2,826 research outputs found
Regulatory activity revealed by dynamic correlations in gene expression noise
Gene regulatory interactions are context dependent, active in some cellular states but not in others. Stochastic fluctuations, or 'noise', in gene expression propagate through active, but not inactive, regulatory links^(1,2). Thus, correlations in gene expression noise could provide a noninvasive means to probe the activity states of regulatory links. However, global, 'extrinsic', noise sources generate correlations even without direct regulatory links. Here we show that single-cell time-lapse microscopy, by revealing time lags due to regulation, can discriminate between active regulatory connections and extrinsic noise. We demonstrate this principle mathematically, using stochastic modeling, and experimentally, using simple synthetic gene circuits. We then use this approach to analyze dynamic noise correlations in the galactose metabolism genes of Escherichia coli. We find that the CRP-GalS-GalE feed-forward loop is inactive in standard conditions but can become active in a GalR mutant. These results show how noise can help analyze the context dependence of regulatory interactions in endogenous gene circuits
Staircase polygons: moments of diagonal lengths and column heights
We consider staircase polygons, counted by perimeter and sums of k-th powers
of their diagonal lengths, k being a positive integer. We derive limit
distributions for these parameters in the limit of large perimeter and compare
the results to Monte-Carlo simulations of self-avoiding polygons. We also
analyse staircase polygons, counted by width and sums of powers of their column
heights, and we apply our methods to related models of directed walks.Comment: 24 pages, 7 figures; to appear in proceedings of Counting Complexity:
An International Workshop On Statistical Mechanics And Combinatorics, 10-15
July 2005, Queensland, Australi
Validation of Claims Data Algorithms to Identify Nonmelanoma Skin Cancer
Health maintenance organization (HMO) administrative databases have been used as sampling frames for ascertaining nonmelanoma skin cancer (NMSC). However, because of the lack of tumor registry information on these cancers, these ascertainment methods have not been previously validated. NMSC cases arising from patients served by a staff model medical group and diagnosed between 1 January 2007 and 31 December 2008 were identified from claims data using three ascertainment strategies. These claims data cases were then compared with NMSC identified using natural language processing (NLP) of electronic pathology reports (EPRs), and sensitivity, specificity, positive and negative predictive values were calculated. Comparison of claims data–ascertained cases with the NLP demonstrated sensitivities ranging from 48 to 65% and specificities from 85 to 98%, with ICD-9-CM ascertainment demonstrating the highest case sensitivity, although the lowest specificity. HMO health plan claims data had a higher specificity than all-payer claims data. A comparison of EPR and clinic log registry cases showed a sensitivity of 98% and a specificity of 99%. Validation of administrative data to ascertain NMSC demonstrates respectable sensitivity and specificity, although NLP ascertainment was superior. There is a substantial difference in cases identified by NLP compared with claims data, suggesting that formal surveillance efforts should be considered
Pure point diffraction and cut and project schemes for measures: The smooth case
We present cut and project formalism based on measures and continuous weight
functions of sufficiently fast decay. The emerging measures are strongly almost
periodic. The corresponding dynamical systems are compact groups and
homomorphic images of the underlying torus. In particular, they are strictly
ergodic with pure point spectrum and continuous eigenfunctions. Their
diffraction can be calculated explicitly. Our results cover and extend
corresponding earlier results on dense Dirac combs and continuous weight
functions with compact support. They also mark a clear difference in terms of
factor maps between the case of continuous and non-continuous weight functions.Comment: 30 page
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Circulating anti-angiogenic factors during hypertensive pregnancy and increased risk of respiratory distress syndrome in preterm neonates
Objective: To test the hypothesis that high circulating concen-trations of maternal anti-angiogenic factors are associated with increased risk of respiratory distress syndrome (RDS). Study Design: This is a nested case-control study of nulliparous women who delivered less than 37 weeks of gestation within the Calcium for Preeclampsia Prevention (CPEP) trial. The study included 116 women with preeclampsia or gestational hyperten-sion and 323 normotensive controls. Soluble fms-like tyrosine kinase 1 (sFlt1), placental growth factor (PlGF) and soluble endo-glin (sEng) in maternal serum were measured at 21–32 weeks of gestation. Results: Preterm infants born to hypertensive mothers were more likely to develop RDS (22.5% vs. 20.9%, p =0.03). After adjustment for gestational age at delivery, the odds ratio for the relationship between hypertension in pregnancy and RDS was 2.18 (95% CI 1.08–4.39). In hypertensive pregnancies women whose infants developed RDS had significantly higher circulating mean sFlt1 levels during midpregnancy (21–32 weeks of gestation) even after adjustment for gestational age at delivery (21,516 pg/mL vs. 7,000 pg/mL, p =0.01). Conclusions: Preterm preeclampsia and gestational hypertension, charac-terized by high circulating levels of sFlt1, are associated with a twofold increased risk of RDS in infants delivered before 37 weeks. Among women with these hypertensive pregnancies circulating sFlt1 concentrations during midpregnancy were substantially higher in women whose infants developed RDS
Rigorous results on spontaneous symmetry breaking in a one-dimensional driven particle system
We study spontaneous symmetry breaking in a one-dimensional driven
two-species stochastic cellular automaton with parallel sublattice update and
open boundaries. The dynamics are symmetric with respect to interchange of
particles. Starting from an empty initial lattice, the system enters a symmetry
broken state after some time T_1 through an amplification loop of initial
fluctuations. It remains in the symmetry broken state for a time T_2 through a
traffic jam effect. Applying a simple martingale argument, we obtain rigorous
asymptotic estimates for the expected times ~ L ln(L) and ln() ~ L,
where L is the system size. The actual value of T_1 depends strongly on the
initial fluctuation in the amplification loop. Numerical simulations suggest
that T_2 is exponentially distributed with a mean that grows exponentially in
system size. For the phase transition line we argue and confirm by simulations
that the flipping time between sign changes of the difference of particle
numbers approaches an algebraic distribution as the system size tends to
infinity.Comment: 23 pages, 7 figure
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