231 research outputs found
A Computational Approach for Designing Tiger Corridors in India
Wildlife corridors are components of landscapes, which facilitate the
movement of organisms and processes between intact habitat areas, and thus
provide connectivity between the habitats within the landscapes. Corridors are
thus regions within a given landscape that connect fragmented habitat patches
within the landscape. The major concern of designing corridors as a
conservation strategy is primarily to counter, and to the extent possible,
mitigate the effects of habitat fragmentation and loss on the biodiversity of
the landscape, as well as support continuance of land use for essential local
and global economic activities in the region of reference. In this paper, we
use game theory, graph theory, membership functions and chain code algorithm to
model and design a set of wildlife corridors with tiger (Panthera tigris
tigris) as the focal species. We identify the parameters which would affect the
tiger population in a landscape complex and using the presence of these
identified parameters construct a graph using the habitat patches supporting
tiger presence in the landscape complex as vertices and the possible paths
between them as edges. The passage of tigers through the possible paths have
been modelled as an Assurance game, with tigers as an individual player. The
game is played recursively as the tiger passes through each grid considered for
the model. The iteration causes the tiger to choose the most suitable path
signifying the emergence of adaptability. As a formal explanation of the game,
we model this interaction of tiger with the parameters as deterministic finite
automata, whose transition function is obtained by the game payoff.Comment: 12 pages, 5 figures, 6 tables, NGCT conference 201
Selection of Inhibitor-Resistant Viral Potassium Channels Identifies a Selectivity Filter Site that Affects Barium and Amantadine Block
BACKGROUND:Understanding the interactions between ion channels and blockers remains an important goal that has implications for delineating the basic mechanisms of ion channel function and for the discovery and development of ion channel directed drugs. METHODOLOGY/PRINCIPAL FINDINGS:We used genetic selection methods to probe the interaction of two ion channel blockers, barium and amantadine, with the miniature viral potassium channel Kcv. Selection for Kcv mutants that were resistant to either blocker identified a mutant bearing multiple changes that was resistant to both. Implementation of a PCR shuffling and backcrossing procedure uncovered that the blocker resistance could be attributed to a single change, T63S, at a position that is likely to form the binding site for the inner ion in the selectivity filter (site 4). A combination of electrophysiological and biochemical assays revealed a distinct difference in the ability of the mutant channel to interact with the blockers. Studies of the analogous mutation in the mammalian inward rectifier Kir2.1 show that the T-->S mutation affects barium block as well as the stability of the conductive state. Comparison of the effects of similar barium resistant mutations in Kcv and Kir2.1 shows that neighboring amino acids in the Kcv selectivity filter affect blocker binding. CONCLUSIONS/SIGNIFICANCE:The data support the idea that permeant ions have an integral role in stabilizing potassium channel structure, suggest that both barium and amantadine act at a similar site, and demonstrate how genetic selections can be used to map blocker binding sites and reveal mechanistic features
Quantitative Modeling of Currents from a Voltage Gated Ion Channel Undergoing Fast Inactivation
Ion channels play a central role in setting gradients of ion concentration and electrostatic potentials, which in turn regulate sensory systems and other functions. Based on the structure of the open configuration of the Kv1.2 channel and the suggestion that the two ends of the N-terminal inactivating peptide form a bivalent complex that simultaneously blocks the channel pore and binds to the cytoplasmic T1 domain, we propose a six state kinetic model that for the first time reproduces the kinetics of recovery of the Drosophila Shaker over the full range of time scales and hyperpolarization potentials, including tail currents. The model is motivated by a normal mode analysis of the inactivated channel that suggests that a displacement consistent with models of the closed state propagates to the T1 domain via the S1-T1 linker. This motion stretches the bound (inactivating) peptide, hastening the unblocking of the pore. This pulling force is incorporated into the rates of the open to blocked states, capturing the fast recovery phase of the current for repolarization events shorter than 1 ms. If the membrane potential is hyperpolarized, essential dynamics further suggests that the T1 domain returns to a configuration where the peptide is unstretched and the S1-T1 linker is extended. Coupling this novel hyperpolarized substate to the closed, open and blocked pore states is enough to quantitatively estimate the number of open channels as a function of time and membrane potential. A straightforward prediction of the model is that a slow ramping of the potential leads to very small currents
Search For Heavy Pointlike Dirac Monopoles
We have searched for central production of a pair of photons with high
transverse energies in collisions at TeV using of data collected with the D\O detector at the Fermilab Tevatron in
1994--1996. If they exist, virtual heavy pointlike Dirac monopoles could
rescatter pairs of nearly real photons into this final state via a box diagram.
We observe no excess of events above background, and set lower 95% C.L. limits
of on the mass of a spin 0, 1/2, or 1 Dirac
monopole.Comment: 12 pages, 4 figure
The Dijet Mass Spectrum and a Search for Quark Compositeness in bar{p}p Collisions at sqrt{s} = 1.8 TeV
Using the DZero detector at the 1.8 TeV pbarp Fermilab Tevatron collider, we
have measured the inclusive dijet mass spectrum in the central pseudorapidity
region |eta_jet| < 1.0 for dijet masses greater than 200 Gev/c^2. We have also
measured the ratio of spectra sigma(|eta_jet| < 0.5)/sigma(0.5 < |eta_jet| <
1.0). The order alpha_s^3 QCD predictions are in good agreement with the data
and we rule out models of quark compositeness with a contact interaction scale
< 2.4 TeV at the 95% confidence level.Comment: 11 pages, 4 figures, 2 tables, submitted to Phys. Rev. Let
Search for High Mass Photon Pairs in p-pbar --> gamma-gamma-jet-jet Events at sqrt(s)=1.8 TeV
A search has been carried out for events in the channel p-barp --> gamma
gamma jet jet. Such a signature can characterize the production of a
non-standard Higgs boson together with a W or Z boson. We refer to this
non-standard Higgs, having standard model couplings to vector bosons but no
coupling to fermions, as a "bosonic Higgs." With the requirement of two high
transverse energy photons and two jets, the diphoton mass (m(gamma gamma))
distribution is consistent with expected background. A 90(95)% C.L. upper limit
on the cross section as a function of mass is calculated, ranging from
0.60(0.80) pb for m(gamma gamma) = 65 GeV/c^2 to 0.26(0.34) pb for m(gamma
gamma) = 150 GeV/c^2, corresponding to a 95% C.L. lower limit on the mass of a
bosonic Higgs of 78.5 GeV/c^2.Comment: 9 pages, 3 figures. Replacement has new H->gamma gamma branching
ratios and corresponding new mass limit
Zgamma Production in pbarp Collisions at sqrt(s)=1.8 TeV and Limits on Anomalous ZZgamma and Zgammagamma Couplings
We present a study of Z +gamma + X production in p-bar p collisions at
sqrt{S}=1.8 TeV from 97 (87) pb^{-1} of data collected in the eegamma
(mumugamma) decay channel with the D0 detector at Fermilab. The event yield and
kinematic characteristics are consistent with the Standard Model predictions.
We obtain limits on anomalous ZZgamma and Zgammagamma couplings for form factor
scales Lambda = 500 GeV and Lambda = 750 GeV. Combining this analysis with our
previous results yields 95% CL limits |h{Z}_{30}| < 0.36, |h{Z}_{40}| < 0.05,
|h{gamma}_{30}| < 0.37, and |h{gamma}_{40}| < 0.05 for a form factor scale
Lambda=750 GeV.Comment: 17 Pages including 2 Figures. Submitted to PR
A Measurement of the W Boson Mass
We report a measurement of the W boson mass based on an integrated luminosity
of 82 pb from \ppbar collisions at TeV recorded in
1994--1995 by the \Dzero detector at the Fermilab Tevatron. We identify W
bosons by their decays to and extract the mass by fitting the transverse
mass spectrum from 28,323 W boson candidates. A sample of 3,563 dielectron
events, mostly due to Z to ee decays, constrains models of W boson production
and the detector. We measure \mw=80.44\pm0.10(stat)\pm0.07(syst)~GeV. By
combining this measurement with our result from the 1992--1993 data set, we
obtain \mw=80.43\pm0.11 GeV.Comment: 11 pages, 5 figure
Probing Hard Color-Singlet Exchange in ppbar Collisions at root-s=630 GeV and 1800 GeV
We present results on dijet production via hard color-singlet exchange in
proton-antiproton collisions at root-s = 630 GeV and 1800 GeV using the DZero
detector. The fraction of dijet events produced via color-singlet exchange is
measured as a function of jet transverse energy, separation in pseudorapidity
between the two highest transverse energy jets, and proton-antiproton
center-of-mass energy. The results are consistent with a color-singlet fraction
that increases with an increasing fraction of quark-initiated processes and
inconsistent with two-gluon models for the hard color-singlet.Comment: 16 pages, 6 figure
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies
<p>Abstract</p> <p>Background</p> <p>All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences.</p> <p>Results</p> <p>The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%.</p> <p>Conclusions</p> <p>This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.</p
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