Identification of Chloroacetaldehyde Dehydrogenase Involved in 1,2-Dichloroethane Degradation

The degradation of 1,2-dichloroethane and 2-chloroethanol by Xanthobacter autotrophicus GJ10 proceeds via chloroacetaldehyde, a reactive and potentially toxic intermediate. The organism produced at least three different aldehyde dehydrogenases, of which one is plasmid encoded. Two mutants of strain GJ10, designated GJ10M30 and GJ10M41, could no longer grow on 2-chloroethanol and were found to lack the NAD-dependent aldehyde dehydrogenase that is the predominant protein in wild-type cells growing on 2-chloroethanol. Mutant GJ10M30, selected on the basis of its resistance to 1,2-dibromoethane, also had lost haloalkane dehalogenase activity and Hg(2+) resistance, indicating plasmid loss. From a gene bank of strain GJ10, different clones that complemented one of these mutants were isolated. In both transconjugants, the aldehyde dehydrogenase that was absent in the mutants was overexpressed. The enzyme was purified and was a tetrameric protein of 55-kDa subunits. The substrate range was rather broad, with the highest activity measured for acetaldehyde. The K(m) value for chloroacetaldehyde was 160 μM, higher than those for other aldehydes tested. It is concluded that the ability of GJ10 to grow with 2-chloroethanol is due to the high expression level of an aldehyde dehydrogenase with a rather low activity for chloroacetaldehyde

Spitzer Observations of the North Ecliptic Pole

We present a photometric catalog for Spitzer Space Telescope warm mission observations of the North Ecliptic Pole (NEP; centered at $\rm R.A.=18^h00^m00^s$, $\rm Decl.=66^d33^m38^s.552$). The observations are conducted with IRAC in 3.6 $\mu$m and 4.5 $\mu$m bands over an area of 7.04 deg$^2$ reaching 1$\sigma$ depths of 1.29 $\mu$Jy and 0.79 $\mu$Jy in the 3.6 $\mu$m and 4.5 $\mu$m bands respectively. The photometric catalog contains 380,858 sources with 3.6 $\mu$m and 4.5 $\mu$m band photometry over the full-depth NEP mosaic. Point source completeness simulations show that the catalog is 80% complete down to 19.7 AB. The accompanying catalog can be utilized in constraining the physical properties of extra-galactic objects, studying the AGN population, measuring the infrared colors of stellar objects, and studying the extra-galactic infrared background light.Comment: 10 pages, 11 figures and 3 tables. Accepted to the ApJ

Simulations of energetic beam deposition: from picoseconds to seconds

We present a new method for simulating crystal growth by energetic beam deposition. The method combines a Kinetic Monte-Carlo simulation for the thermal surface diffusion with a small scale molecular dynamics simulation of every single deposition event. We have implemented the method using the effective medium theory as a model potential for the atomic interactions, and present simulations for Ag/Ag(111) and Pt/Pt(111) for incoming energies up to 35 eV. The method is capable of following the growth of several monolayers at realistic growth rates of 1 monolayer per second, correctly accounting for both energy-induced atomic mobility and thermal surface diffusion. We find that the energy influences island and step densities and can induce layer-by-layer growth. We find an optimal energy for layer-by-layer growth (25 eV for Ag), which correlates with where the net impact-induced downward interlayer transport is at a maximum. A high step density is needed for energy induced layer-by-layer growth, hence the effect dies away at increased temperatures, where thermal surface diffusion reduces the step density. As part of the development of the method, we present molecular dynamics simulations of single atom-surface collisions on flat parts of the surface and near straight steps, we identify microscopic mechanisms by which the energy influences the growth, and we discuss the nature of the energy-induced atomic mobility

Physiotherapy alone or in combination with corticosteroid injection for acute lateral epicondylitis in general practice: A protocol for a randomised, placebo-controlled study

<p>Abstract</p> <p>Background</p> <p>Lateral epicondylitis is a painful condition responsible for loss of function and sick leave for long periods of time. In many countries, the treatment guidelines recommend a wait-and-see policy, reflecting that no conclusions on the best treatment can be drawn from the available research, published studies and meta-analyses.</p> <p>Methods/Design</p> <p>Randomized double blind controlled clinical trial in a primary care setting. While earlier trials have either compared corticosteroid injections to physical therapy or to naproxen orally, we will compare the clinical effect of physiotherapy alone or physiotherapy combined with corticosteroid injection in the initial treatment of acute tennis elbow. Patients seeing their general practitioner with lateral elbow pain of recent onset will be randomised to one of three interventions: 1: physiotherapy, corticosteroid injection and naproxen or 2: physiotherapy, placebo injection and naproxen or 3: wait and see treatment with naproxen alone. Treatment and assessments are done by two different doctors, and the contents of the injection is unknown to both the treating doctor and patient. The primary outcome measure is the patient's evaluation of improvement after 6, 12, 26 and 52 weeks. Secondary outcome measures are pain, function and severity of main complaint, pain-free grip strength, maximal grip strength, pressure-pain threshold, the patient's satisfaction with the treatment and duration of sick leave.</p> <p>Conclusion</p> <p>This article describes a randomized, double blind, controlled clinical trial with a one year follow up to investigate the effects of adding steroid injections to physiotherapy in acute lateral epicondylitis.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier: NCT00826462</p

Scale-dependence of Non-Gaussianity in the Curvaton Model

We investigate the scale-dependence of f_NL in the self-interacting curvaton model. We show that the scale-dependence, encoded in the spectral index n_{f_NL}, can be observable by future cosmic microwave background observations, such as CMBpol, in a significant part of the parameter space of the model. We point out that together with information about the trispectrum g_NL, the self-interacting curvaton model parameters could be completely fixed by observations. We also discuss the scale-dependence of g_NL and its implications for the curvaton model, arguing that it could provide a complementary probe in cases where the theoretical value of n_{f_NL} is below observational sensitivity.Comment: 14 pages, 5 figures, Eq.(10) correcte

The Impact of Assuming Flatness in the Determination of Neutrino Properties from Cosmological Data

Cosmological data have provided new constraints on the number of neutrino species and the neutrino mass. However these constraints depend on assumptions related to the underlying cosmology. Since a correlation is expected between the number of effective neutrinos N_{eff}, the neutrino mass \sum m_\nu, and the curvature of the universe \Omega_k, it is useful to investigate the current constraints in the framework of a non-flat universe. In this paper we update the constraints on neutrino parameters by making use of the latest cosmic microwave background (CMB) data from the ACT and SPT experiments and consider the possibility of a universe with non-zero curvature. We first place new constraints on N_{eff} and \Omega_k, with N_{eff} = 4.03 +/- 0.45 and 10^3 \Omega_k = -4.46 +/- 5.24. Thus, even when \Omega_k is allowed to vary, N_{eff} = 3 is still disfavored with 95% confidence. We then investigate the correlation between neutrino mass and curvature that shifts the 95% upper limit of \sum m_\nu < 0.45 eV to \sum m_\nu < 0.95 eV. Thus, the impact of assuming flatness in neutrino cosmology is significant and an essential consideration with future experiments.Comment: 6 pages. 4 figures. Submitted to PR

Local stochastic non-Gaussianity and N-body simulations

Large-scale clustering of highly biased tracers of large-scale structure has emerged as one of the best observational probes of primordial non-Gaussianity of the local type (i.e. f_{NL}^{local}). This type of non-Gaussianity can be generated in multifield models of inflation such as the curvaton model. Recently, Tseliakhovich, Hirata, and Slosar showed that the clustering statistics depend qualitatively on the ratio of inflaton to curvaton power \xi after reheating, a free parameter of the model. If \xi is significantly different from zero, so that the inflaton makes a non-negligible contribution to the primordial adiabatic curvature, then the peak-background split ansatz predicts that the halo bias will be stochastic on large scales. In this paper, we test this prediction in N-body simulations. We find that large-scale stochasticity is generated, in qualitative agreement with the prediction, but that the level of stochasticity is overpredicted by ~30%. Other predictions, such as \xi independence of the halo bias, are confirmed by the simulations. Surprisingly, even in the Gaussian case we do not find that halo model predictions for stochasticity agree consistently with simulations, suggesting that semi-analytic modeling of stochasticity is generally more difficult than modeling halo bias.Comment: v3: minor changes matching published versio

Trispectrum from Ghost Inflation

Ghost inflation predicts almost scale-invariant primordial cosmological perturbations with relatively large non-Gaussianity. The bispectrum is known to have a large contribution at the wavenumbers forming an equilateral triangle and the corresponding nonlinear parameter $f_{NL}^{equil}$ is typically of order $O(10^2)$. In this paper we calculate trispectrum from ghost inflation and show that the corresponding nonlinear parameter $\tau_{NL}$ is typically of order $O(10^4)$. We investigate the shape dependence of the trispectrum and see that it has some features different from DBI inflation. Therefore, our result may be useful as a template to distinguish ghost inflation from other models of inflation by future experiments.Comment: 25 pages, 10 figure

MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study

Simple SummaryThe prediction of pathologic complete response (pCR) to neo-adjuvant systemic therapy (NST) based on radiological assessment of pretreatment MRI exams in breast cancer patients is not possible to date. In this study, we investigated the value of pretreatment MRI-based radiomics analysis for the prediction of pCR to NST. Radiomics, clinical, and combined models were developed and validated based on MRI exams containing 320 tumors collected from two hospitals. The clinical models significantly outperformed the radiomics models for the prediction of pCR to NST and were of similar or better performance than the combined models. This indicates poor performance of the radiomics features and that in these scenarios the radiomic features did not have an added value for the clinical models developed. Due to previous and current work, we tentatively attribute the lack of significant improvement in clinical models following the addition of radiomics features to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data meant this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.This retrospective study investigated the value of pretreatment contrast-enhanced Magnetic Resonance Imaging (MRI)-based radiomics for the prediction of pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients. A total of 292 breast cancer patients, with 320 tumors, who were treated with neo-adjuvant systemic therapy and underwent a pretreatment MRI exam were enrolled. As the data were collected in two different hospitals with five different MRI scanners and varying acquisition protocols, three different strategies to split training and validation datasets were used. Radiomics, clinical, and combined models were developed using random forest classifiers in each strategy. The analysis of radiomics features had no added value in predicting pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients compared with the clinical models, nor did the combined models perform significantly better than the clinical models. Further, the radiomics features selected for the models and their performance differed with and within the different strategies. Due to previous and current work, we tentatively attribute the lack of improvement in clinical models following the addition of radiomics to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data (i.e., test-retest or similar) meant that this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics