518 research outputs found
On the complexity of color-avoiding site and bond percolation
The mathematical analysis of robustness and error-tolerance of complex
networks has been in the center of research interest. On the other hand, little
work has been done when the attack-tolerance of the vertices or edges are not
independent but certain classes of vertices or edges share a mutual
vulnerability. In this study, we consider a graph and we assign colors to the
vertices or edges, where the color-classes correspond to the shared
vulnerabilities. An important problem is to find robustly connected vertex
sets: nodes that remain connected to each other by paths providing any type of
error (i.e. erasing any vertices or edges of the given color). This is also
known as color-avoiding percolation. In this paper, we study various possible
modeling approaches of shared vulnerabilities, we analyze the computational
complexity of finding the robustly (color-avoiding) connected components. We
find that the presented approaches differ significantly regarding their
complexity.Comment: 14 page
Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates
Computational drug design based on artificial intelligence is an emerging
research area. At the time of writing this paper, the world suffers from an
outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus
replication is via protease inhibition. We propose an evolutionary
multi-objective algorithm (EMOA) to design potential protease inhibitors for
SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA
maximizes the binding of candidate ligands to the protein using the docking
tool QuickVina 2, while at the same time taking into account further objectives
like drug-likeliness or the fulfillment of filter constraints. The experimental
part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202
Cognitive function, social integration and mortality in a U.S. national cohort study of older adults
<p>Abstract</p> <p>Background</p> <p>Prior research suggests an interaction between social networks and Alzheimer's disease pathology and cognitive function, all predictors of survival in the elderly. We test the hypotheses that both social integration and cognitive function are independently associated with subsequent mortality and there is an interaction between social integration and cognitive function as related to mortality in a national cohort of older persons.</p> <p>Methods</p> <p>Data were analyzed from a longitudinal follow-up study of 5,908 American men and women aged 60 years and over examined in 1988–1994 followed an average 8.5 yr. Measurements at baseline included self-reported social integration, socio-demographics, health, body mass index, C-reactive protein and a short index of cognitive function (SICF).</p> <p>Results</p> <p>Death during follow-up occurred in 2,431. In bivariate analyses indicators of greater social integration were associated with higher cognitive function. Among persons with SICF score of 17, 22% died compared to 54% of those with SICF score of 0–11 (p < 0.0001). After adjusting for confounding by baseline socio-demographics and health status, the hazards ratio (HR) (95% confidence limits) for low SICF score was 1.43 (1.13–1.80, p < 0.001). After controlling for health behaviors, blood pressure and body mass, C-reactive protein and social integration, the HR was 1.36 (1.06–1.76, p = 0.02). Further low compared to high social integration was also independently associated with increased risk of mortality: HR 1.24 (1.02–1.52, p = 0.02).</p> <p>Conclusion</p> <p>In a cohort of older Americans, analyses demonstrated a higher risk of death independent of confounders among those with low cognitive function and low social integration with no significant interaction between them.</p
Influence of hypoxia on the domiciliation of Mesenchymal Stem Cells after infusion into rats: possibilities of targeting pulmonary artery remodeling via cells therapies?
BACKGROUND: Bone marrow (BM) cells are promising tools for vascular therapies. Here, we focused on the possibility of targeting the hypoxia-induced pulmonary artery hypertension remodeling with systemic delivery of BM-derived mesenchymal stem cells (MSCs) into non-irradiated rats. METHODS: Six-week-old Wistar rats were exposed to 3-week chronic hypoxia leading to pulmonary artery wall remodeling. Domiciliation of adhesive BM-derived CD45(- )CD73(+ )CD90(+ )MSCs was first studied after a single intravenous infusion of Indium-111-labeled MSCs followed by whole body scintigraphies and autoradiographies of different harvested organs. In a second set of experiments, enhanced-GFP labeling allowed to observe distribution at later times using sequential infusions during the 3-week hypoxia exposure. RESULTS: A 30% pulmonary retention was observed by scintigraphies and no differences were observed in the global repartition between hypoxic and control groups. Intrapulmonary radioactivity repartition was homogenous in both groups, as shown by autoradiographies. BM-derived GFP-labeled MSCs were observed with a global repartition in liver, in spleen, in lung parenchyma and rarely in the adventitial layer of remodeled vessels. Furthermore this global repartition was not modified by hypoxia. Interestingly, these cells displayed in vivo bone marrow homing, proving a preservation of their viability and function. Bone marrow homing of GFP-labeled MSCs was increased in the hypoxic group. CONCLUSION: Adhesive BM-derived CD45(- )CD73(+ )CD90(+ )MSCs are not integrated in the pulmonary arteries remodeled media after repeated intravenous infusions in contrast to previously described in systemic vascular remodeling or with endothelial progenitor cells infusions
Communicable Diseases Prioritized for Surveillance and Epidemiological Research: Results of a Standardized Prioritization Procedure in Germany, 2011
To establish strategic priorities for the German national public health institute (RKI) and guide the institute's mid-term strategic decisions, we prioritized infectious pathogens in accordance with their importance for national surveillance and epidemiological research.We used the Delphi process with internal (RKI) and external experts and a metric-consensus approach to score pathogens according to ten three-tiered criteria. Additional experts were invited to weight each criterion, leading to the calculation of a median weight by which each score was multiplied. We ranked the pathogens according to the total weighted score and divided them into four priority groups.., Respiratory syncytial virus or Hantavirus) indicate a possible under-recognised importance within the current German public health framework. A process to strengthen respective surveillance systems and research has been started. The prioritization methodology has worked well; its modular structure makes it potentially useful for other settings
On the magnetic fields generated by experimental dynamos
We review the results obtained by three successful fluid dynamo experiments
and discuss what has been learnt from them about the effect of turbulence on
the dynamo threshold and saturation. We then discuss several questions that are
still open and propose experiments that could be performed to answer some of
them.Comment: 40 pages, 13 figure
Mesoscopic organization reveals the constraints governing C. elegans nervous system
One of the biggest challenges in biology is to understand how activity at the
cellular level of neurons, as a result of their mutual interactions, leads to
the observed behavior of an organism responding to a variety of environmental
stimuli. Investigating the intermediate or mesoscopic level of organization in
the nervous system is a vital step towards understanding how the integration of
micro-level dynamics results in macro-level functioning. In this paper, we have
considered the somatic nervous system of the nematode Caenorhabditis elegans,
for which the entire neuronal connectivity diagram is known. We focus on the
organization of the system into modules, i.e., neuronal groups having
relatively higher connection density compared to that of the overall network.
We show that this mesoscopic feature cannot be explained exclusively in terms
of considerations, such as optimizing for resource constraints (viz., total
wiring cost) and communication efficiency (i.e., network path length).
Comparison with other complex networks designed for efficient transport (of
signals or resources) implies that neuronal networks form a distinct class.
This suggests that the principal function of the network, viz., processing of
sensory information resulting in appropriate motor response, may be playing a
vital role in determining the connection topology. Using modular spectral
analysis, we make explicit the intimate relation between function and structure
in the nervous system. This is further brought out by identifying functionally
critical neurons purely on the basis of patterns of intra- and inter-modular
connections. Our study reveals how the design of the nervous system reflects
several constraints, including its key functional role as a processor of
information.Comment: Published version, Minor modifications, 16 pages, 9 figure
Type Ia Supernovae as Stellar Endpoints and Cosmological Tools
Empirically, Type Ia supernovae are the most useful, precise, and mature
tools for determining astronomical distances. Acting as calibrated candles they
revealed the presence of dark energy and are being used to measure its
properties. However, the nature of the SN Ia explosion, and the progenitors
involved, have remained elusive, even after seven decades of research. But now
new large surveys are bringing about a paradigm shift --- we can finally
compare samples of hundreds of supernovae to isolate critical variables. As a
result of this, and advances in modeling, breakthroughs in understanding all
aspects of SNe Ia are finally starting to happen.Comment: Invited review for Nature Communications. Final published version.
Shortened, update
Clusters of galaxies : observational properties of the diffuse radio emission
Clusters of galaxies, as the largest virialized systems in the Universe, are
ideal laboratories to study the formation and evolution of cosmic
structures...(abridged)... Most of the detailed knowledge of galaxy clusters
has been obtained in recent years from the study of ICM through X-ray
Astronomy. At the same time, radio observations have proved that the ICM is
mixed with non-thermal components, i.e. highly relativistic particles and
large-scale magnetic fields, detected through their synchrotron emission. The
knowledge of the properties of these non-thermal ICM components has increased
significantly, owing to sensitive radio images and to the development of
theoretical models. Diffuse synchrotron radio emission in the central and
peripheral cluster regions has been found in many clusters. Moreover
large-scale magnetic fields appear to be present in all galaxy clusters, as
derived from Rotation Measure (RM) studies. Non-thermal components are linked
to the cluster X-ray properties, and to the cluster evolutionary stage, and are
crucial for a comprehensive physical description of the intracluster medium.
They play an important role in the cluster formation and evolution. We review
here the observational properties of diffuse non-thermal sources detected in
galaxy clusters: halos, relics and mini-halos. We discuss their classification
and properties. We report published results up to date and obtain and discuss
statistical properties. We present the properties of large-scale magnetic
fields in clusters and in even larger structures: filaments connecting galaxy
clusters. We summarize the current models of the origin of these cluster
components, and outline the improvements that are expected in this area from
future developments thanks to the new generation of radio telescopes.Comment: Accepted for the publication in The Astronomy and Astrophysics
Review. 58 pages, 26 figure
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