple thermodynamically stable conformations that interchange depending on its environment. Such flexible proteins pose unique challenges to structural biology: (1) not only is it often difficult to determine structures by X-ray crystallography for all biologically relevant conformations because of the flat energy landscape (2) but also experimental conditions can easily perturb the biologically relevant conformation. The first challenge can be overcome by applying orthogonal structural biology techniques that are capable of observing alternative, biologically relevant conformations. The second challenge can be addressed by determining the structure in the same biological state with two independent techniques under different experimental conditions. If both techniques converge to the same structural model, the confidence that an unperturbed biologically relevant conformation is observed increases. To this end, we determine the structure of the C-terminal domain of the effector protein, ExoU, from data obtained by electron paramagnetic resonance spectroscopy in conjunction with site-directed spin labeling and in silico de novo structure determination. Our protocol encompasses a multimodule approach, consisting of low-resolution topology sampling, clustering, and high-resolution refinement. The resulting model was compared with an ExoU model in complex with its chaperone SpcU obtained previously by X-ray crystallography. The two models converged to a minimal RMSD100 of 3.2 Å, providing evidence that the unbound structure of ExoU matches the fold observed in complex with SpcU. PMID:28691114

Is filtering difficulty the basis of attentional deficits in schizophrenia?

PubMed

Ravizza, Susan M; Robertson, Lynn C; Carter, Cameron S; Nordahl, Thomas E; Salo, Ruth E

2007-06-30

The distractibility that schizophrenia patients display may be the result of a deficiency in filtering out irrelevant information. The aim of the current study was to assess whether patients with schizophrenia exhibit greater difficulty when task-irrelevant features change compared to healthy participants. Thirteen medicated outpatients with a diagnosis of schizophrenia and thirteen age- and parental education-matched controls performed a target selection task in which the task-relevant letter or the task-irrelevant features of color, and/or location repeated or switched. Participants were required to respond by pressing the appropriate key associated with the target letter. These patients with schizophrenia were slower when the task-relevant target letter switched than when it repeated. In contrast, schizophrenia patients performed similarly to controls when task-irrelevant information changed. Thus, we found no evidence that patients with schizophrenia were impaired in inhibiting irrelevant perceptual features. In contrast, changes in task-relevant features were problematic for patients relative to control participants. These results suggest that medicated outpatients who are mild to moderately symptomatic do not exhibit global impairments of feature processing. Instead, impairments are restricted to situations when task-relevant features vary. The current findings also suggest that when a course of action is not implied by an irrelevant feature, outpatients' behavior is not modulated by extraneous visual information any more than in healthy controls.

Rapid Parallel Screening for Strain Optimization

DTIC Science & Technology

2013-08-16

fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can...reporter, and, 2) a yeast TAR cloning shuttle vector for transferring catabolic clusters to E. coli. 15. SUBJECT TERMS NA 16. SECURITY CLASSIFICATION OF... fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can utilize

Rapid Parallel Screening for Strain Optimization

DTIC Science & Technology

2013-05-16

fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can...reporter, and, 2) a yeast TAR cloning shuttle vector for transferring catabolic clusters to E. coli. 15. SUBJECT TERMS NA 16. SECURITY CLASSIFICATION OF... fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can utilize

Comparative Evaluation of Two Serial Gene Expression Experiments | Division of Cancer Prevention

Cancer.gov

Stuart G. Baker, 2014 Introduction This program fits biologically relevant response curves in comparative analysis of the two gene expression experiments involving same genes but under different scenarios and at least 12 responses. The program outputs gene pairs with biologically relevant response curve shapes including flat, linear, sigmoid, hockey stick, impulse and step

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

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

PubMed

Calabrese, Edward J

2013-11-01

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. Copyright © 2013 Elsevier Ltd. All rights reserved.

Features and heterogeneities in growing network models

NASA Astrophysics Data System (ADS)

Ferretti, Luca; Cortelezzi, Michele; Yang, Bin; Marmorini, Giacomo; Bianconi, Ginestra

2012-06-01

Many complex networks from the World Wide Web to biological networks grow taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document such as personal page, thematic website, news, blog, search engine, social network, etc., or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an “effective fitness” for each class of nodes, determining the rate at which nodes acquire new links. The degree distribution exhibits a multiscaling behavior analogous to the the fitness model. This property is robust with respect to variations in the model, as long as links are assigned through effective preferential attachment. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show that it disappears for large network size, a property shared with the Barabási-Albert model. Negative degree correlations are also present in this class of models, along with nontrivial mixing patterns among features. We therefore conclude that both small clustering coefficients and disassortative mixing are outcomes of the preferential attachment mechanism in general growing networks.

Outdoor cultivation of microalgae for carotenoid production: current state and perspectives.

PubMed

Del Campo, José A; García-González, Mercedes; Guerrero, Miguel G

2007-04-01

Microalgae are a major natural source for a vast array of valuable compounds, including a diversity of pigments, for which these photosynthetic microorganisms represent an almost exclusive biological resource. Yellow, orange, and red carotenoids have an industrial use in food products and cosmetics as vitamin supplements and health food products and as feed additives for poultry, livestock, fish, and crustaceans. The growing worldwide market value of carotenoids is projected to reach over US$1,000 million by the end of the decade. The nutraceutical boom has also integrated carotenoids mainly on the claim of their proven antioxidant properties. Recently established benefits in human health open new uses for some carotenoids, especially lutein, an effective agent for the prevention and treatment of a variety of degenerative diseases. Consumers' demand for natural products favors development of pigments from biological sources, thus increasing opportunities for microalgae. The biotechnology of microalgae has gained considerable progress and relevance in recent decades, with carotenoid production representing one of its most successful domains. In this paper, we review the most relevant features of microalgal biotechnology related to the production of different carotenoids outdoors, with a main focus on beta-carotene from Dunaliella, astaxanthin from Haematococcus, and lutein from chlorophycean strains. We compare the current state of the corresponding production technologies, based on either open-pond systems or closed photobioreactors. The potential of scientific and technological advances for improvements in yield and reduction in production costs for carotenoids from microalgae is also discussed.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

PubMed

Castro-Mondragon, Jaime Abraham; Jaeger, Sébastien; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2017-07-27

Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

LiverAtlas: a unique integrated knowledge database for systems-level research of liver and hepatic disease.

PubMed

Zhang, Yanqiong; Yang, Chunyuan; Wang, Shaochuang; Chen, Tao; Li, Mansheng; Wang, Xue; Li, Dongsheng; Wang, Kang; Ma, Jie; Wu, Songfeng; Zhang, Xueli; Zhu, Yunping; Wu, Jinsheng; He, Fuchu

2013-09-01

A large amount of liver-related physiological and pathological data exist in publicly available biological and bibliographic databases, which are usually far from comprehensive or integrated. Data collection, integration and mining processes pose a great challenge to scientific researchers and clinicians interested in the liver. To address these problems, we constructed LiverAtlas (http://liveratlas.hupo.org.cn), a comprehensive resource of biomedical knowledge related to the liver and various hepatic diseases by incorporating 53 databases. In the present version, LiverAtlas covers data on liver-related genomics, transcriptomics, proteomics, metabolomics and hepatic diseases. Additionally, LiverAtlas provides a wealth of manually curated information, relevant literature citations and cross-references to other databases. Importantly, an expert-confirmed Human Liver Disease Ontology, including relevant information for 227 types of hepatic disease, has been constructed and is used to annotate LiverAtlas data. Furthermore, we have demonstrated two examples of applying LiverAtlas data to identify candidate markers for hepatocellular carcinoma (HCC) at the systems level and to develop a systems biology-based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC differential diagnosis. LiverAtlas is the most comprehensive liver and hepatic disease resource, which helps biologists and clinicians to analyse their data at the systems level and will contribute much to the biomarker discovery and diagnostic performance enhancement for liver diseases. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Analysis and prediction of presynaptic and postsynaptic neurotoxins by Chou's general pseudo amino acid composition and motif features.

PubMed

Mei, Juan; Zhao, Ji

2018-06-14

Presynaptic neurotoxins and postsynaptic neurotoxins are two important neurotoxins isolated from venoms of venomous animals and have been proven to be potential effective in neurosciences and pharmacology. With the number of toxin sequences appeared in the public databases, there was a need for developing a computational method for fast and accurate identification and classification of the novel presynaptic neurotoxins and postsynaptic neurotoxins in the large databases. In this study, the Multinomial Naive Bayes Classifier (MNBC) had been developed to discriminate the presynaptic neurotoxins and postsynaptic neurotoxins based on the different kinds of features. The Minimum Redundancy Maximum Relevance (MRMR) feature selection method was used for ranking 400 pseudo amino acid (PseAA) compositions and 50 top ranked PseAA compositions were selected for improving the prediction results. The motif features, 400 PseAA compositions and 50 PseAA compositions were combined together, and selected as the input parameters of MNBC. The best correlation coefficient (CC) value of 0.8213 was obtained when the prediction quality was evaluated by the jackknife test. It was anticipated that the algorithm presented in this study may become a useful tool for identification of presynaptic neurotoxin and postsynaptic neurotoxin sequences and may provide some useful help for in-depth investigation into the biological mechanism of presynaptic neurotoxins and postsynaptic neurotoxins. Copyright © 2018 Elsevier Ltd. All rights reserved.

Velocity-curvature patterns limit human-robot physical interaction

PubMed Central

Maurice, Pauline; Huber, Meghan E.; Hogan, Neville; Sternad, Dagmar

2018-01-01

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration. PMID:29744380

Velocity-curvature patterns limit human-robot physical interaction.

PubMed

Maurice, Pauline; Huber, Meghan E; Hogan, Neville; Sternad, Dagmar

2018-01-01

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.

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

PubMed

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.

Sociability modifies dogs' sensitivity to biological motion of different social relevance.

PubMed

Ishikawa, Yuko; Mills, Daniel; Willmott, Alexander; Mullineaux, David; Guo, Kun

2018-03-01

Preferential attention to living creatures is believed to be an intrinsic capacity of the visual system of several species, with perception of biological motion often studied and, in humans, it correlates with social cognitive performance. Although domestic dogs are exceptionally attentive to human social cues, it is unknown whether their sociability is associated with sensitivity to conspecific and heterospecific biological motion cues of different social relevance. We recorded video clips of point-light displays depicting a human or dog walking in either frontal or lateral view. In a preferential looking paradigm, dogs spontaneously viewed 16 paired point-light displays showing combinations of normal/inverted (control condition), human/dog and frontal/lateral views. Overall, dogs looked significantly longer at frontal human point-light display versus the inverted control, probably due to its clearer social/biological relevance. Dogs' sociability, assessed through owner-completed questionnaires, further revealed that low-sociability dogs preferred the lateral point-light display view, whereas high-sociability dogs preferred the frontal view. Clearly, dogs can recognize biological motion, but their preference is influenced by their sociability and the stimulus salience, implying biological motion perception may reflect aspects of dogs' social cognition.

Noun and knowledge retrieval for biological and non-biological entities following right occipitotemporal lesions.

PubMed

Bruffaerts, Rose; De Weer, An-Sofie; De Grauwe, Sophie; Thys, Miek; Dries, Eva; Thijs, Vincent; Sunaert, Stefan; Vandenbulcke, Mathieu; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2014-09-01

We investigated the critical contribution of right ventral occipitotemporal cortex to knowledge of visual and functional-associative attributes of biological and non-biological entities and how this relates to category-specificity during confrontation naming. In a consecutive series of 7 patients with lesions confined to right ventral occipitotemporal cortex, we conducted an extensive assessment of oral generation of visual-sensory and functional-associative features in response to the names of biological and nonbiological entities. Subjects also performed a confrontation naming task for these categories. Our main novel finding related to a unique case with a small lesion confined to right medial fusiform gyrus who showed disproportionate naming impairment for nonbiological versus biological entities, specifically for tools. Generation of visual and functional-associative features was preserved for biological and non-biological entities. In two other cases, who had a relatively small posterior lesion restricted to primary visual and posterior fusiform cortex, retrieval of visual attributes was disproportionately impaired compared to functional-associative attributes, in particular for biological entities. However, these cases did not show a category-specific naming deficit. Two final cases with the largest lesions showed a classical dissociation between biological versus nonbiological entities during naming, with normal feature generation performance. This is the first lesion-based evidence of a critical contribution of the right medial fusiform cortex to tool naming. Second, dissociations along the dimension of attribute type during feature generation do not co-occur with category-specificity during naming in the current patient sample. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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.

The good taste of peptides.

PubMed

Temussi, Piero A

2012-02-01

The taste of peptides is seldom one of the most relevant issues when one considers the many important biological functions of this class of molecules. However, peptides generally do have a taste, covering essentially the entire range of established taste modalities: sweet, bitter, umami, sour and salty. The last two modalities cannot be attributed to peptides as such because they are due to the presence of charged terminals and/or charged side chains, thus reflecting only the zwitterionic nature of these compounds and/or the nature of some side chains but not the electronic and/or conformational features of a specific peptide. The other three tastes, that is, sweet, umami and bitter, are represented by different families of peptides. This review describes the main peptides with a sweet, umami or bitter taste and their relationship with food acceptance or rejection. Particular emphasis will be given to the sweet taste modality, owing to the practical and scientific relevance of aspartame, the well-known sweetener, and to the theoretical importance of sweet proteins, the most potent peptide sweet molecules. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.

A report on older-age bipolar disorder from the International Society for Bipolar Disorders Task Force

PubMed Central

Sajatovic, Martha; Strejilevich, Sergio A; Gildengers, Ariel G; Dols, Annemiek; Al Jurdi, Rayan K; Forester, Brent P; Kessing, Lars Vedel; Beyer, John; Manes, Facundo; Rej, Soham; Rosa, Adriane R; Schouws, Sigfried NTM; Tsai, Shang-Ying; Young, Robert C; Shulman, Kenneth I

2015-01-01

Objectives In the coming generation, older adults with bipolar disorder (BD) will increase in absolute numbers as well as proportion of the general population. This is the first report of the International Society for Bipolar Disorder (ISBD) Task Force on Older-Age Bipolar Disorder (OABD). Methods This task force report addresses the unique aspects of OABD including epidemiology and clinical features, neuropathology and biomarkers, physical health, cognition, and care approaches. Results The report describes an expert consensus summary on OABD that is intended to advance the care of patients, and shed light on issues of relevance to BD research across the lifespan. Although there is still a dearth of research and health efforts focused on older adults with BD, emerging data has brought some answers, innovative questions, and novel perspectives related to the notion of late onset, medical comorbidity, and the vexing issue of cognitive impairment and decline. Conclusions Improving our understanding of the biological, clinical, and social underpinnings relevant to OABD is an indispensable step in building a complete map of BD across the lifespan. PMID:26384588

Clustering document fragments using background color and texture information

NASA Astrophysics Data System (ADS)

Chanda, Sukalpa; Franke, Katrin; Pal, Umapada

2012-01-01

Forensic analysis of questioned documents sometimes can be extensively data intensive. A forensic expert might need to analyze a heap of document fragments and in such cases to ensure reliability he/she should focus only on relevant evidences hidden in those document fragments. Relevant document retrieval needs finding of similar document fragments. One notion of obtaining such similar documents could be by using document fragment's physical characteristics like color, texture, etc. In this article we propose an automatic scheme to retrieve similar document fragments based on visual appearance of document paper and texture. Multispectral color characteristics using biologically inspired color differentiation techniques are implemented here. This is done by projecting document color characteristics to Lab color space. Gabor filter-based texture analysis is used to identify document texture. It is desired that document fragments from same source will have similar color and texture. For clustering similar document fragments of our test dataset we use a Self Organizing Map (SOM) of dimension 5×5, where the document color and texture information are used as features. We obtained an encouraging accuracy of 97.17% from 1063 test images.

Fluid models and simulations of biological cell phenomena

NASA Technical Reports Server (NTRS)

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.

Outlier analysis of functional genomic profiles enriches for oncology targets and enables precision medicine.

PubMed

Zhu, Zhou; Ihle, Nathan T; Rejto, Paul A; Zarrinkar, Patrick P

2016-06-13

Genome-scale functional genomic screens across large cell line panels provide a rich resource for discovering tumor vulnerabilities that can lead to the next generation of targeted therapies. Their data analysis typically has focused on identifying genes whose knockdown enhances response in various pre-defined genetic contexts, which are limited by biological complexities as well as the incompleteness of our knowledge. We thus introduce a complementary data mining strategy to identify genes with exceptional sensitivity in subsets, or outlier groups, of cell lines, allowing an unbiased analysis without any a priori assumption about the underlying biology of dependency. Genes with outlier features are strongly and specifically enriched with those known to be associated with cancer and relevant biological processes, despite no a priori knowledge being used to drive the analysis. Identification of exceptional responders (outliers) may not lead only to new candidates for therapeutic intervention, but also tumor indications and response biomarkers for companion precision medicine strategies. Several tumor suppressors have an outlier sensitivity pattern, supporting and generalizing the notion that tumor suppressors can play context-dependent oncogenic roles. The novel application of outlier analysis described here demonstrates a systematic and data-driven analytical strategy to decipher large-scale functional genomic data for oncology target and precision medicine discoveries.

How to build an information gathering and processing system: lessons from naturally and artificially intelligent systems.

PubMed

Chappell, Jackie; Demery, Zoe P; Arriola-Rios, Veronica; Sloman, Aaron

2012-02-01

Imagine a situation in which you had to design a physical agent that could collect information from its environment, then store and process that information to help it respond appropriately to novel situations. What kinds of information should it attend to? How should the information be represented so as to allow efficient use and re-use? What kinds of constraints and trade-offs would there be? There are no unique answers. In this paper, we discuss some of the ways in which the need to be able to address problems of varying kinds and complexity can be met by different information processing systems. We also discuss different ways in which relevant information can be obtained, and how different kinds of information can be processed and used, by both biological organisms and artificial agents. We analyse several constraints and design features, and show how they relate both to biological organisms, and to lessons that can be learned from building artificial systems. Our standpoint overlaps with Karmiloff-Smith (1992) in that we assume that a collection of mechanisms geared to learning and developing in biological environments are available in forms that constrain, but do not determine, what can or will be learnt by individuals. Copyright © 2011 Elsevier B.V. All rights reserved.

A review of the biological and clinical aspects of radiation caries.

PubMed

Aguiar, Gabrielle P; Jham, Bruno C; Magalhães, Cláudia S; Sensi, Luis Guilherme; Freire, Addah R

2009-07-01

The aim of this article is to review the clinical and biological features underlying the development and progression of radiation caries. Although radiotherapy (RT) plays an important role in the management of patients with head and neck cancer (HNC), it is also associated with several undesired side effects such as radiation caries which is a common, yet serious, complication. To review the condition, the Pubmed database was searched using the keywords "radiotherapy," "radiation," "caries," "hyposalivation," "prevention" and "management". Only studies published in the English language were selected. Cross-referencing identified additionally relevant studies. RT leads to alterations in the dentition, saliva, oral microflora, and diet of patients. Consequently, irradiated patients are at increased risk for the development of a rapid, rampant carious process known as radiation caries. Motivation of patients, adequate plaque control, stimulation of salivary flow, fluoride use, and nutritional orientation are essential to reduce the incidence of radiation caries and ultimately improve the quality of life for HNC patients. Radiation caries is an aggressive side effect of RT. Dentists play an important role in the prevention of the condition via comprehensive oral healthcare before, during, and after the active cancer therapy. Dentists should understand the clinical and biological aspects underlying radiation caries to prevent the development of lesions and provide optimal treatment when needed.

Immortalized N/TERT keratinocytes as an alternative cell source in 3D human epidermal models.

PubMed

Smits, Jos P H; Niehues, Hanna; Rikken, Gijs; van Vlijmen-Willems, Ivonne M J J; van de Zande, Guillaume W H J F; Zeeuwen, Patrick L J M; Schalkwijk, Joost; van den Bogaard, Ellen H

2017-09-19

The strong societal urge to reduce the use of experimental animals, and the biological differences between rodent and human skin, have led to the development of alternative models for healthy and diseased human skin. However, the limited availability of primary keratinocytes to generate such models hampers large-scale implementation of skin models in biomedical, toxicological, and pharmaceutical research. Immortalized cell lines may overcome these issues, however, few immortalized human keratinocyte cell lines are available and most do not form a fully stratified epithelium. In this study we compared two immortalized keratinocyte cell lines (N/TERT1, N/TERT2G) to human primary keratinocytes based on epidermal differentiation, response to inflammatory mediators, and the development of normal and inflammatory human epidermal equivalents (HEEs). Stratum corneum permeability, epidermal morphology, and expression of epidermal differentiation and host defence genes and proteins in N/TERT-HEE cultures was similar to that of primary human keratinocytes. We successfully generated N/TERT-HEEs with psoriasis or atopic dermatitis features and validated these models for drug-screening purposes. We conclude that the N/TERT keratinocyte cell lines are useful substitutes for primary human keratinocytes thereby providing a biologically relevant, unlimited cell source for in vitro studies on epidermal biology, inflammatory skin disease pathogenesis and therapeutics.

Ezrin and moesin expression in canine and feline osteosarcoma.

PubMed

Hlavaty, Juraj; Wolfesberger, Birgitt; Hauck, Marlene; Obermayer-Pietsch, Barbara; Fuchs-Baumgartinger, Andrea; Miller, Ingrid; Walter, Ingrid

2017-08-01

Biological features of canine osteosarcomas (OS) differ markedly from those found in feline and resemble more human osteosarcomas, in particular for their high rate of metastasis and poor prognosis. Ezrin, radixin and moesin are members of the ERM protein family and link the actin cytoskeleton with the cell membrane. Ezrin and moesin have been shown to be of prognostic significance in tumor progression due to their role in the metastatic process. The objective of this study was to analyze ezrin and moesin protein expression in a series of dog (n = 16) and cat (n = 8) osteosarcoma samples using immunohistochemistry and western blot techniques. We found that cat OS have a higher moesin expression compared to dog OS, however, the active phosphorylated forms of moesin and ezrin Tyr353 were more abundant in the dog samples. A statistically significant difference was found for the low and high immunohistochemical scores of ezrin and pan-phospho-ERM proteins between cat and dog. Although phospho-ezrin Thr567 was higher in feline OS, the membranous localization in dog OS samples indicates the presence of the biologically active form. Therefore, the observed differences in phosphorylated forms of ezrin and moesin status should be further studied to demonstrate if they are relevant for different biological behavior between dog and cat OS.

Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

PubMed

Basu, Sumanta; Duren, William; Evans, Charles R; Burant, Charles F; Michailidis, George; Karnovsky, Alla

2017-05-15

Recent technological advances in mass spectrometry, development of richer mass spectral libraries and data processing tools have enabled large scale metabolic profiling. Biological interpretation of metabolomics studies heavily relies on knowledge-based tools that contain information about metabolic pathways. Incomplete coverage of different areas of metabolism and lack of information about non-canonical connections between metabolites limits the scope of applications of such tools. Furthermore, the presence of a large number of unknown features, which cannot be readily identified, but nonetheless can represent bona fide compounds, also considerably complicates biological interpretation of the data. Leveraging recent developments in the statistical analysis of high-dimensional data, we developed a new Debiased Sparse Partial Correlation algorithm (DSPC) for estimating partial correlation networks and implemented it as a Java-based CorrelationCalculator program. We also introduce a new version of our previously developed tool Metscape that enables building and visualization of correlation networks. We demonstrate the utility of these tools by constructing biologically relevant networks and in aiding identification of unknown compounds. http://metscape.med.umich.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Pre-eclampsia and offspring cardiovascular health: mechanistic insights from experimental studies.

PubMed

Davis, Esther F; Newton, Laura; Lewandowski, Adam J; Lazdam, Merzaka; Kelly, Brenda A; Kyriakou, Theodosios; Leeson, Paul

2012-07-01

Pre-eclampsia is increasingly recognized as more than an isolated disease of pregnancy. Women who have had a pregnancy complicated by pre-eclampsia have a 4-fold increased risk of later cardiovascular disease. Intriguingly, the offspring of affected pregnancies also have an increased risk of higher blood pressure and almost double the risk of stroke in later life. Experimental approaches to identify the key features of pre-eclampsia responsible for this programming of offspring cardiovascular health, or the key biological pathways modified in the offspring, have the potential to highlight novel targets for early primary prevention strategies. As pre-eclampsia occurs in 2-5% of all pregnancies, the findings are relevant to the current healthcare of up to 3 million people in the U.K. and 15 million people in the U.S.A. In the present paper, we review the current literature that concerns potential mechanisms for adverse cardiovascular programming in offspring exposed to pre-eclampsia, considering two major areas of investigation: first, experimental models that mimic features of the in utero environment characteristic of pre-eclampsia, and secondly, how, in humans, offspring cardiovascular phenotype is altered after exposure to pre-eclampsia. We compare and contrast the findings from these two bodies of work to develop insights into the likely key pathways of relevance. The present review and analysis highlights the pivotal role of long-term changes in vascular function and identifies areas of growing interest, specifically, response to hypoxia, immune modification, epigenetics and the anti-angiogenic in utero milieu.

Construction and analysis of lncRNA-lncRNA synergistic networks to reveal clinically relevant lncRNAs in cancer.

PubMed

Li, Yongsheng; Chen, Juan; Zhang, Jinwen; Wang, Zishan; Shao, Tingting; Jiang, Chunjie; Xu, Juan; Li, Xia

2015-09-22

Long non-coding RNAs (lncRNAs) play key roles in diverse biological processes. Moreover, the development and progression of cancer often involves the combined actions of several lncRNAs. Here we propose a multi-step method for constructing lncRNA-lncRNA functional synergistic networks (LFSNs) through co-regulation of functional modules having three features: common coexpressed genes of lncRNA pairs, enrichment in the same functional category and close proximity within protein interaction networks. Applied to three cancers, we constructed cancer-specific LFSNs and found that they exhibit a scale free and modular architecture. In addition, cancer-associated lncRNAs tend to be hubs and are enriched within modules. Although there is little synergistic pairing of lncRNAs across cancers, lncRNA pairs involved in the same cancer hallmarks by regulating same or different biological processes. Finally, we identify prognostic biomarkers within cancer lncRNA expression datasets using modules derived from LFSNs. In summary, this proof-of-principle study indicates synergistic lncRNA pairs can be identified through integrative analysis of genome-wide expression data sets and functional information.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

NASA Astrophysics Data System (ADS)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing

NASA Technical Reports Server (NTRS)

Farhat, Nabil H.

1987-01-01

Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.

Iris phenotypes and pigment dispersion caused by genes influencing pigmentation

PubMed Central

Hawes, Norman L.; Trantow, Colleen M.; Chang, Bo; John, Simon W.M.

2010-01-01

Summary Spontaneous mutations altering mouse coat colors have been a classic resource for discovery of numerous molecular pathways. Although often overlooked, the mouse iris is also densely pigmented and easily observed, thus representing a similarly powerful opportunity for studying pigment cell biology. Here, we present an analysis of iris phenotypes among sixteen mouse strains with mutations influencing melanosomes. Many of these strains exhibit biologically and medically relevant phenotypes, including pigment dispersion, a common feature of several human ocular diseases. Pigment dispersion was identified in several strains with mutant alleles known to influence melanosomes, including beige, light, and vitiligo. Pigment dispersion was also detected in the recently arising spontaneous coat color variant, nm2798. We have identified the nm2798 mutation as a missense mutation in the Dct gene, an identical re-occurrence of the slaty light mutation. These results suggest that dysregulated events of melanosomes can be potent contributors to the pigment dispersion phenotype. Combined, these findings illustrate the utility of studying iris phenotypes as a means of discovering new pathways, and re-linking old ones, to processes of pigmented cells in health and disease. PMID:18715234

Iris phenotypes and pigment dispersion caused by genes influencing pigmentation.

PubMed

Anderson, Michael G; Hawes, Norman L; Trantow, Colleen M; Chang, Bo; John, Simon W M

2008-10-01

Spontaneous mutations altering mouse coat colors have been a classic resource for discovery of numerous molecular pathways. Although often overlooked, the mouse iris is also densely pigmented and easily observed, thus representing a similarly powerful opportunity for studying pigment cell biology. Here, we present an analysis of iris phenotypes among 16 mouse strains with mutations influencing melanosomes. Many of these strains exhibit biologically and medically relevant phenotypes, including pigment dispersion, a common feature of several human ocular diseases. Pigment dispersion was identified in several strains with mutant alleles known to influence melanosomes, including beige, light, and vitiligo. Pigment dispersion was also detected in the recently arising spontaneous coat color variant, nm2798. We have identified the nm2798 mutation as a missense mutation in the Dct gene, an identical re-occurrence of the slaty light mutation. These results suggest that dysregulated events of melanosomes can be potent contributors to the pigment dispersion phenotype. Combined, these findings illustrate the utility of studying iris phenotypes as a means of discovering new pathways, and re-linking old ones, to processes of pigmented cells in health and disease.

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

Biological Relevance of Key Events (KE) in utero in The Androgen Adverse Outcome Pathway Network (AOPn) to Adverse Effects in F1 Male Rats

EPA Science Inventory

We are conducting studies to evaluate the biological relevance of changes in KEs and molecular initiating events (MIE) in AOPs to determine if these can accurately predict of the dose levels of chemicals that disrupt the androgen signaling pathway in utero. Herein, we focus on ch...

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

ERIC Educational Resources Information Center

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…

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

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

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

DOE PAGES

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya; ...

2017-11-30

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Protein control of true, gated, and coupled electron transfer reactions.

PubMed

Davidson, Victor L

2008-06-01

Electron transfer (ET) through and between proteins is a fundamental biological process. The rates of ET depend upon the thermodynamic driving force, the reorganization energy, and the degree of electronic coupling between the reactant and product states. The analysis of protein ET reactions is complicated by the fact that non-ET processes might influence the observed ET rate in kinetically complex biological systems. This Account describes studies of the methylamine dehydrogenase-amicyanin-cytochrome c-551i protein ET complex that have revealed the influence of several features of the protein structure on the magnitudes of the physical parameters for true ET reactions and how they dictate the kinetic mechanisms of non-ET processes that sometimes influence protein ET reactions. Kinetic and thermodynamic studies, coupled with structural information and biochemical data, are necessary to fully describe the ET reactions of proteins. Site-directed mutagenesis can be used to elucidate specific structure-function relationships. When mutations selectively alter the electronic coupling, reorganization energy, or driving force for the ET reaction, it becomes possible to use the parameters of the ET process to determine how specific amino acid residues and other features of the protein structure influence the ET rates. When mutations alter the kinetic mechanism for ET, one can determine the mechanisms by which non-ET processes, such as protein conformational changes or proton transfers, control the rates of ET reactions and how specific amino acid residues and certain features of the protein structure influence these non-ET reactions. A complete description of the mechanism of regulation of biological ET reactions enhances our understanding of metabolism, respiration, and photosynthesis at the molecular level. Such information has important medical relevance. Defective protein ET leads to production of the reactive oxygen species and free radicals that are associated with aging and many disease states. Defective ET within the respiratory chain also causes certain mitochondrial myopathies. An understanding of the mechanisms of regulation of protein ET is also of practical value because it provides a logical basis for the design of applications utilizing redox enzymes, such as enzyme-based electrode sensors and fuel cells.

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.

PubMed

Taguchi, Y-H

2018-05-08

Even though coexistence of multiple phenotypes sharing the same genomic background is interesting, it remains incompletely understood. Epigenomic profiles may represent key factors, with unknown contributions to the development of multiple phenotypes, and social-insect castes are a good model for elucidation of the underlying mechanisms. Nonetheless, previous studies have failed to identify genes associated with aberrant gene expression and methylation profiles because of the lack of suitable methodology that can address this problem properly. A recently proposed principal component analysis (PCA)-based and tensor decomposition (TD)-based unsupervised feature extraction (FE) can solve this problem because these two approaches can deal with gene expression and methylation profiles even when a small number of samples is available. PCA-based and TD-based unsupervised FE methods were applied to the analysis of gene expression and methylation profiles in the brains of two social insects, Polistes canadensis and Dinoponera quadriceps. Genes associated with differential expression and methylation between castes were identified, and analysis of enrichment of Gene Ontology terms confirmed reliability of the obtained sets of genes from the biological standpoint. Biologically relevant genes, shown to be associated with significant differential gene expression and methylation between castes, were identified here for the first time. The identification of these genes may help understand the mechanisms underlying epigenetic control of development of multiple phenotypes under the same genomic conditions.

Biological and Clinical Aspects of Lanthanide Coordination Compounds

PubMed Central

Misra, Sudhindra N.; M., Indira Devi; Shukla, Ram S.

2004-01-01

The coordinating chemistry of lanthanides, relevant to the biological, biochemical and medical aspects, makes a significant contribution to understanding the basis of application of lanthanides, particularly in biological and medical systems. The importance of the applications of lanthanides, as an excellent diagnostic and prognostic probe in clinical diagnostics, and an anticancer material, is remarkably increasing. Lanthanide complexes based X-ray contrast imaging and lanthanide chelates based contrast enhancing agents for magnetic resonance imaging (MRI) are being excessively used in radiological analysis in our body systems. The most important property of the chelating agents, in lanthanide chelate complex, is its ability to alter the behaviour of lanthanide ion with which it binds in biological systems, and the chelation markedly modifies the biodistribution and excretion profile of the lanthanide ions. The chelating agents, especially aminopoly carboxylic acids, being hydrophilic, increase the proportion of their complex excreted from complexed lanthanide ion form biological systems. Lanthanide polyamino carboxylate-chelate complexes are used as contrast enhancing agents for Magnetic Resonance Imaging. Conjugation of antibodies and other tissue specific molecules to lanthanide chelates has led to a new type of specific MRI contrast agents and their conjugated MRI contrast agents with improved relaxivity, functioning in the body similar to drugs. Many specific features of contrast agent assisted MRI make it particularly effective for musculoskeletal and cerebrospinal imaging. Lanthanide-chelate contrast agents are effectively used in clinical diagnostic investigations involving cerebrospinal diseases and in evaluation of central nervous system. Chelated lanthanide complexes shift reagent aided 23Na NMR spectroscopic analysis is used in cellular, tissue and whole organ systems. PMID:18365075

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

PubMed

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 (<5%) with activity concentration and reconstruction protocol making them suitable for heterogeneity quantification. On the other hand, there is a high statistically significant correlation between MAV and entropy (P<0.05). Entropy feature is, indeed, correlated (P<0.05) with all patient parameters, except body mass index. The textural 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.

Feature saliency and feedback information interactively impact visual category learning

PubMed Central

Hammer, Rubi; Sloutsky, Vladimir; Grill-Spector, Kalanit

2015-01-01

Visual category learning (VCL) involves detecting which features are most relevant for categorization. VCL relies on attentional learning, which enables effectively redirecting attention to object’s features most relevant for categorization, while ‘filtering out’ irrelevant features. When features relevant for categorization are not salient, VCL relies also on perceptual learning, which enables becoming more sensitive to subtle yet important differences between objects. Little is known about how attentional learning and perceptual learning interact when VCL relies on both processes at the same time. Here we tested this interaction. Participants performed VCL tasks in which they learned to categorize novel stimuli by detecting the feature dimension relevant for categorization. Tasks varied both in feature saliency (low-saliency tasks that required perceptual learning vs. high-saliency tasks), and in feedback information (tasks with mid-information, moderately ambiguous feedback that increased attentional load, vs. tasks with high-information non-ambiguous feedback). We found that mid-information and high-information feedback were similarly effective for VCL in high-saliency tasks. This suggests that an increased attentional load, associated with the processing of moderately ambiguous feedback, has little effect on VCL when features are salient. In low-saliency tasks, VCL relied on slower perceptual learning; but when the feedback was highly informative participants were able to ultimately attain the same performance as during the high-saliency VCL tasks. However, VCL was significantly compromised in the low-saliency mid-information feedback task. We suggest that such low-saliency mid-information learning scenarios are characterized by a ‘cognitive loop paradox’ where two interdependent learning processes have to take place simultaneously. PMID:25745404

The Biology of Cancer Health Disparities

Cancer.gov

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.

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Organic Nanoflowers from a Wide Variety of Molecules Templated by a Hierarchical Supramolecular Scaffold.

PubMed

Negrón, Luis M; Díaz, Tanya L; Ortiz-Quiles, Edwin O; Dieppa-Matos, Diómedes; Madera-Soto, Bismark; Rivera, José M

2016-03-15

Nanoflowers (NFs) are flowered-shaped particles with overall sizes or features in the nanoscale. Beyond their pleasing aesthetics, NFs have found a number of applications ranging from catalysis, to sensing, to drug delivery. Compared to inorganic based NFs, their organic and hybrid counterparts are relatively underdeveloped mostly because of the lack of a reliable and versatile method for their construction. We report here a method for constructing NFs from a wide variety of biologically relevant molecules (guests), ranging from small molecules, like doxorubicin, to biomacromolecules, like various proteins and plasmid DNA. The method relies on the encapsulation of the guests within a hierarchically structured particle made from supramolecular G-quadruplexes. The size and overall flexibility of the guests dictate the broad morphological features of the resulting NFs, specifically, small and rigid guests favor the formation of NFs with spiky petals, while large and/or flexible guests promote NFs with wide petals. The results from experiments using confocal fluorescence microscopy, and scanning electron microscopy provides the basis for the proposed mechanism for the NF formation.

Mitochondrial ADCK3 employs an atypical protein kinase-like fold to enable coenzyme Q biosynthesis

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

Stefely, Jonathan A.; Reidenbach, Andrew G.; Ulbrich, Arne

The ancient UbiB protein kinase-like family is involved in isoprenoid lipid biosynthesis and is implicated in human diseases, but demonstration of UbiB kinase activity has remained elusive for unknown reasons. In this paper, we quantitatively define UbiB-specific sequence motifs and reveal their positions within the crystal structure of a UbiB protein, ADCK3. We find that multiple UbiB-specific features are poised to inhibit protein kinase activity, including an N-terminal domain that occupies the typical substrate binding pocket and a unique A-rich loop that limits ATP binding by establishing an unusual selectivity for ADP. A single alanine-to-glycine mutation of this loop flipsmore » this coenzyme selectivity and enables autophosphorylation but inhibits coenzyme Q biosynthesis in vivo, demonstrating functional relevance for this unique feature. Finally, our work provides mechanistic insight into UbiB enzyme activity and establishes a molecular foundation for further investigation of how UbiB family proteins affect diseases and diverse biological pathways.« less

Mitochondrial ADCK3 employs an atypical protein kinase-like fold to enable coenzyme Q biosynthesis

DOE PAGES

Stefely, Jonathan A.; Reidenbach, Andrew G.; Ulbrich, Arne; ...

2014-12-11

The ancient UbiB protein kinase-like family is involved in isoprenoid lipid biosynthesis and is implicated in human diseases, but demonstration of UbiB kinase activity has remained elusive for unknown reasons. In this paper, we quantitatively define UbiB-specific sequence motifs and reveal their positions within the crystal structure of a UbiB protein, ADCK3. We find that multiple UbiB-specific features are poised to inhibit protein kinase activity, including an N-terminal domain that occupies the typical substrate binding pocket and a unique A-rich loop that limits ATP binding by establishing an unusual selectivity for ADP. A single alanine-to-glycine mutation of this loop flipsmore » this coenzyme selectivity and enables autophosphorylation but inhibits coenzyme Q biosynthesis in vivo, demonstrating functional relevance for this unique feature. Finally, our work provides mechanistic insight into UbiB enzyme activity and establishes a molecular foundation for further investigation of how UbiB family proteins affect diseases and diverse biological pathways.« less

Machine-assisted discovery of relationships in astronomy

NASA Astrophysics Data System (ADS)

Graham, Matthew J.; Djorgovski, S. G.; Mahabal, Ashish A.; Donalek, Ciro; Drake, Andrew J.

2013-05-01

High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of parameters is non-trivial. Similar problems in biological and geosciences have led to the development of systems which can explore large parameter spaces and identify potentially interesting sets of associations. In this paper, we describe the application of automated discovery systems of relationships to astronomical data sets, focusing on an evolutionary programming technique and an information-theory technique. We demonstrate their use with classical astronomical relationships - the Hertzsprung-Russell diagram and the Fundamental Plane of elliptical galaxies. We also show how they work with the issue of binary classification which is relevant to the next generation of large synoptic sky surveys, such as the Large Synoptic Survey Telescope (LSST). We find that comparable results to more familiar techniques, such as decision trees, are achievable. Finally, we consider the reality of the relationships discovered and how this can be used for feature selection and extraction.

What amyloidoses may tell us about normal protein folding: The Alzheimer's disease story

NASA Astrophysics Data System (ADS)

Teplow, David B.

2002-03-01

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder characterized by severe neuronal injury and death. A prominent histopathologic feature of AD is disseminated parenchymal and vascular amyloid deposition. The fibrils in these deposits are composed of the amyloid β-protein (Aβ), a peptide of 4 kDa mass. In vitro and in vivo studies of Aβ fibril formation have shown that both oligomeric and polymeric Aβ assemblies have neurotoxic activity. Understanding how these assemblies form thus could be of direct therapeutic relevance. However, the aggregation and fibril-forming propensities of Aβ have complicated structure determination. Nevertheless, careful morphologic, spectroscopic, protein chemical, and physiologic analyses of the time-dependent changes in Aβ conformation, assembly state, and biological activity which occur during fibrillogenesis have significantly advanced our understanding of this clinically important process. Here, I will discuss recent findings about the pathway(s) of Aβ folding and assembly and about key structural features of Aβ which control the associated kinetics. Interestingly, the amyloidogenic folding pathway of Aβ is in some respects the mirror image of that through which natively folded amyloidogenic proteins proceed.

High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

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

2016-07-01

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

Pomegranate peel and peel extracts: chemistry and food features.

PubMed

Akhtar, Saeed; Ismail, Tariq; Fraternale, Daniele; Sestili, Piero

2015-05-01

The present review focuses on the nutritional, functional and anti-infective properties of pomegranate (Punica granatum L.) peel (PoP) and peel extract (PoPx) and on their applications as food additives, functional food ingredients or biologically active components in nutraceutical preparations. Due to their well-known ethnomedical relevance and chemical features, the biomolecules available in PoP and PoPx have been proposed, for instance, as substitutes of synthetic food additives, as nutraceuticals and chemopreventive agents. However, because of their astringency and anti-nutritional properties, PoP and PoPx are not yet considered as ingredients of choice in food systems. Indeed, considering the prospects related to both their health promoting activity and chemical features, the nutritional and nutraceutical potential of PoP and PoPx seems to be still underestimated. The present review meticulously covers the wide range of actual and possible applications (food preservatives, stabilizers, supplements, prebiotics and quality enhancers) of PoP and PoPx components in various food products. Given the overall properties of PoP and PoPx, further investigations in toxicological and sensory aspects of PoP and PoPx should be encouraged to fully exploit the health promoting and technical/economic potential of these waste materials as food supplements. Copyright © 2014 Elsevier Ltd. All rights reserved.

Herb Medicines against Osteoporosis: Active Compounds & Relevant Biological Mechanisms.

PubMed

Wu, Lei; Ling, Zhuoyan; Feng, Xueqin; Mao, Caiping; Xu, Zhice

2017-01-01

Osteoporosis is one of common bone disorders, affecting millions of people worldwide. Treatments of osteoporosis consist of pharmacotherapy and non-pharmacological interventions, such as mineral supplementation, lifestyle changes, and exercise programs. Due to the minimum side effects and favorable cost-effective therapeutic effects, herbal medicine has been widely applied in clinical practices for more than 2,000 years in China. Of the many traditional formulas reported for treating bone diseases, 4 single herbs namely (1) Herba Epimedii, (2) Rhizoma Drynariae, (3) Fructus Psoraleae, and (4) Cortex Eucommiae, are considered as the featured "Kidney-Yang" tonics, and frequently and effectively applied for preventing and treating osteoporosis. With the accruing development of modern chemistry, hundreds of active compounds have been identified and isolated for their anti-osteoporotic effects. This review would first sketch the phytochemistry of these featured "Kidney- Yang" tonics and present the pharmacological characteristics of the most abundant and bioactive compounds derived from the herb Herba Epimedii and Rhizoma Drynariae, including icariin and naringin. Then, the cellular and molecular underpinnings under anti-osteoporotic effects of icariin and naringin are discussed. The concerned structure-function relationships of the featured active herbal compounds would also be reviewed so as to pave the way for future drug design in treating osteoporosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach.

PubMed

Schmidt, Ellen M; Zhang, Ji; Zhou, Wei; Chen, Jin; Mohlke, Karen L; Chen, Y Eugene; Willer, Cristen J

2015-08-15

The majority of variation identified by genome wide association studies falls in non-coding genomic regions and is hypothesized to impact regulatory elements that modulate gene expression. Here we present a statistically rigorous software tool GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) for evaluating enrichment of any set of genetic variants with any set of regulatory features. Using variants from five phenotypes, we describe a data-driven approach to determine the tissue and cell types most relevant to a trait of interest and to identify the subset of regulatory features likely impacted by these variants. Last, we experimentally evaluate six predicted functional variants at six lipid-associated loci and demonstrate significant evidence for allele-specific impact on expression levels. GREGOR systematically evaluates enrichment of genetic variation with the vast collection of regulatory data available to explore novel biological mechanisms of disease and guide us toward the functional variant at trait-associated loci. GREGOR, including source code, documentation, examples, and executables, is available at http://genome.sph.umich.edu/wiki/GREGOR. cristen@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Social Eavesdropping in Zebrafish: Tuning of Attention to Social Interactions

PubMed Central

Abril-de-Abreu, Rodrigo; Cruz, José; Oliveira, Rui F.

2015-01-01

Group living animals may eavesdrop on signalling interactions between conspecifics in order to collect adaptively relevant information obtained from others, without incurring in the costs of first-hand information acquisition. This ability (aka social eavesdropping) is expected to impact Darwinian fitness, and hence predicts the evolution of cognitive processes that enable social animals to use public information available in the environment. These adaptive specializations in cognition may have evolved both at the level of learning and memory mechanisms, and at the level of input mechanisms, such as attention, which select the information that is available for learning. Here we used zebrafish to test if attention in a social species is tuned to the exchange of information between conspecifics. Our results show that zebrafish are more attentive towards interacting (i.e. fighting) than towards non-interacting pairs of conspecifics, with the exposure to fighting not increasing activity or stress levels. Moreover, using video playbacks to manipulate form features of the fighting fish, we show that during the assessment phase of the fight, bystanders’ attention is more driven by form features of the interacting opponents; whereas during the post-resolution phase, it is driven by biological movement features of the dominant fish chasing the subordinate fish. PMID:26242246

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

PubMed

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.

PomBase: a comprehensive online resource for fission yeast

PubMed Central

Wood, Valerie; Harris, Midori A.; McDowall, Mark D.; Rutherford, Kim; Vaughan, Brendan W.; Staines, Daniel M.; Aslett, Martin; Lock, Antonia; Bähler, Jürg; Kersey, Paul J.; Oliver, Stephen G.

2012-01-01

PomBase (www.pombase.org) is a new model organism database established to provide access to comprehensive, accurate, and up-to-date molecular data and biological information for the fission yeast Schizosaccharomyces pombe to effectively support both exploratory and hypothesis-driven research. PomBase encompasses annotation of genomic sequence and features, comprehensive manual literature curation and genome-wide data sets, and supports sophisticated user-defined queries. The implementation of PomBase integrates a Chado relational database that houses manually curated data with Ensembl software that supports sequence-based annotation and web access. PomBase will provide user-friendly tools to promote curation by experts within the fission yeast community. This will make a key contribution to shaping its content and ensuring its comprehensiveness and long-term relevance. PMID:22039153

Electrospun nanofibers for neural tissue engineering

NASA Astrophysics Data System (ADS)

Xie, Jingwei; MacEwan, Matthew R.; Schwartz, Andrea G.; Xia, Younan

2010-01-01

Biodegradable nanofibers produced by electrospinning represent a new class of promising scaffolds to support nerve regeneration. We begin with a brief discussion on the electrospinning of nanofibers and methods for controlling the structure, porosity, and alignment of the electrospun nanofibers. The methods include control of the nanoscale morphology and microscale alignment of the nanofibers, as well as the fabrication of macroscale, three-dimensional tubular structures. We then highlight recent studies that utilize electrospun nanofibers to manipulate biological processes relevant to nervous tissue regeneration, including stem cell differentiation, guidance of neurite extension, and peripheral nerve injury treatments. The main objective of this feature article is to provide valuable insights into methods for investigating the mechanisms of neurite growth on novel nanofibrous scaffolds and optimization of the nanofiber scaffolds and conduits for repairing peripheral nerve injuries.

Biological Evidence Management for DNA Analysis in Cases of Sexual Assault

PubMed Central

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

Modeling for Visual Feature Extraction Using Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Kimura, Ichiro; Kuroe, Yasuaki; Kotera, Hiromichi; Murata, Tomoya

This paper develops models for “visual feature extraction” in biological systems by using “spiking neural network (SNN)”. The SNN is promising for developing the models because the information is encoded and processed by spike trains similar to biological neural networks. Two architectures of SNN are proposed for modeling the directionally selective and the motion parallax cell in neuro-sensory systems and they are trained so as to possess actual biological responses of each cell. To validate the developed models, their representation ability is investigated and their visual feature extraction mechanisms are discussed from the neurophysiological viewpoint. It is expected that this study can be the first step to developing a sensor system similar to the biological systems and also a complementary approach to investigating the function of the brain.

Biological network extraction from scientific literature: state of the art and challenges.

PubMed

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.

Psychomotor retardation in depression: Biological underpinnings, measurement, and treatment

PubMed Central

Buyukdura, Jeylan S.; McClintock, Shawn M.; Croarkin, Paul E.

2013-01-01

Psychomotor retardation is a long established component of depression that can have significant clinical and therapeutic implications for treatment. Due to its negative impact on overall function in depressed patients, we review its biological correlates, optimal methods of measurement, and relevance in the context of therapeutic interventions. The aim of the paper is to provide a synthesis of the literature on psychomotor retardation in depression with the goal of enhanced awareness for clinicians and researchers. Increased knowledge and understanding of psychomotor retardation in major depressive disorder may lead to further research and better informed diagnosis in regards to psychomotor retardation. Manifestations of psychomotor retardation include slowed speech, decreased movement, and impaired cognitive function. It is common in patients with melancholic depression and those with psychotic features. Biological correlates may include abnormalities in the basal ganglia and dopaminergic pathways. Neurophysiologic tools such as neuroimaging and transcranial magnetic stimulation may play a role in the study of this symptom in the future. At present, there are three objective scales to evaluate psychomotor retardation severity. Studies examining the impact of psychomotor retardation on clinical outcome have found differential results. However, available evidence suggests that depressed patients with psychomotor retardation may respond well to electroconvulsive therapy (ECT). Current literature regarding antidepressants is inconclusive, though tricyclic antidepressants may be considered for treatment of patients with psychomotor retardation. Future work examining this objective aspect of major depressive disorder (MDD) is essential. This could further elucidate the biological underpinnings of depression and optimize its treatment. PMID:21044654

Simple Biological Systems for Assessing the Activity of Superoxide Dismutase Mimics

PubMed Central

Tovmasyan, Artak; Reboucas, Julio S.

2014-01-01

Abstract Significance: Half a century of research provided unambiguous proof that superoxide and species derived from it—reactive oxygen species (ROS)—play a central role in many diseases and degenerative processes. This stimulated the search for pharmaceutical agents that are capable of preventing oxidative damage, and methods of assessing their therapeutic potential. Recent Advances: The limitations of superoxide dismutase (SOD) as a therapeutic tool directed attention to small molecules, SOD mimics, that are capable of catalytically scavenging superoxide. Several groups of compounds, based on either metal complexes, including metalloporphyrins, metallocorroles, Mn(II) cyclic polyamines, and Mn(III) salen derivatives, or non-metal based compounds, such as fullerenes, nitrones, and nitroxides, have been developed and studied in vitro and in vivo. Very few entered clinical trials. Critical Issues and Future Directions: Development of SOD mimics requires in-depth understanding of their mechanisms of biological action. Elucidation of both molecular features, essential for efficient ROS-scavenging in vivo, and factors limiting the potential side effects requires biologically relevant and, at the same time, relatively simple testing systems. This review discuses the advantages and limitations of genetically engineered SOD-deficient unicellular organisms, Escherichia coli and Saccharomyces cerevisiae as tools for investigating the efficacy and mechanisms of biological actions of SOD mimics. These simple systems allow the scrutiny of the minimal requirements for a functional SOD mimic: the association of a high catalytic activity for superoxide dismutation, low toxicity, and an efficient cellular uptake/biodistribution. Antioxid. Redox Signal. 20, 2416–2436. PMID:23964890

The relevance and implications of signet-ring cell adenocarcinoma of the oesophagus.

PubMed

Bleaney, Christopher William; Barrow, Mickhaiel; Hayes, Stephen; Ang, Yeng

2018-03-01

To review the current understanding of signet-ring type oesophageal adenocarcinoma including evidence for prognosis. We conducted a literature search of nine healthcare literature databases for articles detailing the biology and clinical outcomes of signet-ring cell adenocarcinoma of the oesophagus. The impact of signet-ring cell morphology was analysed and detailed in written text and tabular format. Current understanding of the biology of signet-ring cell adenocarcinoma of the oesophagus was summarised. Signet-ring cell carcinoma was represented in 7.61% of the 18 989 cases of oesophageal carcinoma reviewed in multiple studies. The presence of signet-ring cells conferred a worse prognosis and these tumours responded differently to conventional treatments as compared with typical adenocarcinoma. Little is known about the biological features of signet-ring cell adenocarcinoma of the oesophagus. Work in gastric lesions has identified potential targets for future treatments such as CDH1 and RHOA genes. Categorisation of signet-ring cell carcinomas by the proportion of signet-ring cells within tumours differs among clinicians despite WHO criteria for classification. The current UK guidelines for histopathological reporting of oesophageal tumours do not emphasise the importance of identifying signet-ring cells. The presence of signet-ring cells in oesophageal adenocarcinomas leads to poorer clinical outcomes. Current understanding of signet-ring cell biology in oesophageal cancer is limited. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Prediction of lysine glutarylation sites by maximum relevance minimum redundancy feature selection.

PubMed

Ju, Zhe; He, Jian-Jun

2018-06-01

Lysine glutarylation is new type of protein acylation modification in both prokaryotes and eukaryotes. To better understand the molecular mechanism of glutarylation, it is important to identify glutarylated substrates and their corresponding glutarylation sites accurately. In this study, a novel bioinformatics tool named GlutPred is developed to predict glutarylation sites by using multiple feature extraction and maximum relevance minimum redundancy feature selection. On the one hand, amino acid factors, binary encoding, and the composition of k-spaced amino acid pairs features are incorporated to encode glutarylation sites. And the maximum relevance minimum redundancy method and the incremental feature selection algorithm are adopted to remove the redundant features. On the other hand, a biased support vector machine algorithm is used to handle the imbalanced problem in glutarylation sites training dataset. As illustrated by 10-fold cross-validation, the performance of GlutPred achieves a satisfactory performance with a Sensitivity of 64.80%, a Specificity of 76.60%, an Accuracy of 74.90% and a Matthew's correlation coefficient of 0.3194. Feature analysis shows that some k-spaced amino acid pair features play the most important roles in the prediction of glutarylation sites. The conclusions derived from this study might provide some clues for understanding the molecular mechanisms of glutarylation. Copyright © 2018 Elsevier Inc. All rights reserved.

Learning Systems Biology: Conceptual Considerations toward a Web-Based Learning Platform

ERIC Educational Resources Information Center

Emmert-Streib, Frank; Dehmer, Matthias; Lyardet, Fernando

2013-01-01

Within recent years, there is an increasing need to train students, from biology and beyond, in quantitative methods that are relevant to cope with data-driven biology. Systems Biology is such a field that places a particular focus on the functional aspect of biology and molecular interacting processes. This paper deals with the conceptual design…

A Comparison of Biological and Adoptive Mothers and Fathers: The Relevance of Biological Kinship and Gendered Constructs of Parenthood.

ERIC Educational Resources Information Center

Miall, Charlene E.; March, Karen

2003-01-01

Used qualitative interviews to examine beliefs and values about biological and adoptive parents. Considered how biological kinship, gender, and actual parenting behavior affect the assessments respondents made of the emotional bonding between parents and children. Found that biological and adoptive parents viewed motherhood as instinctive and…

Microbial Development and Metabolic Engineering | Bioenergy | NREL

Science.gov Websites

beaker filled with a green liquid cyanobacteria culture that is bubbling. Synthetic Biology We have utilized the power of synthetic biology to uncover relevant genetic factors to predictably regulate gene operating a gas chromatograph mass spectrometer. Systems Biology Our comprehensive systems biology

PathText: a text mining integrator for biological pathway visualizations

PubMed Central

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

Neural evidence reveals the rapid effects of reward history on selective attention.

PubMed

MacLean, Mary H; Giesbrecht, Barry

2015-05-05

Selective attention is often framed as being primarily driven by two factors: task-relevance and physical salience. However, factors like selection and reward history, which are neither currently task-relevant nor physically salient, can reliably and persistently influence visual selective attention. The current study investigated the nature of the persistent effects of irrelevant, physically non-salient, reward-associated features. These features affected one of the earliest reliable neural indicators of visual selective attention in humans, the P1 event-related potential, measured one week after the reward associations were learned. However, the effects of reward history were moderated by current task demands. The modulation of visually evoked activity supports the hypothesis that reward history influences the innate salience of reward associated features, such that even when no longer relevant, nor physically salient, these features have a rapid, persistent, and robust effect on early visual selective attention. Copyright © 2015 Elsevier B.V. All rights reserved.

Multiple mechanisms in the perception of face gender: Effect of sex-irrelevant features.

PubMed

Komori, Masashi; Kawamura, Satoru; Ishihara, Shigekazu

2011-06-01

Effects of sex-relevant and sex-irrelevant facial features on the evaluation of facial gender were investigated. Participants rated masculinity of 48 male facial photographs and femininity of 48 female facial photographs. Eighty feature points were measured on each of the facial photographs. Using a generalized Procrustes analysis, facial shapes were converted into multidimensional vectors, with the average face as a starting point. Each vector was decomposed into a sex-relevant subvector and a sex-irrelevant subvector which were, respectively, parallel and orthogonal to the main male-female axis. Principal components analysis (PCA) was performed on the sex-irrelevant subvectors. One principal component was negatively correlated with both perceived masculinity and femininity, and another was correlated only with femininity, though both components were orthogonal to the male-female dimension (and thus by definition sex-irrelevant). These results indicate that evaluation of facial gender depends on sex-irrelevant as well as sex-relevant facial features.

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

PubMed

Bravi, Luca; Piccialli, Veronica; Sciandrone, Marco

2017-04-01

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

Information Theory in Biology after 18 Years

ERIC Educational Resources Information Center

Johnson, Horton A.

1970-01-01

Reviews applications of information theory to biology, concluding that they have not proved very useful. Suggests modifications and extensions to increase the biological relevance of the theory, and speculates about applications in quantifying cell proliferation, chemical homeostasis and aging. (EB)

Human Metabolites of Cannabidiol: A Review on Their Formation, Biological Activity, and Relevance in Therapy

PubMed Central

Ujváry, István; Hanuš, Lumír

2016-01-01

Abstract Cannabidiol (CBD), the main nonpsychoactive constituent of Cannabis sativa, has shown a wide range of therapeutically promising pharmacological effects either as a sole drug or in combination with other drugs in adjunctive therapy. However, the targets involved in the therapeutic effects of CBD appear to be elusive. Furthermore, scarce information is available on the biological activity of its human metabolites which, when formed in pharmacologically relevant concentration, might contribute to or even account for the observed therapeutic effects. The present overview summarizes our current knowledge on the pharmacokinetics and metabolic fate of CBD in humans, reviews studies on the biological activity of CBD metabolites either in vitro or in vivo, and discusses relevant drug–drug interactions. To facilitate further research in the area, the reported syntheses of CBD metabolites are also catalogued. PMID:28861484

Human Metabolites of Cannabidiol: A Review on Their Formation, Biological Activity, and Relevance in Therapy.

PubMed

Ujváry, István; Hanuš, Lumír

2016-01-01

Cannabidiol (CBD), the main nonpsychoactive constituent of Cannabis sativa , has shown a wide range of therapeutically promising pharmacological effects either as a sole drug or in combination with other drugs in adjunctive therapy. However, the targets involved in the therapeutic effects of CBD appear to be elusive. Furthermore, scarce information is available on the biological activity of its human metabolites which, when formed in pharmacologically relevant concentration, might contribute to or even account for the observed therapeutic effects. The present overview summarizes our current knowledge on the pharmacokinetics and metabolic fate of CBD in humans, reviews studies on the biological activity of CBD metabolites either in vitro or in vivo , and discusses relevant drug-drug interactions. To facilitate further research in the area, the reported syntheses of CBD metabolites are also catalogued.

Biology of acute lymphoblastic leukemia (ALL): clinical and therapeutic relevance.

PubMed

Graux, Carlos

2011-04-01

Acute lymphoblastic leukemia is a heterogeneous disease comprising several clinico-biological entities. Karyotyping of leukemic cells identifies recurrent chromosome rearrangements. These are usually translocations that activate genes encoding transcription factor regulating B- or T-cell differentiation. Gene expression-array confirms the prognostic relevance of ALL subgroups identified by specific chromosomal rearrangements and isolates new subgroups. Analysis of genomic copy number changes and high throughput sequencing reveal new cryptic deletions. The challenge is now to understand how these cooperative genetic lesions interact in order to have the molecular rationales needed to select new therapeutic targets and to develop and combine inhibitors with high levels of anti-leukemic specificity. The aim of this paper is to provide some data on the biology of acute lymphoblastic leukemia which are relevant in clinical practice. Copyright © 2011 Elsevier Ltd. All rights reserved.

Prediction of heterotrimeric protein complexes by two-phase learning using neighboring kernels

PubMed Central

2014-01-01

Background Protein complexes play important roles in biological systems such as gene regulatory networks and metabolic pathways. Most methods for predicting protein complexes try to find protein complexes with size more than three. It, however, is known that protein complexes with smaller sizes occupy a large part of whole complexes for several species. In our previous work, we developed a method with several feature space mappings and the domain composition kernel for prediction of heterodimeric protein complexes, which outperforms existing methods. Results We propose methods for prediction of heterotrimeric protein complexes by extending techniques in the previous work on the basis of the idea that most heterotrimeric protein complexes are not likely to share the same protein with each other. We make use of the discriminant function in support vector machines (SVMs), and design novel feature space mappings for the second phase. As the second classifier, we examine SVMs and relevance vector machines (RVMs). We perform 10-fold cross-validation computational experiments. The results suggest that our proposed two-phase methods and SVM with the extended features outperform the existing method NWE, which was reported to outperform other existing methods such as MCL, MCODE, DPClus, CMC, COACH, RRW, and PPSampler for prediction of heterotrimeric protein complexes. Conclusions We propose two-phase prediction methods with the extended features, the domain composition kernel, SVMs and RVMs. The two-phase method with the extended features and the domain composition kernel using SVM as the second classifier is particularly useful for prediction of heterotrimeric protein complexes. PMID:24564744

Vision and change in introductory physics for the life sciences

NASA Astrophysics Data System (ADS)

Mochrie, S. G. J.

2016-07-01

Since 2010, our physics department has offered a re-imagined calculus-based introductory physics sequence for the life sciences. These courses include a selection of biologically and medically relevant topics that we believe are more meaningful to undergraduate premedical and biological science students than those found in a traditional course. In this paper, we highlight new aspects of the first-semester course, and present a comparison of student evaluations of this course versus a more traditional one. We also present the effect on student perception of the relevance of physics to biology and medicine after having taken this course.

An inventory and evaluation of biological investigations that relate to stream-water quality in the upper Illinois River basin of Illinois, Indiana, and Wisconsin

USGS Publications Warehouse

Steffeck, D.W.; Striegl, Robert G.

1989-01-01

Results of studies of the aquatic biology of the upper Illinois River basin provide a historical data source from which inferences can be made about changes in the quality of water in the main stem river and its tributaries. The results of biological investigations that have been conducted throughout the basin since 1900 are summarized and their relevance to stream-water-quality assessment is described, particularly their relevance to the upper Illinois River basin pilot project for the National Water Quality Assessment program. Four general categories of biological investigations were identified: Populations and community structure, chemical concentrations in tissue, organism health, and toxicity measurements. Biological investigations were identified by their location in the basin and by their relevance to each general investigation category. The most abundant literature was in the populations and community structure category. Tissue data were limited to polychlorinated biphenyls, organochlorine pesticides, dioxin, and several metals. The most cited measure of organism health was a condition factor for fish that associates body length with weight or body depth. Toxicity measurements included bioassays and the Ames Tests. The bioassays included several testing methods and test organism. (USGS)

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

Differential transcriptomic responses of Biomphalaria glabrata (Gastropoda, Mollusca) to bacteria and metazoan parasites, Schistosoma mansoni and Echinostoma paraensei (Digenea, Platyhelminthes)

PubMed Central

Adema, Coen M; Hanington, Patrick C.; Lun, Cheng-Man; Rosenberg, George H.; Aragon, Anthony D; Stout, Barbara A; Richard, Mara L. Lennard; Gross, Paul S.; Loker, Eric S

2009-01-01

A 70-mer oligonucleotide-based microarray (1152 features) that emphasizes stress and immune responses factors was constructed to study transcriptomic responses of the snail Biomphalaria glabrata to different immune challenges. In addition to sequences with relevant putative ID and Gene Ontology (GO) annotation, the array features non-immune factors and unknown B. glabrata ESTs for functional gene discovery. The transcription profiles of B. glabrata (3 biological replicates, each a pool of 5 snails) were recorded at 12 hours post wounding, exposure to Gram negative or Gram positive bacteria (Escherichia coli and Micrococcus luteus, respectively), or infection with compatible trematode parasites (S. mansoni or E. paraensei, 20 miracidia/snail), relative to controls, using universal reference RNA. The data were subjected to Significance Analysis for Microarrays (SAM), with a false positive rate (FPR) ≤10%. Wounding yielded a modest differential expression profile (27 up/21 down) with affected features mostly dissimilar from other treatments. Partially overlapping, yet distinct expression profiles were recorded from snails challenged with E. coli (83 up/20 down) or M. luteus (120 up/42 down), mostly showing up-regulation of defense and stress-related features. Significantly altered expression of selected immune features indicates that B. glabrata detects and responds differently to compatible trematodes. Echinostoma paraensei infection was associated mostly with down regulation of many (immune-) transcripts (42 up/68 down), whereas S. mansoni exposure yielded a preponderance of up-regulated features (140 up/23 down), with only few known immune genes affected. These observations may reflect the divergent strategies developed by trematodes during their evolution as specialized pathogens of snails to negate host defense responses. Clearly, the immune defenses of B. glabrata distinguish and respond differently to various immune challenges. PMID:19962194

Measurement of food-related approach-avoidance biases: Larger biases when food stimuli are task relevant.

PubMed

Lender, Anja; Meule, Adrian; Rinck, Mike; Brockmeyer, Timo; Blechert, Jens

2018-06-01

Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them "near" with a joystick that controls a corresponding image zoom. One version of the task couples movement direction with image content-independent features, for example, pulling blue-framed images and pushing green-framed images regardless of content ('irrelevant feature version'). However, participants might selectively attend to this feature and ignore image content and, thus, such a task setup might underestimate existing biases. The present study tested this attention account by comparing two irrelevant feature versions of the task with either a more peripheral (image frame color: green vs. blue) or central (small circle vs. cross overlaid over the image content) image feature as response instruction to a 'relevant feature version', in which participants responded to the image content, thus making it impossible to ignore that content. Images of chocolate-containing foods and of objects were used, and several trait and state measures were acquired to validate the obtained biases. Results revealed a robust approach bias towards food only in the relevant feature condition. Interestingly, a positive correlation with state chocolate craving during the task was found when all three conditions were combined, indicative of criterion validity of all three versions. However, no correlations were found with trait chocolate craving. Results provide a strong case for the relevant feature version of the AAT for bias measurement. They also point to several methodological avenues for future research around selective attention in the irrelevant versions and task validity regarding trait vs. state variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

Planning to avoid trouble in the operating room: experts' formulation of the preoperative plan.

PubMed

Zilbert, Nathan R; St-Martin, Laurent; Regehr, Glenn; Gallinger, Steven; Moulton, Carol-Anne

2015-01-01

The purpose of this study was to capture the preoperative plans of expert hepato-pancreato-biliary (HPB) surgeons with the goal of finding consistent aspects of the preoperative planning process. HPB surgeons were asked to think aloud when reviewing 4 preoperative computed tomography scans of patients with distal pancreatic tumors. The imaging features they identified and the planned actions they proposed were tabulated. Surgeons viewed the tabulated list of imaging features for each case and rated the relevance of each feature for their subsequent preoperative plan. Average rater intraclass correlation coefficients were calculated for each type of data collected (imaging features detected, planned actions reported, and relevance of each feature) to establish whether the surgeons were consistent with one another in their responses. Average rater intraclass correlation coefficient values greater than 0.7 were considered indicative of consistency. Division of General Surgery, University of Toronto. HPB surgeons affiliated with the University of Toronto. A total of 11 HPB surgeons thought aloud when reviewing 4 computed tomography scans. Surgeons were consistent in the imaging features they detected but inconsistent in the planned actions they reported. Of the HPB surgeons, 8 completed the assessment of feature relevance. For 3 of the 4 cases, the surgeons were consistent in rating the relevance of specific imaging features on their preoperative plans. These results suggest that HPB surgeons are consistent in some aspects of the preoperative planning process but not others. The findings further our understanding of the preoperative planning process and will guide future research on the best ways to incorporate the teaching and evaluation of preoperative planning into surgical training. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

biologically relevant effects of dipentyl phthalate

EPA Pesticide Factsheets

metadata sheet, data sheet for each table and figure in the published manuscriptThis dataset is associated with the following publication:Gray , E., J. Furr , K. Tatum-Gibbs, C. Lambright , H. Sampson, B. Hannas, V. Wilson , A. Hotchkiss , and P. Foster. Establishing the Biological Relevance of Dipentyl Phthalate Reductions in Fetal Rat Testosterone Production and Plasma and Testis Testosterone Levels. TOXICOLOGICAL SCIENCES. Society of Toxicology, 149(1): 178-91, (2016).

An analysis of the positional distribution of DNA motifs in promoter regions and its biological relevance.

PubMed

Casimiro, Ana C; Vinga, Susana; Freitas, Ana T; Oliveira, Arlindo L

2008-02-07

Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior classification of the output still suffers from some limitations, which makes it difficult to assess the biological significance of the motifs found. Previous work has highlighted the existence of positional bias of motifs in the DNA sequences, which might indicate not only that the pattern is important, but also provide hints of the positions where these patterns occur preferentially. We propose to integrate position uniformity tests and over-representation tests to improve the accuracy of the classification of motifs. Using artificial data, we have compared three different statistical tests (Chi-Square, Kolmogorov-Smirnov and a Chi-Square bootstrap) to assess whether a given motif occurs uniformly in the promoter region of a gene. Using the test that performed better in this dataset, we proceeded to study the positional distribution of several well known cis-regulatory elements, in the promoter sequences of different organisms (S. cerevisiae, H. sapiens, D. melanogaster, E. coli and several Dicotyledons plants). The results show that position conservation is relevant for the transcriptional machinery. We conclude that many biologically relevant motifs appear heterogeneously distributed in the promoter region of genes, and therefore, that non-uniformity is a good indicator of biological relevance and can be used to complement over-representation tests commonly used. In this article we present the results obtained for the S. cerevisiae data sets.

Male Inmate Profiles and Their Biological Correlates

PubMed Central

Horn, Mathilde; Potvin, Stephane; Allaire, Jean-François; Côté, Gilles; Gobbi, Gabriella; Benkirane, Karim; Vachon, Jeanne; Dumais, Alexandre

2014-01-01

Objective: Borderline and antisocial personality disorders (PDs) share common clinical features (impulsivity, aggressiveness, substance use disorders [SUDs], and suicidal behaviours) that are greatly overrepresented in prison populations. These disorders have been associated biologically with testosterone and cortisol levels. However, the associations are ambiguous and the subject of controversy, perhaps because these heterogeneous disorders have been addressed as unitary constructs. A consideration of profiles of people, rather than of exclusive diagnoses, might yield clearer relationships. Methods: In our study, multiple correspondence analysis and cluster analysis were employed to identify subgroups among 545 newly convicted inmates. The groups were then compared in terms of clinical features and biological markers, including levels of cortisol, testosterone, estradiol, progesterone, and sulfoconjugated dehydroepiandrosterone (DHEA-S). Results: Four clusters with differing psychiatric, criminal, and biological profiles emerged. Clinically, one group had intermediate scores for each of the tested clinical features. Another group comprised people with little comorbidity. Two others displayed severe impulsivity, PD, and SUD. Biologically, cortisol levels were lowest in the last 2 groups and highest in the group with less comorbidity. In keeping with previous findings reported in the literature, testosterone was higher in a younger population with severe psychiatric symptoms. However, some apparently comparable behavioural outcomes were found to be related to distinct biological profiles. No differences were observed for estradiol, progesterone, or DHEA-S levels. Conclusions: The results not only confirm the importance of biological markers in the study of personality features but also demonstrate the need to consider the role of comorbidities and steroid coregulation. PMID:25161069

Biology Curriculum Reform in Venezuela.

ERIC Educational Resources Information Center

Rondon, Leonor Mariasole

2001-01-01

Describes science in the Venezuelan school system which reflects on the process of development followed to design and validate the Biology Study Programs (BSP) with the emphasis on the relevance of curricular changes proposed in biological science for secondary education. (Contains 19 references.) (ASK)

IQ Predicts Biological Motion Perception in Autism Spectrum Disorders

ERIC Educational Resources Information Center

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…

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

ERIC Educational Resources Information Center

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…

OCT-based approach to local relaxations discrimination from translational relaxation motions

NASA Astrophysics Data System (ADS)

Matveev, Lev A.; Matveyev, Alexandr L.; Gubarkova, Ekaterina V.; Gelikonov, Grigory V.; Sirotkina, Marina A.; Kiseleva, Elena B.; Gelikonov, Valentin M.; Gladkova, Natalia D.; Vitkin, Alex; Zaitsev, Vladimir Y.

2016-04-01

Multimodal optical coherence tomography (OCT) is an emerging tool for tissue state characterization. Optical coherence elastography (OCE) is an approach to mapping mechanical properties of tissue based on OCT. One of challenging problems in OCE is elimination of the influence of residual local tissue relaxation that complicates obtaining information on elastic properties of the tissue. Alternatively, parameters of local relaxation itself can be used as an additional informative characteristic for distinguishing the tissue in normal and pathological states over the OCT image area. Here we briefly present an OCT-based approach to evaluation of local relaxation processes in the tissue bulk after sudden unloading of its initial pre-compression. For extracting the local relaxation rate we evaluate temporal dependence of local strains that are mapped using our recently developed hybrid phase resolved/displacement-tracking (HPRDT) approach. This approach allows one to subtract the contribution of global displacements of scatterers in OCT scans and separate the temporal evolution of local strains. Using a sample excised from of a coronary arteria, we demonstrate that the observed relaxation of local strains can be reasonably fitted by an exponential law, which opens the possibility to characterize the tissue by a single relaxation time. The estimated local relaxation times are assumed to be related to local biologically-relevant processes inside the tissue, such as diffusion, leaking/draining of the fluids, local folding/unfolding of the fibers, etc. In general, studies of evolution of such features can provide new metrics for biologically-relevant changes in tissue, e.g., in the problems of treatment monitoring.

CHEMICAL PRIORITIZATION FOR DEVELOPMENTAL ...

EPA Pesticide Factsheets

Defining a predictive model of developmental toxicity from in vitro and high-throughput screening (HTS) assays can be limited by the availability of developmental defects data. ToxRefDB (www.epa.gov/ncct/todrefdb) was built from animal studies on data-rich environmental chemicals, and has been used as an anchor for predictive modeling of ToxCast™ data. Scaling to thousands of untested chemicals requires another approach. ToxPlorer™ was developed as a tool to query and extract specific facts about defined biological entities from the open scientific literature and to coherently synthesize relevant knowledge about relationships, pathways and processes in toxicity. Here, we investigated the specific application of ToxPlorer to weighting HTS assay targets for relevance to developmental defects as defined in the literature. First, we systemically analyzed 88,193 Pubmed abstracts selected by bulk query using harmonized terminology for 862 developmental endpoints (www.devtox.net) and 364,334 dictionary term entities in our VT-KB (virtual tissues knowledgebase). We specifically focused on entities corresponding to genes/proteins mapped across of >500 ToxCast HTS assays. The 88,193 devtox abstracts mentioned 244 gene/protein entities in an aggregated total of ~8,000 occurrences. Each of the 244 assays was scored and weighted by the number of devtox articles and relevance to developmental processes. This score was used as a feature for chemical prioritization by Toxic

Habitat classification modeling with incomplete data: Pushing the habitat envelope

USGS Publications Warehouse

Zarnetske, P.L.; Edwards, T.C.; Moisen, Gretchen G.

2007-01-01

Habitat classification models (HCMs) are invaluable tools for species conservation, land-use planning, reserve design, and metapopulation assessments, particularly at broad spatial scales. However, species occurrence data are often lacking and typically limited to presence points at broad scales. This lack of absence data precludes the use of many statistical techniques for HCMs. One option is to generate pseudo-absence points so that the many available statistical modeling tools can be used. Traditional techniques generate pseudoabsence points at random across broadly defined species ranges, often failing to include biological knowledge concerning the species-habitat relationship. We incorporated biological knowledge of the species-habitat relationship into pseudo-absence points by creating habitat envelopes that constrain the region from which points were randomly selected. We define a habitat envelope as an ecological representation of a species, or species feature's (e.g., nest) observed distribution (i.e., realized niche) based on a single attribute, or the spatial intersection of multiple attributes. We created HCMs for Northern Goshawk (Accipiter gentilis atricapillus) nest habitat during the breeding season across Utah forests with extant nest presence points and ecologically based pseudo-absence points using logistic regression. Predictor variables were derived from 30-m USDA Landfire and 250-m Forest Inventory and Analysis (FIA) map products. These habitat-envelope-based models were then compared to null envelope models which use traditional practices for generating pseudo-absences. Models were assessed for fit and predictive capability using metrics such as kappa, thresholdindependent receiver operating characteristic (ROC) plots, adjusted deviance (Dadj2), and cross-validation, and were also assessed for ecological relevance. For all cases, habitat envelope-based models outperformed null envelope models and were more ecologically relevant, suggesting that incorporating biological knowledge into pseudo-absence point generation is a powerful tool for species habitat assessments. Furthermore, given some a priori knowledge of the species-habitat relationship, ecologically based pseudo-absence points can be applied to any species, ecosystem, data resolution, and spatial extent. ?? 2007 by the Ecological Society of America.

Outcome after reduced chemotherapy for intermediate-risk neuroblastoma.

PubMed

Baker, David L; Schmidt, Mary L; Cohn, Susan L; Maris, John M; London, Wendy B; Buxton, Allen; Stram, Daniel; Castleberry, Robert P; Shimada, Hiroyuki; Sandler, Anthony; Shamberger, Robert C; Look, A Thomas; Reynolds, C Patrick; Seeger, Robert C; Matthay, Katherine K

2010-09-30

The survival rate among patients with intermediate-risk neuroblastoma who receive dose-intensive chemotherapy is excellent, but the survival rate among patients who receive reduced doses of chemotherapy for shorter periods of time is not known. We conducted a prospective, phase 3, nonrandomized trial to determine whether a 3-year estimated overall survival of more than 90% could be maintained with reductions in the duration of therapy and drug doses, using a tumor biology-based therapy assignment. Eligible patients had newly diagnosed, intermediate-risk neuroblastoma without MYCN amplification; these patients included infants (<365 days of age) who had stage 3 or 4 disease, children (≥365 days of age) who had stage 3 tumors with favorable histopathological features, and infants who had stage 4S disease with a diploid DNA index or unfavorable histopathological features. Patients who had disease with favorable histopathological features and hyperdiploidy were assigned to four cycles of chemotherapy, and those with an incomplete response or either unfavorable feature were assigned to eight cycles. Between 1997 and 2005, a total of 479 eligible patients were enrolled in this trial (270 patients with stage 3 disease, 178 with stage 4 disease, and 31 with stage 4S disease). A total of 323 patients had tumors with favorable biologic features, and 141 had tumors with unfavorable biologic features. Ploidy, but not histopathological features, was significantly predictive of the outcome. Severe adverse events without disease progression occurred in 10 patients (2.1%), including secondary leukemia (in 3 patients), death from infection (in 3 patients), and death at surgery (in 4 patients). The 3-year estimate (±SE) of overall survival for the entire group was 96±1%, with an overall survival rate of 98±1% among patients who had tumors with favorable biologic features and 93±2% among patients who had tumors with unfavorable biologic features. A very high rate of survival among patients with intermediate-risk neuroblastoma was achieved with a biologically based treatment assignment involving a substantially reduced duration of chemotherapy and reduced doses of chemotherapeutic agents as compared with the regimens used in earlier trials. These data provide support for further reduction in chemotherapy with more refined risk stratification. (Funded by the National Cancer Institute; ClinicalTrials.gov number, NCT00003093.)

Severe impingement of lumbar disc replacements increases the functional biological activity of polyethylene wear debris.

PubMed

Baxter, Ryan M; Macdonald, Daniel W; Kurtz, Steven M; Steinbeck, Marla J

2013-06-05

Wear, oxidation, and particularly rim impingement damage of ultra-high molecular weight polyethylene total disc replacement components have been observed following surgical revision. However, neither in vitro testing nor retrieval-based evidence has shown the effect(s) of impingement on the characteristics of polyethylene wear debris. Thus, we sought to determine (1) differences in polyethylene particle size, shape, number, or biological activity that correspond to mild or severe rim impingement and (2) in an analysis of all total disc replacements, regardless of impingement classification, whether there are correlations between the extent of regional damage and the characteristics of polyethylene wear debris. The extent of dome and rim damage was characterized for eleven retrieved polyethylene cores obtained at revision surgery after an average duration of implantation of 9.7 years (range, 4.6 to 16.1 years). Polyethylene wear debris was isolated from periprosthetic tissues with use of nitric acid and was imaged with use of environmental scanning electron microscopy. Subsequently, particle size, shape, number, biological activity, and chronic inflammation scores were determined. Grouping of particles by size ranges that represented high biological relevance (<0.1 to 1-μm particles), intermediate biological relevance (1 to 10-μm particles), and low biological relevance (>10-μm particles) revealed an increased volume fraction of particles in the <0.1 to 1-μm and 1 to 10-μm size ranges in the mild-impingement cohort as compared with the severe-impingement cohort. The increased volume fractions resulted in a higher specific biological activity per unit particle volume in the mild-impingement cohort than in the severe-impingement cohort. However, functional biological activity, which is normalized by particle volume (mm3/g of tissue), was significantly higher in the severe-impingement cohort. This increase was due to a larger volume of particles in all three size ranges. In both cohorts, the functional biological activity correlated with the chronic inflammatory response, and the extent of rim penetration positively correlated with increasing particle size, number, and functional biological activity. The results of this study suggest that severe rim impingement increases the production of biologically relevant particles from motion-preserving lumbar total disc replacement components. Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Severe Impingement of Lumbar Disc Replacements Increases the Functional Biological Activity of Polyethylene Wear Debris

PubMed Central

Baxter, Ryan M.; MacDonald, Daniel W.; Kurtz, Steven M.; Steinbeck, Marla J.

2013-01-01

Background: Wear, oxidation, and particularly rim impingement damage of ultra-high molecular weight polyethylene total disc replacement components have been observed following surgical revision. However, neither in vitro testing nor retrieval-based evidence has shown the effect(s) of impingement on the characteristics of polyethylene wear debris. Thus, we sought to determine (1) differences in polyethylene particle size, shape, number, or biological activity that correspond to mild or severe rim impingement and (2) in an analysis of all total disc replacements, regardless of impingement classification, whether there are correlations between the extent of regional damage and the characteristics of polyethylene wear debris. Methods: The extent of dome and rim damage was characterized for eleven retrieved polyethylene cores obtained at revision surgery after an average duration of implantation of 9.7 years (range, 4.6 to 16.1 years). Polyethylene wear debris was isolated from periprosthetic tissues with use of nitric acid and was imaged with use of environmental scanning electron microscopy. Subsequently, particle size, shape, number, biological activity, and chronic inflammation scores were determined. Results: Grouping of particles by size ranges that represented high biological relevance (<0.1 to 1-μm particles), intermediate biological relevance (1 to 10-μm particles), and low biological relevance (>10-μm particles) revealed an increased volume fraction of particles in the <0.1 to 1-μm and 1 to 10-μm size ranges in the mild-impingement cohort as compared with the severe-impingement cohort. The increased volume fractions resulted in a higher specific biological activity per unit particle volume in the mild-impingement cohort than in the severe-impingement cohort. However, functional biological activity, which is normalized by particle volume (mm3/g of tissue), was significantly higher in the severe-impingement cohort. This increase was due to a larger volume of particles in all three size ranges. In both cohorts, the functional biological activity correlated with the chronic inflammatory response, and the extent of rim penetration positively correlated with increasing particle size, number, and functional biological activity. Conclusions: The results of this study suggest that severe rim impingement increases the production of biologically relevant particles from motion-preserving lumbar total disc replacement components. Level of Evidence: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence. PMID:23780545

Remembering Complex Objects in Visual Working Memory: Do Capacity Limits Restrict Objects or Features?

PubMed Central

Hardman, Kyle; Cowan, Nelson

2014-01-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli which possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results, but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PMID:25089739

Feature-based attentional modulations in the absence of direct visual stimulation.

PubMed

Serences, John T; Boynton, Geoffrey M

2007-07-19

When faced with a crowded visual scene, observers must selectively attend to behaviorally relevant objects to avoid sensory overload. Often this selection process is guided by prior knowledge of a target-defining feature (e.g., the color red when looking for an apple), which enhances the firing rate of visual neurons that are selective for the attended feature. Here, we used functional magnetic resonance imaging and a pattern classification algorithm to predict the attentional state of human observers as they monitored a visual feature (one of two directions of motion). We find that feature-specific attention effects spread across the visual field-even to regions of the scene that do not contain a stimulus. This spread of feature-based attention to empty regions of space may facilitate the perception of behaviorally relevant stimuli by increasing sensitivity to attended features at all locations in the visual field.

BioCarian: search engine for exploratory searches in heterogeneous biological databases.

PubMed

Zaki, Nazar; Tennakoon, Chandana

2017-10-02

There are a large number of biological databases publicly available for scientists in the web. Also, there are many private databases generated in the course of research projects. These databases are in a wide variety of formats. Web standards have evolved in the recent times and semantic web technologies are now available to interconnect diverse and heterogeneous sources of data. Therefore, integration and querying of biological databases can be facilitated by techniques used in semantic web. Heterogeneous databases can be converted into Resource Description Format (RDF) and queried using SPARQL language. Searching for exact queries in these databases is trivial. However, exploratory searches need customized solutions, especially when multiple databases are involved. This process is cumbersome and time consuming for those without a sufficient background in computer science. In this context, a search engine facilitating exploratory searches of databases would be of great help to the scientific community. We present BioCarian, an efficient and user-friendly search engine for performing exploratory searches on biological databases. The search engine is an interface for SPARQL queries over RDF databases. We note that many of the databases can be converted to tabular form. We first convert the tabular databases to RDF. The search engine provides a graphical interface based on facets to explore the converted databases. The facet interface is more advanced than conventional facets. It allows complex queries to be constructed, and have additional features like ranking of facet values based on several criteria, visually indicating the relevance of a facet value and presenting the most important facet values when a large number of choices are available. For the advanced users, SPARQL queries can be run directly on the databases. Using this feature, users will be able to incorporate federated searches of SPARQL endpoints. We used the search engine to do an exploratory search on previously published viral integration data and were able to deduce the main conclusions of the original publication. BioCarian is accessible via http://www.biocarian.com . We have developed a search engine to explore RDF databases that can be used by both novice and advanced users.

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

PubMed

Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed ADAGE signature analysis to perform gene set analysis using data-defined functional gene signatures. This approach addresses an important gap for biologists studying non-traditional model organisms and those without extensive curated resources available. We built both an R package and web server to provide ADAGE signature analysis to the community.

Electroencephalogram Signal Classification for Automated Epileptic Seizure Detection Using Genetic Algorithm

PubMed Central

Nanthini, B. Suguna; Santhi, B.

2017-01-01

Background: Epilepsy causes when the repeated seizure occurs in the brain. Electroencephalogram (EEG) test provides valuable information about the brain functions and can be useful to detect brain disorder, especially for epilepsy. In this study, application for an automated seizure detection model has been introduced successfully. Materials and Methods: The EEG signals are decomposed into sub-bands by discrete wavelet transform using db2 (daubechies) wavelet. The eight statistical features, the four gray level co-occurrence matrix and Renyi entropy estimation with four different degrees of order, are extracted from the raw EEG and its sub-bands. Genetic algorithm (GA) is used to select eight relevant features from the 16 dimension features. The model has been trained and tested using support vector machine (SVM) classifier successfully for EEG signals. The performance of the SVM classifier is evaluated for two different databases. Results: The study has been experimented through two different analyses and achieved satisfactory performance for automated seizure detection using relevant features as the input to the SVM classifier. Conclusion: Relevant features using GA give better accuracy performance for seizure detection. PMID:28781480

Design, Development, and Psychometric Analysis of a General, Organic, and Biological Chemistry Topic Inventory Based on the Identified Main Chemistry Topics Relevant to Nursing Clinical Practice

ERIC Educational Resources Information Center

Brown, Corina E.

2013-01-01

This two-stage study focused on the undergraduate nursing course that covers topics in general, organic, and biological (GOB) chemistry. In the first stage, the central objective was to identify the main concepts of GOB chemistry relevant to the clinical practice of nursing. The collection of data was based on open-ended interviews of both nursing…

Lateral Hypothalamus GABAergic Neurons Modulate Consummatory Behaviors Regardless of the Caloric Content or Biological Relevance of the Consumed Stimuli.

PubMed

Navarro, Montserrat; Olney, Jeffrey J; Burnham, Nathan W; Mazzone, Christopher M; Lowery-Gionta, Emily G; Pleil, Kristen E; Kash, Thomas L; Thiele, Todd E

2016-05-01

It was recently reported that activation of a subset of lateral hypothalamus (LH) GABAergic neurons induced both appetitive (food-seeking) and consummatory (eating) behaviors in vGat-ires-cre mice, while inhibition or deletion of GABAergic neurons blunted these behaviors. As food and caloric-dense liquid solutions were used, the data reported suggest that these LH GABAergic neurons may modulate behaviors that function to maintain homeostatic caloric balance. Here we report that chemogenetic activation of this GABAergic population in vGat-ires-cre mice increased consummatory behavior directed at any available stimulus, including those entailing calories (food, sucrose, and ethanol), those that do not (saccharin and water), and those lacking biological relevance (wood). Chemogenetic inhibition of these neurons attenuated consummatory behaviors. These data indicate that LH GABAergic neurons modulate consummatory behaviors regardless of the caloric content or biological relevance of the consumed stimuli.

Relevance in the science classroom: A multidimensional analysis

NASA Astrophysics Data System (ADS)

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 groups. The findings combine to support a multidimensional perspective of relevance in the 9th grade biology classroom; offering researchers a useful model for future investigation and educators with insights into the students' classroom experience.

The cost of selective attention in category learning: Developmental differences between adults and infants

PubMed Central

Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.

2013-01-01

Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914

Recent developments on ultrasound-assisted one-pot multicomponent synthesis of biologically relevant heterocycles.

PubMed

Banerjee, Bubun

2017-03-01

Heterocycles are the backbone of organic compounds. Specially, N- &O-containing heterocycles represent privileged structural subunits well distributed in naturally occurring compounds with immense biological activities. Multicomponent reactions (MCRs) are becoming valuable tool for synthesizing structurally diverse molecular entities. On the other hand, the last decade has seen a tremendous outburst in modifying chemical processes to make them sustainable for the betterment of our environment. The application of ultrasound in organic synthesis is fulfilling some of the goals of 'green and sustainable chemistry' as it has some advantages over the traditional thermal methods in terms of reaction rates, yields, purity of the products, product selectivity, etc. Therefore the synthesis of biologically relevant heterocycles using one-pot multi-component technique coupled with the application of ultrasound is one of the thrusting areas in the 21st Century among the organic chemists. The present review deals with the "up to date" developments on ultrasound assisted one-pot multi-component synthesis of biologically relevant heterocycles reported so far. Copyright © 2016 Elsevier B.V. All rights reserved.

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

GAMOLA2, a Comprehensive Software Package for the Annotation and Curation of Draft and Complete Microbial Genomes

PubMed Central

Altermann, Eric; Lu, Jingli; McCulloch, Alan

2017-01-01

Expert curated annotation remains one of the critical steps in achieving a reliable biological relevant annotation. Here we announce the release of GAMOLA2, a user friendly and comprehensive software package to process, annotate and curate draft and complete bacterial, archaeal, and viral genomes. GAMOLA2 represents a wrapping tool to combine gene model determination, functional Blast, COG, Pfam, and TIGRfam analyses with structural predictions including detection of tRNAs, rRNA genes, non-coding RNAs, signal protein cleavage sites, transmembrane helices, CRISPR repeats and vector sequence contaminations. GAMOLA2 has already been validated in a wide range of bacterial and archaeal genomes, and its modular concept allows easy addition of further functionality in future releases. A modified and adapted version of the Artemis Genome Viewer (Sanger Institute) has been developed to leverage the additional features and underlying information provided by the GAMOLA2 analysis, and is part of the software distribution. In addition to genome annotations, GAMOLA2 features, among others, supplemental modules that assist in the creation of custom Blast databases, annotation transfers between genome versions, and the preparation of Genbank files for submission via the NCBI Sequin tool. GAMOLA2 is intended to be run under a Linux environment, whereas the subsequent visualization and manual curation in Artemis is mobile and platform independent. The development of GAMOLA2 is ongoing and community driven. New functionality can easily be added upon user requests, ensuring that GAMOLA2 provides information relevant to microbiologists. The software is available free of charge for academic use. PMID:28386247

GAMOLA2, a Comprehensive Software Package for the Annotation and Curation of Draft and Complete Microbial Genomes.

PubMed

Altermann, Eric; Lu, Jingli; McCulloch, Alan

2017-01-01

Expert curated annotation remains one of the critical steps in achieving a reliable biological relevant annotation. Here we announce the release of GAMOLA2, a user friendly and comprehensive software package to process, annotate and curate draft and complete bacterial, archaeal, and viral genomes. GAMOLA2 represents a wrapping tool to combine gene model determination, functional Blast, COG, Pfam, and TIGRfam analyses with structural predictions including detection of tRNAs, rRNA genes, non-coding RNAs, signal protein cleavage sites, transmembrane helices, CRISPR repeats and vector sequence contaminations. GAMOLA2 has already been validated in a wide range of bacterial and archaeal genomes, and its modular concept allows easy addition of further functionality in future releases. A modified and adapted version of the Artemis Genome Viewer (Sanger Institute) has been developed to leverage the additional features and underlying information provided by the GAMOLA2 analysis, and is part of the software distribution. In addition to genome annotations, GAMOLA2 features, among others, supplemental modules that assist in the creation of custom Blast databases, annotation transfers between genome versions, and the preparation of Genbank files for submission via the NCBI Sequin tool. GAMOLA2 is intended to be run under a Linux environment, whereas the subsequent visualization and manual curation in Artemis is mobile and platform independent. The development of GAMOLA2 is ongoing and community driven. New functionality can easily be added upon user requests, ensuring that GAMOLA2 provides information relevant to microbiologists. The software is available free of charge for academic use.

Pre-eclampsia and offspring cardiovascular health: mechanistic insights from experimental studies

PubMed Central

Davis, Esther F.; Newton, Laura; Lewandowski, Adam J.; Lazdam, Merzaka; Kelly, Brenda A.; Kyriakou, Theodosios; Leeson, Paul

2012-01-01

Pre-eclampsia is increasingly recognized as more than an isolated disease of pregnancy. Women who have had a pregnancy complicated by pre-eclampsia have a 4-fold increased risk of later cardiovascular disease. Intriguingly, the offspring of affected pregnancies also have an increased risk of higher blood pressure and almost double the risk of stroke in later life. Experimental approaches to identify the key features of pre-eclampsia responsible for this programming of offspring cardiovascular health, or the key biological pathways modified in the offspring, have the potential to highlight novel targets for early primary prevention strategies. As pre-eclampsia occurs in 2–5% of all pregnancies, the findings are relevant to the current healthcare of up to 3 million people in the U.K. and 15 million people in the U.S.A. In the present paper, we review the current literature that concerns potential mechanisms for adverse cardiovascular programming in offspring exposed to pre-eclampsia, considering two major areas of investigation: first, experimental models that mimic features of the in utero environment characteristic of pre-eclampsia, and secondly, how, in humans, offspring cardiovascular phenotype is altered after exposure to pre-eclampsia. We compare and contrast the findings from these two bodies of work to develop insights into the likely key pathways of relevance. The present review and analysis highlights the pivotal role of long-term changes in vascular function and identifies areas of growing interest, specifically, response to hypoxia, immune modification, epigenetics and the anti-angiogenic in utero milieu. PMID:22455350

Visualising associations between paired ‘omics’ data sets

PubMed Central

2012-01-01

Background Each omics platform is now able to generate a large amount of data. Genomics, proteomics, metabolomics, interactomics are compiled at an ever increasing pace and now form a core part of the fundamental systems biology framework. Recently, several integrative approaches have been proposed to extract meaningful information. However, these approaches lack of visualisation outputs to fully unravel the complex associations between different biological entities. Results The multivariate statistical approaches ‘regularized Canonical Correlation Analysis’ and ‘sparse Partial Least Squares regression’ were recently developed to integrate two types of highly dimensional ‘omics’ data and to select relevant information. Using the results of these methods, we propose to revisit few graphical outputs to better understand the relationships between two ‘omics’ data and to better visualise the correlation structure between the different biological entities. These graphical outputs include Correlation Circle plots, Relevance Networks and Clustered Image Maps. We demonstrate the usefulness of such graphical outputs on several biological data sets and further assess their biological relevance using gene ontology analysis. Conclusions Such graphical outputs are undoubtedly useful to aid the interpretation of these promising integrative analysis tools and will certainly help in addressing fundamental biological questions and understanding systems as a whole. Availability The graphical tools described in this paper are implemented in the freely available R package mixOmics and in its associated web application. PMID:23148523

75 FR 16046 - Endangered and Threatened Wildlife and Plants; Listing Casey's June Beetle as Endangered and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-31

... the physical and biological features essential to the conservation of Casey's June beetle, and what special management considerations or protections may be required to maintain or enhance the essential... with... [the Act], on which are found those physical or biological features (I) essential to the...

The Possible Role of the Kynurenine Pathway in Adolescent Depression with Melancholic Features

ERIC Educational Resources Information Center

Gabbay, Vilma; Klein, Rachel G.; Katz, Yisrael; Mendoza, Sandra; Guttman, Leah E.; Alonso, Carmen M.; Babb, James S.; Hirsch, Glenn S.; Liebes, Leonard

2010-01-01

Background: Although adolescent major depressive disorder (MDD) is acknowledged to be a heterogeneous disorder, no studies have reported on biological correlates of its clinical subgroups. This study addresses this issue by examining whether adolescent MDD with and without melancholic features (M-MDD and NonM-MDD) have distinct biological features…

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

USDA-ARS?s Scientific Manuscript database

We demonstrated that honey bee viruses, including Deformed Wing Virus (DWV), Black Queen Cell Virus (BQCV) and Isreali Acute Paralysis Virus (IAPV), could infect and replicate in the fungal pathogen Ascosphaera apis, which causes honey bee chalkbrood disease, uncovering a novel biological feature of...

Morphomics: An integral part of systems biology of the human placenta.

PubMed

Mayhew, T M

2015-04-01

The placenta is a transient organ the functioning of which has health consequences far beyond the embryo/fetus. Understanding the biology of any system (organ, organism, single cell, etc) requires a comprehensive and inclusive approach which embraces all the biomedical disciplines and 'omic' technologies and then integrates information obtained from all of them. Among the latest 'omics' is morphomics. The terms morphome and morphomics have been applied incoherently in biology and biomedicine but, recently, they have been given clear and widescale definitions. Morphomics is placed in the context of other 'omics' and its pertinent technologies and tools for sampling and quantitation are reviewed. Emphasis is accorded to the importance of random sampling principles in systems biology and the value of combining 3D quantification with alternative imaging techniques to advance knowledge and understanding of the human placental morphome. By analogy to other 'omes', the morphome is the totality of morphological features within a system and morphomics is the systematic study of those structures. Information about structure is required at multiple levels of resolution in order to understand better the processes by which a given system alters with time, experimental treatment or environmental insult. Therefore, morphomics research includes all imaging techniques at all levels of achievable resolution from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. Quantification is an important element of all 'omics' studies and, because biological systems exist and operate in 3-dimensional (3D) space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. These considerations are relevant to future study contributions to the Human Placenta Project. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure-property relationship of quinuclidinium surfactants--Towards multifunctional biologically active molecules.

PubMed

Skočibušić, Mirjana; Odžak, Renata; Štefanić, Zoran; Križić, Ivana; Krišto, Lucija; Jović, Ozren; Hrenar, Tomica; Primožič, Ines; Jurašin, Darija

2016-04-01

Motivated by diverse biological and pharmacological activity of quinuclidine and oxime compounds we have synthesized and characterized novel class of surfactants, 3-hydroxyimino quinuclidinium bromides with different alkyl chains lengths (CnQNOH; n=12, 14 and 16). The incorporation of non conventional hydroxyimino quinuclidinium headgroup and variation in alkyl chain length affects hydrophilic-hydrophobic balance of surfactant molecule and thereby physicochemical properties important for its application. Therefore, newly synthesized surfactants were characterized by the combination of different experimental techniques: X-ray analysis, potentiometry, electrical conductivity, surface tension and dynamic light scattering measurements, as well as antimicrobial susceptibility tests. Comprehensive investigation of CnQNOH surfactants enabled insight into structure-property relationship i.e., way in which the arrangement of surfactant molecules in the crystal phase correlates with their solution behavior and biologically activity. The synthesized CnQNOH surfactants exhibited high adsorption efficiency and relatively low critical micelle concentrations. In addition, all investigated compounds showed very potent and promising activity against Gram-positive and clinically relevant Gram-negative bacterial strains compared to conventional antimicrobial agents: tetracycline and gentamicin. The overall results indicate that bicyclic headgroup with oxime moiety, which affects both hydrophilicity and hydrophobicity of CnQNOH molecule in addition to enabling hydrogen bonding, has dominant effect on crystal packing and physicochemical properties. The unique structural features of cationic surfactants with hydroxyimino quinuclidine headgroup along with diverse biological activity have made them promising structures in novel drug discovery. Obtained fundamental understanding how combination of different functionalities in a single surfactant molecule affects its physicochemical properties represents a good starting point for further biological research. Copyright © 2015 Elsevier B.V. All rights reserved.

Conservation biology in Asia: the major policy challenges.

PubMed

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.

NMR spectroscopy of Group 13 metal ions: biologically relevant aspects.

PubMed

André, J P; Mäcke, H R

2003-12-01

In spite of the fact that Group 13 metal ions (Al(3+), Ga(3+), In(3+) and Tl(+/3+)) show no main biological role, they are NMR-active nuclides which can be used in magnetic resonance spectroscopy of biologically relevant systems. The fact that these metal ions are quadrupolar (with the exception of thallium) means that they are particularly sensitive to ligand type and coordination geometry. The line width of the NMR signals of their complexes shows a strong dependence on the symmetry of coordination, which constitutes an effective tool in the elucidation of structures. Here we report published NMR studies of this family of elements, applied to systems of biological importance. Special emphasis is given to binding studies of these cations to biological molecules, such as proteins, and to chelating agents of radiopharmaceutical interest. The possibility of in vivo NMR studies is also stressed, with extension to (27)Al-based MRI (magnetic resonance imaging) experiments.

Tobacco derived cancer vaccines for non-Hodgkin's lymphoma: perspectives and progress.

PubMed

McCormick, Alison A

2011-03-01

Everyone appreciates the irony of using tobacco plants to cure cancer. (1) Recently featured in a populist Wall Street Journal article, (2) the use of plants to produce medicinal products was presented as novel, even though we are decades into development of numerous products for specific medical applications (reviewed extensively in (3, 4)). Though the tobacco plant and its relatives offer a qualified set of advantages for producing complex biologicals, and in many cases overcome problems that plague traditional expression systems, FDA licensed products derived from bioengineered plants have yet to appear in the marketplace. Despite a difficult beginning, recent advances in plant biotechnology have been as cutting edge as those in the fields of molecular biology and chemical engineering, which now position the field for a new level of commercial relevance. The basis for this review is a description of the first FDA qualified parenterally administered vaccine clinical trial using a plant derived product. We have confirmed in this trial that plant proteins can be qualified to the same level as biologicals from other sources, and are safe when given as injected vaccines. Most importantly though, immune responses to plant proteins were seen in 66% of cancer patients, and these responses were to the desired antigenic determinants, not to xenogenic plant antigens. Problems and solutions that arose during the development of a safe and effective human vaccine are discussed.

Cell membrane causes the lipid bilayers to behave as variable capacitors: A resonance with self-induction of helical proteins.

PubMed

Monajjemi, Majid

2015-12-01

Cell membrane has a unique feature of storing biological energies in a physiologically relevant environment. This study illustrates a capacitor model of biological cell membrane including DPPC structures. The electron density profile models, electron localization function (ELF) and local information entropy have been applied to study the interaction of proteins with lipid bilayers in the cell membrane. The quantum and coulomb blockade effects of different thicknesses in the membrane have also been specifically investigated. It has been exhibited the quantum effects can appear in a small region of the free space within the membrane thickness due to the number and type of phospholipid layers. In addition, from the viewpoint of quantum effects by Heisenberg rule, it is shown the quantum tunneling is allowed in some micro positions while it is forbidden in other forms of membrane capacitor systems. Due to the dynamical behavior of the cell membrane, its capacitance is not fixed which results a variable capacitor. In presence of the external fields through protein trance membrane or ions, charges exert forces that can influence the state of the cell membrane. This causes to appear the charge capacitive susceptibility that can resonate with self-induction of helical coils; the resonance of which is the main reason for various biological pulses. Copyright © 2015 Elsevier B.V. All rights reserved.

Assembly of hydrogel units for 3D microenvironment in a poly(dimethylsiloxane) channel

NASA Astrophysics Data System (ADS)

Cho, Chang Hyun; Kwon, Seyong; Park, Je-Kyun

2017-12-01

Construction of three-dimensional (3D) microenvironment become an important issue in recent biological studies due to their biological relevance compared to conventional two-dimensional (2D) microenvironment. Various fabrication techniques have been employed to construct a 3D microenvironment, however, it is difficult to fully satisfy the biological and mechanical properties required for the 3D cell culture system, such as heterogeneous tissue structures generated from the functional differences or diseases. We propose here an assembly method for facile construction of 3D microenvironment in a poly(dimethylsiloxane) (PDMS) channel using hydrogel units. The high-aspect-ratio of hydrogel units was achieved by fabricating these units using a 2D mold. With this approach, 3D heterogeneous hydrogel units were produced and assembled in a PDMS channel by structural hookup. In vivo-like 3D heterogeneous microenvironment in a precisely controllable fluidic system was also demonstrated using a controlled assembly of different types of hydrogel units, which was difficult to obtain from previous methods. By regulating the flow condition, the mechanical stability of the assembled hydrogel units was verified by the flow-induced deformation of hydrogel units. In addition, in vivo-like cell culture environment was demonstrated using an assembly of cell-coated hydrogel units in the fluidic channel. Based on these features, our method expects to provide a beneficial tool for the 3D cell culture module and biomimetic engineering.

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Biogeochemical cycling in the ocean. Part 1: Introduction to the effects of upwelling along the west coast of North America

NASA Technical Reports Server (NTRS)

Howe, John T.

1986-01-01

Coastal upwelling is examined as it relates to the cycling of chemical species in coastal waters along the west coast of North America. The temporal and spatial features of upwelling phenomena in the Eastern boundary regions of the North Pacific Ocean are presented and discussed in terms of upwelling episodes. Climate conditions affecting upwelling include: thermal effects, wind-induced shear stress which moves surface layers, and the curl of the wind stress vector which is thought to affect the extent and nature of upwelling and the formation of offshore convergent downwelling fronts. These effects and the interaction of sunlight and upwelled nutrients which result in a biological bloom in surface waters is modeled analytically. The roles of biological and chemical species, including the effects of predation, are discussed in that context, and relevant remote sensing and in situ observations are presented. Climatological, oceanographic, biological, physical, chemical events, and processes that pertain to biogeochemical cycling are presented and described by a set of partial differential equations. Simple preliminary results are obtained and are compared with data. Thus a fairly general framework has been laid where the many facets of biogeochemical cycling in coastal upwelled waters can be examined in their relationship to one another, and to the whole, to whatever level of detail or approximation is warranted or desired.

Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models.

PubMed

Esposito, Emilio Xavier; Hopfinger, Anton J; Shao, Chi-Yu; Su, Bo-Han; Chen, Sing-Zuo; Tseng, Yufeng Jane

2015-10-01

Carbon nanotubes have become widely used in a variety of applications including biosensors and drug carriers. Therefore, the issue of carbon nanotube toxicity is increasingly an area of focus and concern. While previous studies have focused on the gross mechanisms of action relating to nanomaterials interacting with biological entities, this study proposes detailed mechanisms of action, relating to nanotoxicity, for a series of decorated (functionalized) carbon nanotube complexes based on previously reported QSAR models. Possible mechanisms of nanotoxicity for six endpoints (bovine serum albumin, carbonic anhydrase, chymotrypsin, hemoglobin along with cell viability and nitrogen oxide production) have been extracted from the corresponding optimized QSAR models. The molecular features relevant to each of the endpoint respective mechanism of action for the decorated nanotubes are also discussed. Based on the molecular information contained within the optimal QSAR models for each nanotoxicity endpoint, either the decorator attached to the nanotube is directly responsible for the expression of a particular activity, irrespective of the decorator's 3D-geometry and independent of the nanotube, or those decorators having structures that place the functional groups of the decorators as far as possible from the nanotube surface most strongly influence the biological activity. These molecular descriptors are further used to hypothesize specific interactions involved in the expression of each of the six biological endpoints. Copyright © 2015 Elsevier Inc. All rights reserved.

Urokinase-receptor (u-PAR): an essential player in multiple games of cancer: a review on its role in tumor progression, invasion, metastasis, proliferation/dormancy, clinical outcome and minimal residual disease.

PubMed

Laufs, Stephanie; Schumacher, Jens; Allgayer, Heike

2006-08-01

The relevance of the u-PA system in mediating tumor-associated proteolysis, invasion and metastasis, amongst other phenomena associated with tumor progression, has been clearly demonstrated in diverse cancer entities. This review will update on the biological and clinical relevance of the urokinase-receptor (u-PAR). Specifically, the article focuses on the potential importance of u-PAR for the development of minimal residual disease in solid cancer, and in this context reviews the biological relevance of the u-PAR for tumor cell dormancy. Furthermore, transcriptional mechanisms regulating u-PAR in vitro and in vivo, and their potential clinical and therapeutic relevance in gastrointestinal cancers, are elucidated.

Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization.

PubMed

Cai, Yun; Gu, Hong; Kenney, Toby

2017-08-31

Learning the structure of microbial communities is critical in understanding the different community structures and functions of microbes in distinct individuals. We view microbial communities as consisting of many subcommunities which are formed by certain groups of microbes functionally dependent on each other. The focus of this paper is on methods for extracting the subcommunities from the data, in particular Non-Negative Matrix Factorization (NMF). Our methods can be applied to both OTU data and functional metagenomic data. We apply the existing unsupervised NMF method and also develop a new supervised NMF method for extracting interpretable information from classification problems. The relevance of the subcommunities identified by NMF is demonstrated by their excellent performance for classification. Through three data examples, we demonstrate how to interpret the features identified by NMF to draw meaningful biological conclusions and discover hitherto unidentified patterns in the data. Comparing whole metagenomes of various mammals, (Muegge et al., Science 332:970-974, 2011), the biosynthesis of macrolides pathway is found in hindgut-fermenting herbivores, but not carnivores. This is consistent with results in veterinary science that macrolides should not be given to non-ruminant herbivores. For time series microbiome data from various body sites (Caporaso et al., Genome Biol 12:50, 2011), a shift in the microbial communities is identified for one individual. The shift occurs at around the same time in the tongue and gut microbiomes, indicating that the shift is a genuine biological trait, rather than an artefact of the method. For whole metagenome data from IBD patients and healthy controls (Qin et al., Nature 464:59-65, 2010), we identify differences in a number of pathways (some known, others new). NMF is a powerful tool for identifying the key features of microbial communities. These identified features can not only be used to perform difficult classification problems with a high degree of accuracy, they are also very interpretable and can lead to important biological insights into the structure of the communities. In addition, NMF is a dimension-reduction method (similar to PCA) in that it reduces the extremely complex microbial data into a low-dimensional representation, allowing a number of analyses to be performed more easily-for example, searching for temporal patterns in the microbiome. When we are interested in the differences between the structures of two groups of communities, supervised NMF provides a better way to do this, while retaining all the advantages of NMF-e.g. interpretability and a simple biological intuition.

Bioinformatics and School Biology

ERIC Educational Resources Information Center

Dalpech, Roger

2006-01-01

The rapidly changing field of bioinformatics is fuelling the need for suitably trained personnel with skills in relevant biological "sub-disciplines" such as proteomics, transcriptomics and metabolomics, etc. But because of the complexity--and sheer weight of data--associated with these new areas of biology, many school teachers feel…

Exemplary Programs in Secondary School Biology.

ERIC Educational Resources Information Center

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)

Identifying relevant data for a biological database: handcrafted rules versus machine learning.

PubMed

Sehgal, Aditya Kumar; Das, Sanmay; Noto, Keith; Saier, Milton H; Elkan, Charles

2011-01-01

With well over 1,000 specialized biological databases in use today, the task of automatically identifying novel, relevant data for such databases is increasingly important. In this paper, we describe practical machine learning approaches for identifying MEDLINE documents and Swiss-Prot/TrEMBL protein records, for incorporation into a specialized biological database of transport proteins named TCDB. We show that both learning approaches outperform rules created by hand by a human expert. As one of the first case studies involving two different approaches to updating a deployed database, both the methods compared and the results will be of interest to curators of many specialized databases.

A Road Less Traveled By: Exploring a Decade of Ellman Chemistry

PubMed Central

Shelat, Anang A.; Guy, R. Kiplin

2009-01-01

The Ellman group has been one of the most influential in the development and widespread adoption of combinatorial chemistry techniques for biomedical research. Their work has included substantial methodological development for library synthesis with a particular focus on new scaffolds rationally targeted to biomolecules of interest and biologically relevant natural products. Herein we analyze a representative set of libraries from this group with respect to their biological and biomedical relevance in comparison to existing drugs and probe compounds. This analysis reveals that the Ellman group has not only provided new methodologies to the community but also provided libraries with unique potential for further biological study. PMID:18343129

Bridging Physics and Biology Using Resistance and Axons

ERIC Educational Resources Information Center

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…

Making Research Fly in Schools: "Drosophila" as a Powerful Modern Tool for Teaching Biology

ERIC Educational Resources Information Center

Harbottle, Jennifer; Strangward, Patrick; Alnuamaani, Catherine; Lawes, Surita; Patel, Sanjai; Prokop, Andreas

2016-01-01

The "droso4schools" project aims to introduce the fruit fly "Drosophila" as a powerful modern teaching tool to convey curriculum-relevant specifications in biology lessons. Flies are easy and cheap to breed and have been at the forefront of biology research for a century, providing unique conceptual understanding of biology and…

Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae.

PubMed

Mirzarezaee, Mitra; Araabi, Babak N; Sadeghi, Mehdi

2010-12-19

It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes. We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%. We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae's proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs based on their biological features with acceptable accuracy. If such a hypothesis is correct for other species as well, similar methods can be applied to predict the roles of proteins in those species.

Spectroscopic and photoacoustic characterization of encapsulated iron oxide super-paramagnetic nanoparticles as a new multiplatform contrast agent

NASA Astrophysics Data System (ADS)

Armanetti, Paolo; Flori, Alessandra; Avigo, Cinzia; Conti, Luca; Valtancoli, Barbara; Petroni, Debora; Doumett, Saer; Cappiello, Laura; Ravagli, Costanza; Baldi, Giovanni; Bencini, Andrea; Menichetti, Luca

2018-06-01

Recently, a number of photoacoustic (PA) agents with increased tissue penetration and fine spatial resolution have been developed for molecular imaging and mapping of pathophysiological features at the molecular level. Here, we present bio-conjugated near-infrared light-absorbing magnetic nanoparticles as a new agent for PA imaging. These nanoparticles exhibit suitable absorption in the near-infrared region, with good photoacoustic signal generation efficiency and high photo-stability. Furthermore, these encapsulated iron oxide nanoparticles exhibit strong super-paramagnetic behavior and nuclear relaxivities that make them useful as magnetic resonance imaging (MRI) contrast media as well. Their simple bio-conjugation strategy, optical and chemical stability, and straightforward manipulation could enable the development of a PA probe with magnetic and spectroscopic properties suitable for in vitro and in vivo real-time imaging of relevant biological targets.

The B1 Protein Guides the Biosynthesis of a Lasso Peptide

NASA Astrophysics Data System (ADS)

Zhu, Shaozhou; Fage, Christopher D.; Hegemann, Julian D.; Mielcarek, Andreas; Yan, Dushan; Linne, Uwe; Marahiel, Mohamed A.

2016-10-01

Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) with a unique lariat knot-like fold that endows them with extraordinary stability and biologically relevant activity. However, the biosynthetic mechanism of these fascinating molecules remains largely speculative. Generally, two enzymes (B for processing and C for cyclization) are required to assemble the unusual knot-like structure. Several subsets of lasso peptide gene clusters feature a “split” B protein on separate open reading frames (B1 and B2), suggesting distinct functions for the B protein in lasso peptide biosynthesis. Herein, we provide new insights into the role of the RiPP recognition element (RRE) PadeB1, characterizing its capacity to bind the paeninodin leader peptide and deliver its peptide substrate to PadeB2 for processing.

Antibody Engineering and Therapeutics

PubMed Central

Almagro, Juan Carlos; Gilliland, Gary L; Breden, Felix; Scott, Jamie K; Sok, Devin; Pauthner, Matthias; Reichert, Janice M; Helguera, Gustavo; Andrabi, Raiees; Mabry, Robert; Bléry, Mathieu; Voss, James E; Laurén, Juha; Abuqayyas, Lubna; Barghorn, Stefan; Ben-Jacob, Eshel; Crowe, James E; Huston, James S; Johnston, Stephen Albert; Krauland, Eric; Lund-Johansen, Fridtjof; Marasco, Wayne A; Parren, Paul WHI; Xu, Kai Y

2014-01-01

The 24th Antibody Engineering & Therapeutics meeting brought together a broad range of participants who were updated on the latest advances in antibody research and development. Organized by IBC Life Sciences, the gathering is the annual meeting of The Antibody Society, which serves as the scientific sponsor. Preconference workshops on 3D modeling and delineation of clonal lineages were featured, and the conference included sessions on a wide variety of topics relevant to researchers, including systems biology; antibody deep sequencing and repertoires; the effects of antibody gene variation and usage on antibody response; directed evolution; knowledge-based design; antibodies in a complex environment; polyreactive antibodies and polyspecificity; the interface between antibody therapy and cellular immunity in cancer; antibodies in cardiometabolic medicine; antibody pharmacokinetics, distribution and off-target toxicity; optimizing antibody formats for immunotherapy; polyclonals, oligoclonals and bispecifics; antibody discovery platforms; and antibody-drug conjugates. PMID:24589717

The Infrared Spectrum of Matrix Isolated Aminoacetonitrile: A Precursor to the Amino Acid Glycine

NASA Technical Reports Server (NTRS)

Bernstein, Max P.; Bauschlicher, Charles W., Jr.; Sandford, Scott A.

2003-01-01

We present infrared (IR) spectral data from matrix isolation experiments and density functional theory calculations on the pre-biologically interesting molecule aminoacetonitrile, a precursor to glycine. We find that this nitrile has an unusually weak nitrile (C=N) stretch in the infrared, in contrast to expectations based on measurements and models of other nitriles under astrophysical conditions. The absence of an observable nitrile absorption feature in the infrared will make the IR search for this molecule considerably more difficult, and will raise estimates of upper limits on nitriles in interstellar and outer Solar System ices. This is also of relevance to assessing the formation routes of the amino acid glycine, since aminoacetonitrile is the putative precursor to glycine via the Strecker synthesis, the mechanism postulated to have produced the amino acids in meteorites.

Genomic evidence for the emergence and evolution of pathogenicity and niche preferences in the genus Campylobacter.

PubMed

Iraola, Gregorio; Pérez, Ruben; Naya, Hugo; Paolicchi, Fernando; Pastor, Eugenia; Valenzuela, Sebastián; Calleros, Lucía; Velilla, Alejandra; Hernández, Martín; Morsella, Claudia

2014-09-04

The genus Campylobacter includes some of the most relevant pathogens for human and animal health; the continuous effort in their characterization has also revealed new species putatively involved in different kind of infections. Nowadays, the available genomic data for the genus comprise a wide variety of species with different pathogenic potential and niche preferences. In this work, we contribute to enlarge this available information presenting the first genome for the species Campylobacter sputorum bv. sputorum and use this and the already sequenced organisms to analyze the emergence and evolution of pathogenicity and niche preferences among Campylobacter species. We found that campylobacters can be unequivocally distinguished in established and putative pathogens depending on their repertory of virulence genes, which have been horizontally acquired from other bacteria because the nonpathogenic Campylobacter ancestor emerged, and posteriorly interchanged between some members of the genus. Additionally, we demonstrated the role of both horizontal gene transfers and diversifying evolution in niche preferences, being able to distinguish genetic features associated to the tropism for oral, genital, and gastrointestinal tissues. In particular, we highlight the role of nonsynonymous evolution of disulphide bond proteins, the invasion antigen B (CiaB), and other secreted proteins in the determination of niche preferences. Our results arise from assessing the previously unmet goal of considering the whole available Campylobacter diversity for genome comparisons, unveiling notorious genetic features that could explain particular phenotypes and set the basis for future research in Campylobacter biology. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

NASA space cancer risk model-2014: Uncertainties due to qualitative differences in biological effects of HZE particles

NASA Astrophysics Data System (ADS)

Cucinotta, Francis

Uncertainties in estimating health risks from exposures to galactic cosmic rays (GCR) — comprised of protons and high-energy and charge (HZE) nuclei are an important limitation to long duration space travel. HZE nuclei produce both qualitative and quantitative differences in biological effects compared to terrestrial radiation leading to large uncertainties in predicting risks to humans. Our NASA Space Cancer Risk Model-2012 (NSCR-2012) for estimating lifetime cancer risks from space radiation included several new features compared to earlier models from the National Council on Radiation Protection and Measurements (NCRP) used at NASA. New features of NSCR-2012 included the introduction of NASA defined radiation quality factors based on track structure concepts, a Bayesian analysis of the dose and dose-rate reduction effectiveness factor (DDREF) and its uncertainty, and the use of a never-smoker population to represent astronauts. However, NSCR-2012 did not include estimates of the role of qualitative differences between HZE particles and low LET radiation. In this report we discuss evidence for non-targeted effects increasing cancer risks at space relevant HZE particle absorbed doses in tissue (<0.2 Gy), and for increased tumor lethality due to the propensity for higher rates of metastatic tumors from high LET radiation suggested by animal experiments. The NSCR-2014 model considers how these qualitative differences modify the overall probability distribution functions (PDF) for cancer mortality risk estimates from space radiation. Predictions of NSCR-2014 for International Space Station missions and Mars exploration will be described, and compared to those of our earlier NSCR-2012 model.

Intrinsic DNA curvature in trypanosomes.

PubMed

Smircich, Pablo; El-Sayed, Najib M; Garat, Beatriz

2017-11-09

Trypanosoma cruzi and Trypanosoma brucei are protozoan parasites causing Chagas disease and African sleeping sickness, displaying unique features of cellular and molecular biology. Remarkably, no canonical signals for RNA polymerase II promoters, which drive protein coding genes transcription, have been identified so far. The secondary structure of DNA has long been recognized as a signal in biological processes and more recently, its involvement in transcription initiation in Leishmania was proposed. In order to study whether this feature is conserved in trypanosomatids, we undertook a genome wide search for intrinsic DNA curvature in T. cruzi and T. brucei. Using a region integrated intrinsic curvature (RIIC) scoring that we previously developed, a non-random distribution of sequence-dependent curvature was observed. High RIIC scores were found to be significantly correlated with transcription start sites in T. cruzi, which have been mapped in divergent switch regions, whereas in T. brucei, the high RIIC scores correlated with sites that have been involved not only in RNA polymerase II initiation but also in termination. In addition, we observed regions with high RIIC score presenting in-phase tracts of Adenines, in the subtelomeric regions of the T. brucei chromosomes that harbor the variable surface glycoproteins genes. In both T. cruzi and T. brucei genomes, a link between DNA conformational signals and gene expression was found. High sequence dependent curvature is associated with transcriptional regulation regions. High intrinsic curvature also occurs at the T. brucei chromosome subtelomeric regions where the recombination processes involved in the evasion of the immune host system take place. These findings underscore the relevance of indirect DNA readout in these ancient eukaryotes.

Analysis of gene expression in a developmental context emphasizes distinct biological leitmotifs in human cancers

PubMed Central

Naxerova, Kamila; Bult, Carol J; Peaston, Anne; Fancher, Karen; Knowles, Barbara B; Kasif, Simon; Kohane, Isaac S

2008-01-01

Background In recent years, the molecular underpinnings of the long-observed resemblance between neoplastic and immature tissue have begun to emerge. Genome-wide transcriptional profiling has revealed similar gene expression signatures in several tumor types and early developmental stages of their tissue of origin. However, it remains unclear whether such a relationship is a universal feature of malignancy, whether heterogeneities exist in the developmental component of different tumor types and to which degree the resemblance between cancer and development is a tissue-specific phenomenon. Results We defined a developmental landscape by summarizing the main features of ten developmental time courses and projected gene expression from a variety of human tumor types onto this landscape. This comparison demonstrates a clear imprint of developmental gene expression in a wide range of tumors and with respect to different, even non-cognate developmental backgrounds. Our analysis reveals three classes of cancers with developmentally distinct transcriptional patterns. We characterize the biological processes dominating these classes and validate the class distinction with respect to a new time series of murine embryonic lung development. Finally, we identify a set of genes that are upregulated in most cancers and we show that this signature is active in early development. Conclusion This systematic and quantitative overview of the relationship between the neoplastic and developmental transcriptome spanning dozens of tissues provides a reliable outline of global trends in cancer gene expression, reveals potentially clinically relevant differences in the gene expression of different cancer types and represents a reference framework for interpretation of smaller-scale functional studies. PMID:18611264

Anomalous, non-Gaussian tracer diffusion in crowded two-dimensional environments

NASA Astrophysics Data System (ADS)

Ghosh, Surya K.; Cherstvy, Andrey G.; Grebenkov, Denis S.; Metzler, Ralf

2016-01-01

A topic of intense current investigation pursues the question of how the highly crowded environment of biological cells affects the dynamic properties of passively diffusing particles. Motivated by recent experiments we report results of extensive simulations of the motion of a finite sized tracer particle in a heterogeneously crowded environment made up of quenched distributions of monodisperse crowders of varying sizes in finite circular two-dimensional domains. For given spatial distributions of monodisperse crowders we demonstrate how anomalous diffusion with strongly non-Gaussian features arises in this model system. We investigate both biologically relevant situations of particles released either at the surface of an inner domain or at the outer boundary, exhibiting distinctly different features of the observed anomalous diffusion for heterogeneous distributions of crowders. Specifically we reveal an asymmetric spreading of tracers even at moderate crowding. In addition to the mean squared displacement (MSD) and local diffusion exponent we investigate the magnitude and the amplitude scatter of the time averaged MSD of individual tracer trajectories, the non-Gaussianity parameter, and the van Hove correlation function. We also quantify how the average tracer diffusivity varies with the position in the domain with a heterogeneous radial distribution of crowders and examine the behaviour of the survival probability and the dynamics of the tracer survival probability. Inter alia, the systems we investigate are related to the passive transport of lipid molecules and proteins in two-dimensional crowded membranes or the motion in colloidal solutions or emulsions in effectively two-dimensional geometries, as well as inside supercrowded, surface adhered cells.

An Automated, High-Throughput Method for Interpreting the Tandem Mass Spectra of Glycosaminoglycans

NASA Astrophysics Data System (ADS)

Duan, Jiana; Jonathan Amster, I.

2018-05-01

The biological interactions between glycosaminoglycans (GAGs) and other biomolecules are heavily influenced by structural features of the glycan. The structure of GAGs can be assigned using tandem mass spectrometry (MS2), but analysis of these data, to date, requires manually interpretation, a slow process that presents a bottleneck to the broader deployment of this approach to solving biologically relevant problems. Automated interpretation remains a challenge, as GAG biosynthesis is not template-driven, and therefore, one cannot predict structures from genomic data, as is done with proteins. The lack of a structure database, a consequence of the non-template biosynthesis, requires a de novo approach to interpretation of the mass spectral data. We propose a model for rapid, high-throughput GAG analysis by using an approach in which candidate structures are scored for the likelihood that they would produce the features observed in the mass spectrum. To make this approach tractable, a genetic algorithm is used to greatly reduce the search-space of isomeric structures that are considered. The time required for analysis is significantly reduced compared to an approach in which every possible isomer is considered and scored. The model is coded in a software package using the MATLAB environment. This approach was tested on tandem mass spectrometry data for long-chain, moderately sulfated chondroitin sulfate oligomers that were derived from the proteoglycan bikunin. The bikunin data was previously interpreted manually. Our approach examines glycosidic fragments to localize SO3 modifications to specific residues and yields the same structures reported in literature, only much more quickly.

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

PubMed Central

2009-01-01

Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing essentiality. PMID:19758426

NanoTopoChip: High-throughput nanotopographical cell instruction.

PubMed

Hulshof, Frits F B; Zhao, Yiping; Vasilevich, Aliaksei; Beijer, Nick R M; de Boer, Meint; Papenburg, Bernke J; van Blitterswijk, Clemens; Stamatialis, Dimitrios; de Boer, Jan

2017-10-15

Surface topography is able to influence cell phenotype in numerous ways and offers opportunities to manipulate cells and tissues. In this work, we develop the Nano-TopoChip and study the cell instructive effects of nanoscale topographies. A combination of deep UV projection lithography and conventional lithography was used to fabricate a library of more than 1200 different defined nanotopographies. To illustrate the cell instructive effects of nanotopography, actin-RFP labeled U2OS osteosarcoma cells were cultured and imaged on the Nano-TopoChip. Automated image analysis shows that of many cell morphological parameters, cell spreading, cell orientation and actin morphology are mostly affected by the nanotopographies. Additionally, by using modeling, the changes of cell morphological parameters could by predicted by several feature shape parameters such as lateral size and spacing. This work overcomes the technological challenges of fabricating high quality defined nanoscale features on unprecedented large surface areas of a material relevant for tissue culture such as PS and the screening system is able to infer nanotopography - cell morphological parameter relationships. Our screening platform provides opportunities to identify and study the effect of nanotopography with beneficial properties for the culture of various cell types. The nanotopography of biomaterial surfaces can be modified to influence adhering cells with the aim to improve the performance of medical implants and tissue culture substrates. However, the necessary knowledge of the underlying mechanisms remains incomplete. One reason for this is the limited availability of high-resolution nanotopographies on relevant biomaterials, suitable to conduct systematic biological studies. The present study shows the fabrication of a library of nano-sized surface topographies with high fidelity. The potential of this library, called the 'NanoTopoChip' is shown in a proof of principle HTS study which demonstrates how cells are affected by nanotopographies. The large dataset, acquired by quantitative high-content imaging, allowed us to use predictive modeling to describe how feature dimensions affect cell morphology. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Radiation biology of HZE particles

NASA Technical Reports Server (NTRS)

Nelson, Gregory A.

1990-01-01

The biological effects of heavy charged particle (HZE) radiation are of particular interest to travellers and planners for long duration space flights where exposure levels represent a potential health hazard. The unique feature of HZE radiation is the structured pattern of its energy deposition in targets which may be related to charge, velocity, or rate of energy loss. There are many consequences of this feature to biological endpoints when compared to effects of ionizing photons. Dose vs response and dose rate kinetics are modified, DNA and cellular repair systems are altered in their abilities to cope with damage and, the qualitative features of damage are unique for different ions. These features must be incorporated into any risk assessment system for radiation health management. HZE induced mutation, cell inactivation and altered organogenesis will be discussed emphasizing studies with the nematode Caenorhabditis elegans and cultured cells. Observations from radiobiology experiments in space will also be reviewed along with plans for future space-based studies.

Enhancement of COPD biological networks using a web-based collaboration interface

PubMed Central

Boue, Stephanie; Fields, Brett; Hoeng, Julia; Park, Jennifer; Peitsch, Manuel C.; Schlage, Walter K.; Talikka, Marja; Binenbaum, Ilona; Bondarenko, Vladimir; Bulgakov, Oleg V.; Cherkasova, Vera; Diaz-Diaz, Norberto; Fedorova, Larisa; Guryanova, Svetlana; Guzova, Julia; Igorevna Koroleva, Galina; Kozhemyakina, Elena; Kumar, Rahul; Lavid, Noa; Lu, Qingxian; Menon, Swapna; Ouliel, Yael; Peterson, Samantha C.; Prokhorov, Alexander; Sanders, Edward; Schrier, Sarah; Schwaitzer Neta, Golan; Shvydchenko, Irina; Tallam, Aravind; Villa-Fombuena, Gema; Wu, John; Yudkevich, Ilya; Zelikman, Mariya

2015-01-01

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks. PMID:25767696

Enhancement of COPD biological networks using a web-based collaboration interface.

PubMed

Boue, Stephanie; Fields, Brett; Hoeng, Julia; Park, Jennifer; Peitsch, Manuel C; Schlage, Walter K; Talikka, Marja; Binenbaum, Ilona; Bondarenko, Vladimir; Bulgakov, Oleg V; Cherkasova, Vera; Diaz-Diaz, Norberto; Fedorova, Larisa; Guryanova, Svetlana; Guzova, Julia; Igorevna Koroleva, Galina; Kozhemyakina, Elena; Kumar, Rahul; Lavid, Noa; Lu, Qingxian; Menon, Swapna; Ouliel, Yael; Peterson, Samantha C; Prokhorov, Alexander; Sanders, Edward; Schrier, Sarah; Schwaitzer Neta, Golan; Shvydchenko, Irina; Tallam, Aravind; Villa-Fombuena, Gema; Wu, John; Yudkevich, Ilya; Zelikman, Mariya

2015-01-01

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks.

Insights into Structural and Mechanistic Features of Viral IRES Elements

PubMed Central

Martinez-Salas, Encarnacion; Francisco-Velilla, Rosario; Fernandez-Chamorro, Javier; Embarek, Azman M.

2018-01-01

Internal ribosome entry site (IRES) elements are cis-acting RNA regions that promote internal initiation of protein synthesis using cap-independent mechanisms. However, distinct types of IRES elements present in the genome of various RNA viruses perform the same function despite lacking conservation of sequence and secondary RNA structure. Likewise, IRES elements differ in host factor requirement to recruit the ribosomal subunits. In spite of this diversity, evolutionarily conserved motifs in each family of RNA viruses preserve sequences impacting on RNA structure and RNA–protein interactions important for IRES activity. Indeed, IRES elements adopting remarkable different structural organizations contain RNA structural motifs that play an essential role in recruiting ribosomes, initiation factors and/or RNA-binding proteins using different mechanisms. Therefore, given that a universal IRES motif remains elusive, it is critical to understand how diverse structural motifs deliver functions relevant for IRES activity. This will be useful for understanding the molecular mechanisms beyond cap-independent translation, as well as the evolutionary history of these regulatory elements. Moreover, it could improve the accuracy to predict IRES-like motifs hidden in genome sequences. This review summarizes recent advances on the diversity and biological relevance of RNA structural motifs for viral IRES elements. PMID:29354113

Animal thermoregulation: a review of insulation, physiology and behaviour relevant to temperature control in buildings.

PubMed

McCafferty, D J; Pandraud, G; Gilles, J; Fabra-Puchol, M; Henry, P-Y

2017-12-28

Birds and mammals have evolved many thermal adaptations that are relevant to the bioinspired design of temperature control systems and energy management in buildings. Similar to many buildings, endothermic animals generate internal metabolic heat, are well insulated, regulate their temperature within set limits, modify microclimate and adjust thermal exchange with their environment. We review the major components of animal thermoregulation in endothermic birds and mammals that are pertinent to building engineering, in a world where climate is changing and reduction in energy use is needed. In animals, adjustment of insulation together with physiological and behavioural responses to changing environmental conditions fine-tune spatial and temporal regulation of body temperature, while also minimizing energy expenditure. These biological adaptations are characteristically flexible, allowing animals to alter their body temperatures to hourly, daily, or annual demands for energy. They exemplify how buildings could become more thermally reactive to meteorological fluctuations, capitalising on dynamic thermal materials and system properties. Based on this synthesis, we suggest that heat transfer modelling could be used to simulate these flexible biomimetic features and assess their success in reducing energy costs while maintaining thermal comfort for given building types.

An evolutionary ecology of individual differences

PubMed Central

Dall, Sasha R. X.; Bell, Alison M.; Bolnick, Daniel I.; Ratnieks, Francis L. W.

2014-01-01

Individuals often differ in what they do. This has been recognised since antiquity. Nevertheless, the ecological and evolutionary significance of such variation is attracting widespread interest, which is burgeoning to an extent that is fragmenting the literature. As a first attempt at synthesis, we focus on individual differences in behaviour within populations that exceed the day-to-day variation in individual behaviour (i.e. behavioural specialisation). Indeed, the factors promoting ecologically relevant behavioural specialisation within natural populations are likely to have far-reaching ecological and evolutionary consequences. We discuss such individual differences from three distinct perspectives: individual niche specialisations, the division of labour within insect societies and animal personality variation. In the process, while recognising that each area has its own unique motivations, we identify a number of opportunities for productive ‘crossfertilisation’ among the (largely independent) bodies of work. We conclude that a complete understanding of evolutionarily and ecologically relevant individual differences must specify how ecological interactions impact the basic biological process (e.g. Darwinian selection, development and information processing) that underpin the organismal features determining behavioural specialisations. Moreover, there is likely to be covariation amongst behavioural specialisations. Thus, we sketch the key elements of a general framework for studying the evolutionary ecology of individual differences. PMID:22897772