Directional emission from asymmetric resonant cavities

Asymmetric resonant cavities (ARCs) with highly non-circular but convex cross-sections are predicted theoretically to have high-Q whispering gallery modes with very anisotropic emission. We develop a ray dynamics model for the emission pattern and present numerical and experimental confirmation of the theory.Comment: 7 pages LaTeX, 3 postscript figure

Measurement of the WWγWW\gamma gauge boson couplings in ppˉp\bar{p} Collisions at s=1.8\sqrt{s}=1.8 TeV

The $WW\gamma$ gauge boson couplings were measured using $p\bar{p}\to \ell\nu\gamma+X$ ($\ell=e,\mu$) events at $\sqrt{s}=1.8$ TeV observed with the {D\O} detector at the Fermilab Tevatron Collider. The signal, obtained from the data corresponding to an integrated luminosity of $13.8 {\rm pb}^{-1}$, agrees well with the Standard Model prediction. A fit to the photon transverse energy spectrum yields limits at the 95% confidence level on the CP--conserving anomalous coupling parameters of $-1.6<\Delta\kappa<1.8$ ($\lambda$ = 0) and $-0.6<\lambda<0.6$ ($\Delta\kappa$ = 0).Comment: 16pages (14pages + 2figure pages) Uses ReVTEX Two postscript files for figures will follow immediatel

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Modeling the impact of increased adherence to asthma therapy.

BACKGROUND: Nonadherence to medications occurs in up to 70% of patients with asthma. The effect of improving adherence is not well quantified. We developed a mathematical model with which to assess the population-level effects of improving medication prescribing and adherence for asthma. METHODS: A mathematical model, calibrated to clinical trial data from the U.S. NHLBI-funded SOCS trial and validated using data from the NHLBI SLIC trial, was used to model the effects of increased prescribing and adherence to asthma controllers. The simulated population consisted of 4,930 individuals with asthma, derived from a sample the National Asthma Survey. Main outcomes were controller use, reliever use, unscheduled doctor visits, emergency department (ED) visits, and hospitalizations. RESULTS: For the calibration, simulated outcomes agreed closely with SOCS trial outcomes, with treatment failure hazard ratios [95% confidence interval] of 0.92 [0.58-1.26], 0.97 [0.49-1.45], and 1.01 [0-1.87] for simulation vs. trial in the in placebo, salmeterol, and triamcinolone arms, respectively. For validation, simulated outcomes predicted mid- and end-point treatment failure rates, hazard ratios 1.21 [0.08-2.34] and 0.83 [0.60-1.07], respectively, for patients treated with salmeterol/triamcinolone during the first half of the SLIC study and salmeterol monotherapy during the second half. The model performed less well for patients treated with salmeterol/triamcinolone during the entire study duration, with mid- and end-point hazard ratios 0.83 [0.00-2.12] and 0.37 [0.10-0.65], respectively. Simulation of optimal adherence and prescribing indicated that closing adherence and prescription gaps could prevent as many as nine million unscheduled doctor visits, four million emergency department visits, and one million asthma-related hospitalizations each year in the U.S. CONCLUSIONS: Improvements in medication adherence and prescribing could have a substantial impact on asthma morbidity and healthcare utilization

Schematic of modeled physiological progression through time.

<p>An example of physiological progression through time, evolving according to Equation 1, with stimulus event times and effect sizes labeled as s_i and <i>α_i</i>, respectively.</p

Treatment failure rates in the SLIC trial.

<p>Treatment failure vs. time for the SLIC trial (red), and our simulation thereof (black), shown by treatment arm. Treatment failures were more frequent in the salmeterol monotherapy arms (dashed lines) and less frequent in the salmeterol/triamcinolone arms (solid lines). During the ICS reduction phase, simulated failure rates were not significantly different from those observed in the trial in either the salmeterol/triamcinolone (P = 0.71) or salmeterol monotherapy (P = 0.56) arms. During the ICS elimination phase, the simulation underpredicted the trial’s treatment failure rate in the salmeterol/triamcinolone arm (P = 0.04), but showed no significant difference from observed in the salmeterol monotherapy arm (P = 0.76).</p

Average simulated outcome rates, given differential prescribing and adherence scenarios, for asthmatic patients using inhaled controller or relief medications in the US.

<p>Major respiratory outcome rates for patients simulated under each of four prescription/adherence scenarios. All differences in outcome rates observed under different scenarios were significant (p<0.03), with the exception of controller use, reliever use, urgent office visits, and hospitalizations in the OP and EO scenarios. Because each treatment scenario is simulated with the same pool of patients, individual-level outcomes under each treatment condition are highly correlated.</p

Schematic of patient behavior as a function of pulmonary function and behavioral thresholds.

<p>The patient initiates relief medication when his or her pulmonary function (solid line) falls below his or her relief medication threshold (dotted line), and seeks emergency care when his or her pulmonary function falls below his or her emergency care threshold (dashed line).</p

Treatment failure rates in the SOCS trial.

<p>Treatment failure vs. time for the SOCS trial (red), and our simulation thereof (black), shown by treatment arm. Rates are highest in the placebo arm (thin lines), followed by the salmeterol arm (dashed lines), and the triamcinolone arm (thick lines). The difference between simulated and actual failure rates was not statistically significant (log-rank P = 0.22, 0.40, and 0.95 for difference in failure rates between simulation and trial under the placebo, salmeterol, and triamcinolone treatment conditions, respectively).</p

General characteristics of our simulated asthmatic population.

<p>The population was derived by sampling from the National Asthma Survey (NAS), with FEV₁ (absolute and % predicted) imputed using individual spirometry data taken from the run-in period of the SLIC and SOCS trials. All other values are taken directly from NAS.</p><p>Adherence (^†) is defined as the fraction of days of use for patients using a particular medication.</p><p>Smoking status (*) modeled in adults only, based on NAS data.</p