Comparative genomics and understanding of microbial biology.

The sequences of close to 30 microbial genomes have been completed during the past 5 years, and the sequences of more than 100 genomes should be completed in the next 2 to 4 years. Soon, completed microbial genome sequences will represent a collection of >200,000 predicted coding sequences. While analysis of a single genome provides tremendous biological insights on any given organism, comparative analysis of multiple genomes provides substantially more information on the physiology and evolution of microbial species and expands our ability to better assign putative function to predicted coding sequences

Orbital Instabilities in a Triaxial Cusp Potential

This paper constructs an analytic form for a triaxial potential that describes the dynamics of a wide variety of astrophysical systems, including the inner portions of dark matter halos, the central regions of galactic bulges, and young embedded star clusters. Specifically, this potential results from a density profile of the form $\rho (m) \propto m^{-1}$, where the radial coordinate is generalized to triaxial form so that $m^2 = x^2/a^2 + y^2/b^2 + z^2/c^2$. Using the resulting analytic form of the potential, and the corresponding force laws, we construct orbit solutions and show that a robust orbit instability exists in these systems. For orbits initially confined to any of the three principal planes, the motion in the perpendicular direction can be unstable. We discuss the range of parameter space for which these orbits are unstable, find the growth rates and saturation levels of the instability, and develop a set of analytic model equations that elucidate the essential physics of the instability mechanism. This orbit instability has a large number of astrophysical implications and applications, including understanding the formation of dark matter halos, the structure of galactic bulges, the survival of tidal streams, and the early evolution of embedded star clusters.Comment: 50 pages, accepted for publication in Ap

Goodness-of-Fit Tests DIFF1 and DIFF2 for Locally-Normalized Supernova Spectra

Two quantitative tests DIFF1 and DIFF2 for measuring goodness-of-fit between two locally-normalized supernova spectra are presented. Locally-normalized spectra are obtained by dividing a spectrum by the same spectrum smoothed over a wavelength interval relatively large compared to line features, but relatively small compared to continuum features. DIFF1 essentially measures the mean relative difference between the line patterns of locally-normalized spectra and DIFF2 is DIFF1 minimized by a relative logarithmic wavelength shift between the spectra: the shift is effectively an artificial relative Doppler shift. Both DIFF1 and DIFF2 measure the physical similarity of line formation, and thus of supernovae. DIFF1 puts more weight on overall physical similarity of the supernovae than DIFF2 because the DIFF2 shift compensates somewhat for some physical distinction in the supernovae. Both tests are useful in ordering supernovae into empirical groupings for further analysis. We present some examples of locally-normalized spectra for Type IIb supernova SN 1993J with some analysis of these spectra. The UV parts of two of the SN 1993J spectra are HST spectra that have not been published before. We also give an example of fitted locally-normalized spectra and, as an example of the utility of DIFF1 and DIFF2, some preliminary statistical results for hydrogen-deficient core-collapse (HDCC) supernova spectra. This paper makes use of and refers to material to found at the first author's online supernova spectrum database SUSPEND (SUpernovae Spectra PENDing further analysis: see http://www.nhn.ou.edu/~jeffery/astro/sne/spectra/spectra.html)Comment: 6 coauthors, 53 pages, 6 Figures, accepted by the Astrophysical Journal Supplement Series Version 2: Improved discussion from Version

REDUCE-IT USA: Results From the 3146 Patients Randomized in the United States.

BackgroundSome trials have found that patients from the United States derive less benefit than patients enrolled outside the United States. This prespecified REDUCE-IT (Reduction of Cardiovascular Events with Icosapent Ethyl - Intervention Trial) subgroup analysis was conducted to determine the degree of benefit of icosapent ethyl in the United States.MethodsREDUCE-IT randomized 8179 statin-treated patients with qualifying triglycerides ≥135 and <500 mg/dL and low-density lipoprotein cholesterol >40 and ≤100 mg/dL and a history of atherosclerosis or diabetes mellitus to icosapent ethyl 4 g/d or placebo. The primary composite end point was cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, or hospitalization for unstable angina. The key secondary composite end point was cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke. A hierarchy was prespecified for examination of individual and composite end points.ResultsA total of 3146 US patients (38.5% of the trial) were randomized and followed for a median of 4.9 years; 32.3% were women and 9.7% were Hispanic. The primary composite end point occurred in 24.7% of placebo-treated patients versus 18.2% of icosapent ethyl-treated patients (hazard ratio [HR], 0.69 [95% CI, 0.59-0.80]; P=0.000001); the key secondary composite end point occurred in 16.6% versus 12.1% (HR, 0.69 [95% CI, 0.57-0.83]; P=0.00008). All prespecified hierarchical end points were meaningfully and significantly reduced, including cardiovascular death (6.7% to 4.7%; HR, 0.66 [95% CI, 0.49-0.90]; P=0.007), myocardial infarction (8.8% to 6.7%; HR, 0.72 [95% CI, 0.56-0.93]; P=0.01), stroke (4.1% to 2.6%; HR, 0.63 [95% CI, 0.43-0.93]; P=0.02), and all-cause mortality (9.8% to 7.2%; HR, 0.70 [95% CI, 0.55-0.90]; P=0.004); for all-cause mortality in the US versus non-US patients, Pinteraction=0.02. Safety and tolerability findings were consistent with the full study cohort.ConclusionsWhereas the non-US subgroup showed significant reductions in the primary and key secondary end points, the US subgroup demonstrated particularly robust risk reductions across a variety of individual and composite end points, including all-cause mortality.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT01492361

The Optical Alignment System of the ATLAS Muon Spectrometer Endcaps

The muon spectrometer of the ATLAS detector at the Large Hadron Collider (LHC) at CERN consists of over a thousand muon precision chambers, arranged in three concentrical cylinders in the barrel region, and in four wheels in each of the two endcaps. The endcap wheels are located between 7m and 22m from the interaction point, and have diameters between 13m and 24m. Muon chambers are equipped with a complex on-line optical alignment system to monitor their positions and deformations during ATLAS data-taking. We describe the layout of the endcap part of the alignment system and the design and calibration of the optical sensors, as well as the various software components. About 1% of the system has been subjected to performance tests in the H8 beam line at CERN, and results of these tests are discussed. The installation and commissioning of the full system in the ATLAS cavern is well underway, and results from approximately half of the system indicate that we will reach the ambitious goal of a 40mu alignment accuracy, required for reconstructing final-state muons at the highest expected energies

Proton Motive Force-Dependent Hoechst 33342 Transport by the ABC Transporter LmrA of Lactococcus lactis

The fluorescent compound Hoechst 33342 is a substrate for many multidrug resistance (MDR) transporters and is widely used to characterize their transport activity. We have constructed mutants of the adenosine triphosphate (ATP) binding cassette (ABC)-type MDR transporter LmrA of Lactococcus lactis that are defective in ATP hydrolysis. These mutants and wild-type LmrA exhibited an atypical behavior in the Hoechst 33342 transport assay. In membrane vesicles, Hoechst 33342 transport was shown to be independent of the ATPase activity of LmrA, and it was not inhibited by orthovanadate but sensitive to uncouplers that collapse the proton gradient and to N,N'-dicyclohexylcarbodiimide, an inhibitor of the F0F1-ATPase. In contrast, transport of Hoechst 33342 by the homologous, heterodimeric MDR transporter LmrCD showed a normal ATP dependence and was insensitive to uncouplers of the proton gradient. With intact cells, expression of LmrA resulted in an increased rate of Hoechst 33342 influx while LmrCD caused a decrease in the rate of Hoechst 33342 influx. Cellular toxicity assays using a triple knockout strain, i.e., L. lactis ΔlmrA ΔlmrCD, demonstrate that expression of LmrCD protects cells against the growth inhibitory effects of Hoechst 33342, while in the presence of LmrA, cells are more susceptible to Hoechst 33342. Our data demonstrate that the LmrA-mediated Hoechst 33342 transport in membrane vesicles is influenced by the transmembrane pH gradient due to a pH-dependent partitioning of Hoechst 33342 into the membrane.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal