503 research outputs found
Concentration-dependent diffusivity and anomalous diffusion: A magnetic resonance imaging study of water ingress in porous zeolite
Magnetic resonance imaging is employed to study water ingress in fine zeolite powders compacted by high pressure. The experimental conditions are chosen such that the applicability of Boltzmann's transformation of the one-dimensional diffusion equation is approximately satisfied. The measured moisture profiles indicate subdiffusive behavior with a spatiotemporal scaling variable eta=x/t(gamma/2) (0 <gamma < 1). A time-fractional diffusion equation model of anomalous diffusion is adopted to analyze the data, and an expression that yields the moisture dependence of the generalized diffusivity is derived and applied to our measured profiles. In spite of the differences between systems exhibiting different values of gamma a striking similarity in the moisture dependence of the diffusivity is apparent. This suggests that the model addresses the underlying physical processes involved in water transport.731
Ensembles of jittered association rule classifiers
The ensembling of classifiers tends to improve predictive accuracy. To obtain an ensemble with N classifiers, one typically needs to run N learning processes. In this paper we introduce and explore Model Jittering Ensembling, where one single model is perturbed in order to obtain variants that can be used as an ensemble. We use as base classifiers sets of classification association rules. The two methods of jittering ensembling we propose are Iterative Reordering Ensembling (IRE) and Post Bagging (PB). Both methods start by learning one rule set over a single run, and then produce multiple rule sets without relearning. Empirical results on 36 data sets are positive and show that both strategies tend to reduce error with respect to the single model association rule classifier. A bias–variance analysis reveals that while both IRE and PB are able to reduce the variance component of the error, IRE is particularly effective in reducing the bias component. We show that Model Jittering Ensembling can represent a very good speed-up w.r.t. multiple model learning ensembling. We also compare Model Jittering with various state of the art classifiers in terms of predictive accuracy and computational efficiency.This work was partially supported by FCT project Rank! (PTDC/EIA/81178/2006) and by AdI project Palco3.0 financed by QREN and Fundo Europeu de Desenvolvimento Regional (FEDER), and also supported by Fundacao Ciencia e Tecnologia, FEDER e Programa de Financiamento Plurianual de Unidades de I & D. Thanks are due to William Cohen for kindly providing the executable code for the SLIPPER implementation. Our gratitude goes also to our anonymous reviewers who have helped to significantly improve this paper by sharing their knowledge and their informed criticism with the authors
Cryptosporidium Priming Is More Effective than Vaccine for Protection against Cryptosporidiosis in a Murine Protein Malnutrition Model
Cryptosporidium is a major cause of severe diarrhea, especially in malnourished children. Using a murine model of C. parvum oocyst challenge that recapitulates clinical features of severe cryptosporidiosis during malnutrition, we interrogated the effect of protein malnutrition (PM) on primary and secondary responses to C. parvum challenge, and tested the differential ability of mucosal priming strategies to overcome the PM-induced susceptibility. We determined that while PM fundamentally alters systemic and mucosal primary immune responses to Cryptosporidium, priming with C. parvum (106 oocysts) provides robust protective immunity against re-challenge despite ongoing PM. C. parvum priming restores mucosal Th1-type effectors (CD3+CD8+CD103+ T-cells) and cytokines (IFNγ, and IL12p40) that otherwise decrease with ongoing PM. Vaccination strategies with Cryptosporidium antigens expressed in the S. Typhi vector 908htr, however, do not enhance Th1-type responses to C. parvum challenge during PM, even though vaccination strongly boosts immunity in challenged fully nourished hosts. Remote non-specific exposures to the attenuated S. Typhi vector alone or the TLR9 agonist CpG ODN-1668 can partially attenuate C. parvum severity during PM, but neither as effectively as viable C. parvum priming. We conclude that although PM interferes with basal and vaccine-boosted immune responses to C. parvum, sustained reductions in disease severity are possible through mucosal activators of host defenses, and specifically C. parvum priming can elicit impressively robust Th1-type protective immunity despite ongoing protein malnutrition. These findings add insight into potential correlates of Cryptosporidium immunity and future vaccine strategies in malnourished children
Promises and Prospects of Educational Technology, Evidence from Systematic Reviews and Meta-analyses
Prediction of specificity-determining residues for small-molecule kinase inhibitors
<p>Abstract</p> <p>Background</p> <p>Designing small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery. A high-throughput screen for inhibitors of a given kinase will typically yield many compounds that inhibit more than one kinase. A series of chemical modifications are usually required before a compound exhibits an acceptable selectivity profile. Rationalizing the selectivity profile for a small-molecule inhibitor in terms of the specificity-determining kinase residues for that molecule can be an important step toward the goal of developing selective kinase inhibitors.</p> <p>Results</p> <p>Here we describe S-Filter, a method that combines sequence and structural information to predict specificity-determining residues for a small molecule and its kinase selectivity profile. Analysis was performed on seven selective kinase inhibitors where a structural basis for selectivity is known. S-Filter correctly predicts specificity determinants that were described by independent groups. S-Filter also predicts a number of novel specificity determinants that can often be justified by further structural comparison.</p> <p>Conclusion</p> <p>S-Filter is a valuable tool for analyzing kinase selectivity profiles. The method identifies potential specificity determinants that are not readily apparent, and provokes further investigation at the structural level.</p
A Developmental Systems Perspective on Epistasis: Computational Exploration of Mutational Interactions in Model Developmental Regulatory Networks
The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns) depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks). Each layer of this hierarchy displays its own regulatory schemes (i.e. operational rules such as +/− feedback) and associated control parameters, resulting in characteristic variational constraints. This process can be conceptualized as a mapping issue, and in the context of highly-dimensional genotype-phenotype mappings (GPMs) epistatic events have been shown to be ubiquitous, manifested in non-linear correspondences between changes in the genotype and their phenotypic effects. In this study I concentrate on epistatic phenomena pervading levels of biological organization above the genetic material, more specifically the realm of molecular networks. At this level, systems approaches to studying GPMs are specially suitable to shed light on the mechanistic basis of epistatic phenomena. To this aim, I constructed and analyzed ensembles of highly-modular (fully interconnected) networks with distinctive topologies, each displaying dynamic behaviors that were categorized as either arbitrary or functional according to early patterning processes in the Drosophila embryo. Spatio-temporal expression trajectories in virtual syncytial embryos were simulated via reaction-diffusion models. My in silico mutational experiments show that: 1) the average fitness decay tendency to successively accumulated mutations in ensembles of functional networks indicates the prevalence of positive epistasis, whereas in ensembles of arbitrary networks negative epistasis is the dominant tendency; and 2) the evaluation of epistatic coefficients of diverse interaction orders indicates that, both positive and negative epistasis are more prevalent in functional networks than in arbitrary ones. Overall, I conclude that the phenotypic and fitness effects of multiple perturbations are strongly conditioned by both the regulatory architecture (i.e. pattern of coupled feedback structures) and the dynamic nature of the spatio-temporal expression trajectories displayed by the simulated networks
CACHE (Critical Assessment of Computational Hit-finding Experiments): A public–private partnership benchmarking initiative to enable the development of computational methods for hit-finding
One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small-molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small-molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared and openly published. CACHE will launch three new benchmarking exercises every year. The outcomes will be better prediction methods, new small-molecule binders for target proteins of importance for fundamental biology or drug discovery and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins. [Figure not available: see fulltext.
Characterization of the behavior of carotenoids from pitanga (Eugenia uniflora) and buriti (Mauritia flexuosa) during microemulsion production and in a dynamic gastrointestinal system
Uncommon tropical fruits are emerging as raw-material for new food products with health benefits. This work aimed at formulating and processing microemulsions from pitanga (Eugenia uniflora) and buriti (Mauritia flexuosa) fruits, since they are very rich in carotenoids (particularly lycopene and -carotene), in order to encapsulate and increase carotenoids bioaccessibility. Pitanga and buriti microemulsions were produced by applying a direct processing (high-speed homogenization at 15,000 rpm and ultrasound with 20 kHz probe at 40% amplitude) of the whole pulp together with surfactant (Tween 80 or Whey Protein Isolate at 2%) and corn oil (5%). All treatments (HSHUS for 04, 40, 44, 48 minmin) applied were able to increase the amount of carotenoid released. However, the processing also decreased the total amount of carotenoids in the whole pulp of studied fruits. The impact of processing during microemulsion production was not severe. The overall data suggest that the presence of surfactant and oil during processing may protect the carotenoids in fruits and microemulsions. Final recovery of total carotenoids, after passing the samples through a dynamic gastrointestinal system that simulates the human digestion, was higher for microemulsions than for whole pulps. High losses of total carotenoids in buriti and -carotene and lycopene in pitanga occurred during jejunum and ileum phases. The present work confirms that it is possible to increase -carotene and lycopene bioaccessibility from fruits by directly processing microemulsions (p<0.01).This work was supported by the São Paulo Research Foundation—FAPESP through research funding [Grant
#2015/15507-9] and Ph.D. scholarship for Paulo Berni [Grant #2014/15119-6] and a Research Internships Abroad (BEPE) support [Grant #2016/13355-0]. The author Ana C. Pinheiro is recipient of a fellowship from the Portuguese Foundation for Science and Technology (FCT) [Grant SFRH/BPD/101181/2014]info:eu-repo/semantics/publishedVersio
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