Simple Mathematical Model Of Pathologic Microsatellite Expansions: When Self-Reparation Does Not Work

We propose a simple model of pathologic microsatellite expansion, and describe an inherent self-repairing mechanism working against expansion. We prove that if the probabilities of elementary expansions and contractions are equal, microsatellite expansions are always self-repairing. If these probabilities are different, self-reparation does not work. Mosaicism, anticipation and reverse mutation cases are discussed in the framework of the model. We explain these phenomena and provide some theoretical evidence for their properties, for example the rarity of reverse mutations

Slower recovery in space before collapse of connected populations

Slower recovery from perturbations near a tipping point and its indirect signatures in fluctuation patterns have been suggested to foreshadow catastrophes in a wide variety of systems. Recent studies of populations in the field and in the laboratory have used time-series data to confirm some of the theoretically predicted early warning indicators, such as an increase in recovery time or in the size and timescale of fluctuations. However, the predictive power of temporal warning signals is limited by the demand for long-term observations. Large-scale spatial data are more accessible, but the performance of warning signals in spatially extended systems needs to be examined empirically. Here we use spatially extended yeast populations, an experimental system with a fold bifurcation (tipping point), to evaluate early warning signals based on spatio-temporal fluctuations and to identify a novel spatial warning indicator. We found that two leading indicators based on fluctuations increased before collapse of connected populations; however, the magnitudes of the increases were smaller than those observed in isolated populations, possibly because local variation is reduced by dispersal. Furthermore, we propose a generic indicator based on deterministic spatial patterns, which we call ‘recovery length’. As the spatial counterpart of recovery time, recovery length is the distance necessary for connected populations to recover from spatial perturbations. In our experiments, recovery length increased substantially before population collapse, suggesting that the spatial scale of recovery can provide a superior warning signal before tipping points in spatially extended systems.United States. National Institutes of Health (NIH R00 GM085279-02)United States. National Institutes of Health (NIH DP2)Alfred P. Sloan FoundationNational Science Foundation (U.S.

S.8.1 An immunochip-based interrogation of scleroderma susceptibility variants

Introduction. Understanding the genetic architecture of scleroderma (SSc) susceptibility is vital both in gene discovery and in determining the influence of previously identified susceptibility variants. It is particularly important in understanding disease mechanism in a disease with few therapies and great morbidity and mortality. Methods. We selected 557 cases from the Australian Scleroderma Cohort Study (ASCS), for genotyping with the Immunochip, a custom Illumina Infinium genotyping array containing 196 524 rare and common variants shown to be important in a wide variety of autoimmune disorders. A total of 4537 controls were taken from the 1958 British Birth cohort. Genotype data were analysed with PLINK. Samples and SNPs with low call rates were excluded, as were SNPs in Hardy-Weinberg disequilibrium or with less than two occurrences of the minor allele. Eigenstrat was used to analyse population structure. The final data set consisted of 505 cases, 4491 controls and 146 867 SNPs. Allelic association analyses were conducted using Fisher's exact test. Genotype clusters were manually examined for all associations of P < 10−5 since calling is difficult for some rare variants. Results. Significant and suggestive associations were detected at seven loci. Several of these have been previously implicated in scleroderma susceptibility (HLA-DRB1 and STAT4) and several are novel associations, including SNPs near PXK (P = 4.4 × 10−6) and CFDP1(P = 2.6 × 10−6). The strongest associations were with SNPs in the Class II region of the MHC. One of the most strongly associated SNPs [rs4639334; P = 1.6 × 10−8; odds ratio (OR) = 1.8] is in linkage disequilibrium (r2 = 0.46) with the Class II allele HLA-DRB1*11:01. This allele has been associated with SSc. Another strongly associated SNP is rs2857130 (P = 1.6 × 10−8; OR = 0.67), which lies in the promoter region of HLA-DRB1, but is not in LD with any classical MHC alleles. Outside the MHC, there were six regions of association with P < 10−5,including the confirmed SSc locus at STAT4. Several SNPs implicate a locus at PXK, which has been previously associated with SLE but not with SSc. The remaining associations are novel for both SSc and SLE and require replication. Of particular interest is a rare variant located within a non-coding RNA on chromosome 6q21 which was ∼20 times more frequent in cases than controls. We are currently dissecting the potential biological implications of this locus. Conclusions. This pilot study has confirmed previously reported SSc associations, revealed further genetic overlap between SSc and SLE, and identified putative novel SSc susceptibility loci including a rare allele with major effect siz

The dispositionalist deity: how God creates laws and why theists should care

How does God govern the world? For many theists “laws of nature” play a vital role. But what are these laws, metaphysically speaking? I shall argue that laws of nature are not external to the objects they govern, but instead should be thought of as reducible to internal features of properties. Recent work in metaphysics and philosophy of science has revived a dispositionalist conception of nature, according to which nature is not passive, but active and dynamic. Disposition theorists see particulars as being internally powerful rather than being governed by external laws of nature, making external laws in effect ontologically otiose. I will argue that theists should prefer a dispositionalist ontology, since it leads them toward the theory of concurrentism in divine conservation, rather than occasionalism, and revives the distinction between internal and external teleology. God on this view does not govern the world through external laws of nature, but rather through internal aspects of powerful properties

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results