86 research outputs found
Dynamical Patterns of Cattle Trade Movements
Despite their importance for the spread of zoonotic diseases, our
understanding of the dynamical aspects characterizing the movements of farmed
animal populations remains limited as these systems are traditionally studied
as static objects and through simplified approximations. By leveraging on the
network science approach, here we are able for the first time to fully analyze
the longitudinal dataset of Italian cattle movements that reports the mobility
of individual animals among farms on a daily basis. The complexity and
inter-relations between topology, function and dynamical nature of the system
are characterized at different spatial and time resolutions, in order to
uncover patterns and vulnerabilities fundamental for the definition of targeted
prevention and control measures for zoonotic diseases. Results show how the
stationarity of statistical distributions coexists with a strong and
non-trivial evolutionary dynamics at the node and link levels, on all
timescales. Traditional static views of the displacement network hide important
patterns of structural changes affecting nodes' centrality and farms' spreading
potential, thus limiting the efficiency of interventions based on partial
longitudinal information. By fully taking into account the longitudinal
dimension, we propose a novel definition of dynamical motifs that is able to
uncover the presence of a temporal arrow describing the evolution of the system
and the causality patterns of its displacements, shedding light on mechanisms
that may play a crucial role in the definition of preventive actions
Dynamical Patterns of Cattle Trade Movements
Despite their importance for the spread of zoonotic diseases, our
understanding of the dynamical aspects characterizing the movements of farmed
animal populations remains limited as these systems are traditionally studied
as static objects and through simplified approximations. By leveraging on the
network science approach, here we are able for the first time to fully analyze
the longitudinal dataset of Italian cattle movements that reports the mobility
of individual animals among farms on a daily basis. The complexity and
inter-relations between topology, function and dynamical nature of the system
are characterized at different spatial and time resolutions, in order to
uncover patterns and vulnerabilities fundamental for the definition of targeted
prevention and control measures for zoonotic diseases. Results show how the
stationarity of statistical distributions coexists with a strong and
non-trivial evolutionary dynamics at the node and link levels, on all
timescales. Traditional static views of the displacement network hide important
patterns of structural changes affecting nodes' centrality and farms' spreading
potential, thus limiting the efficiency of interventions based on partial
longitudinal information. By fully taking into account the longitudinal
dimension, we propose a novel definition of dynamical motifs that is able to
uncover the presence of a temporal arrow describing the evolution of the system
and the causality patterns of its displacements, shedding light on mechanisms
that may play a crucial role in the definition of preventive actions
Where do these bugs come from? Phenotypic structure of Triatoma infestans populations after control interventions in the Argentine Chaco
Search for the standard model Higgs boson in the H to ZZ to 2l 2nu channel in pp collisions at sqrt(s) = 7 TeV
A search for the standard model Higgs boson in the H to ZZ to 2l 2nu decay
channel, where l = e or mu, in pp collisions at a center-of-mass energy of 7
TeV is presented. The data were collected at the LHC, with the CMS detector,
and correspond to an integrated luminosity of 4.6 inverse femtobarns. No
significant excess is observed above the background expectation, and upper
limits are set on the Higgs boson production cross section. The presence of the
standard model Higgs boson with a mass in the 270-440 GeV range is excluded at
95% confidence level.Comment: Submitted to JHE
A Curve Shaped Description of Large Networks, with an Application to the Evaluation of Network Models
BACKGROUND: Understanding the structure of complex networks is a continuing challenge, which calls for novel approaches and models to capture their structure and reveal the mechanisms that shape the networks. Although various topological measures, such as degree distributions or clustering coefficients, have been proposed to characterize network structure from many different angles, a comprehensive and intuitive representation of large networks that allows quantitative analysis is still difficult to achieve. METHODOLOGY/PRINCIPAL FINDINGS: Here we propose a mesoscopic description of large networks which associates networks of different structures with a set of particular curves, using breadth-first search. After deriving the expressions of the curves of the random graphs and a small-world-like network, we found that the curves possess a number of network properties together, including the size of the giant component and the local clustering. Besides, the curve can also be used to evaluate the fit of network models to real-world networks. We describe a simple evaluation method based on the curve and apply it to the Drosophila melanogaster protein interaction network. The evaluation method effectively identifies which model better reproduces the topology of the real network among the given models and help infer the underlying growth mechanisms of the Drosophila network. CONCLUSIONS/SIGNIFICANCE: This curve-shaped description of large networks offers a wealth of possibilities to develop new approaches and applications including network characterization, comparison, classification, modeling and model evaluation, differing from using a large bag of topological measures
Analysis of feedback loops and robustness in network evolution based on Boolean models
<p>Abstract</p> <p>Background</p> <p>Many biological networks such as protein-protein interaction networks, signaling networks, and metabolic networks have topological characteristics of a scale-free degree distribution. Preferential attachment has been considered as the most plausible evolutionary growth model to explain this topological property. Although various studies have been undertaken to investigate the structural characteristics of a network obtained using this growth model, its dynamical characteristics have received relatively less attention.</p> <p>Results</p> <p>In this paper, we focus on the robustness of a network that is acquired during its evolutionary process. Through simulations using Boolean network models, we found that preferential attachment increases the number of coupled feedback loops in the course of network evolution. Whereas, if networks evolve to have more coupled feedback loops rather than following preferential attachment, the resulting networks are more robust than those obtained through preferential attachment, although both of them have similar degree distributions.</p> <p>Conclusion</p> <p>The presented analysis demonstrates that coupled feedback loops may play an important role in network evolution to acquire robustness. The result also provides a hint as to why various biological networks have evolved to contain a number of coupled feedback loops.</p
FLP Recombinase-Mediated Site-Specific Recombination in Silkworm, Bombyx mori
A comprehensive understanding of gene function and the production of site-specific genetically modified mutants are two major goals of genetic engineering in the post-genomic era. Although site-specific recombination systems have been powerful tools for genome manipulation of many organisms, they have not yet been established for use in the manipulation of the silkworm Bombyx mori genome. In this study, we achieved site-specific excision of a target gene at predefined chromosomal sites in the silkworm using a FLP/FRT site-specific recombination system. We first constructed two stable transgenic target silkworm strains that both contain a single copy of the transgene construct comprising a target gene expression cassette flanked by FRT sites. Using pre-blastoderm microinjection of a FLP recombinase helper expression vector, 32 G3 site-specific recombinant transgenic individuals were isolated from five of 143 broods. The average frequency of FLP recombinase-mediated site-specific excision in the two target strains genome was approximately 3.5%. This study shows that it is feasible to achieve site-specific recombination in silkworms using the FLP/FRT system. We conclude that the FLP/FRT system is a useful tool for genome manipulation in the silkworm. Furthermore, this is the first reported use of the FLP/FRT system for the genetic manipulation of a lepidopteran genome and thus provides a useful reference for the establishment of genome manipulation technologies in other lepidopteran species
Listeria monocytogenes in Milk Products
peer-reviewedMilk and milk products are frequently identified as vectors for transmission of Listeria monocytogenes. Milk can be contaminated at farm level either by indirect external contamination from the farm environment or less frequently by direct contamination of the milk from infection in the animal. Pasteurisation of milk will kill L. monocytogenes, but post-pasteurisation contamination, consumption of unpasteurised milk and manufacture of unpasteurised milk products can lead to milk being the cause of outbreaks of listeriosis. Therefore, there is a concern that L. monocytogenes in milk could lead to a public health risk. To protect against this risk, there is a need for awareness surrounding the issues, hygienic practices to reduce the risk and adequate sampling and analysis to verify that the risk is controlled. This review will highlight the issues surrounding L. monocytogenes in milk and milk products, including possible control measures. It will therefore create awareness about L. monocytogenes, contributing to protection of public health
Polyamide-Scorpion Cyclam Lexitropsins Selectively Bind AT-Rich DNA Independently of the Nature of the Coordinated Metal
Cyclam was attached to 1-, 2- and 3-pyrrole lexitropsins for the first time
through a synthetically facile copper-catalyzed “click” reaction.
The corresponding copper and zinc complexes were synthesized and characterized.
The ligand and its complexes bound AT-rich DNA selectively over GC-rich DNA, and
the thermodynamic profile of the binding was evaluated by isothermal titration
calorimetry. The metal, encapsulated in a scorpion azamacrocyclic complex, did
not affect the binding, which was dominated by the organic tail
Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement
The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the
progress of the discipline. In this paper we describe and critically assess the different ways
AI systems are evaluated, and the role of components and techniques in these systems. We
first focus on the traditional task-oriented evaluation approach. We identify three kinds of
evaluation: human discrimination, problem benchmarks and peer confrontation. We describe
some of the limitations of the many evaluation schemes and competitions in these three categories,
and follow the progression of some of these tests. We then focus on a less customary
(and challenging) ability-oriented evaluation approach, where a system is characterised by
its (cognitive) abilities, rather than by the tasks it is designed to solve. We discuss several
possibilities: the adaptation of cognitive tests used for humans and animals, the development
of tests derived from algorithmic information theory or more integrated approaches under
the perspective of universal psychometrics. We analyse some evaluation tests from AI that
are better positioned for an ability-oriented evaluation and discuss how their problems and
limitations can possibly be addressed with some of the tools and ideas that appear within
the paper. Finally, we enumerate a series of lessons learnt and generic guidelines to be used
when an AI evaluation scheme is under consideration.I thank the organisers of the AEPIA Summer School On Artificial Intelligence, held in September 2014, for giving me the opportunity to give a lecture on 'AI Evaluation'. This paper was born out of and evolved through that lecture. The information about many benchmarks and competitions discussed in this paper have been contrasted with information from and discussions with many people: M. Bedia, A. Cangelosi, C. Dimitrakakis, I. GarcIa-Varea, Katja Hofmann, W. Langdon, E. Messina, S. Mueller, M. Siebers and C. Soares. Figure 4 is courtesy of F. Martinez-Plumed. Finally, I thank the anonymous reviewers, whose comments have helped to significantly improve the balance and coverage of the paper. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under Grants TIN 2013-45732-C4-1-P, TIN 2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII2015/013.José Hernández-Orallo (2016). 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