Esomeprazole 20 mg was superior to placebo for on-demand treatment of GORD; a higher dose did not confer additional clinical benefit. Over 90% of patients were willing to continue on-demand treatment with esomeprazole 20 mg over a 6-month period.
BackgroundRegulation of pre-mRNA splicing diversifies protein products and affects many biological processes. Arabidopsis thaliana Serine/Arginine-rich 45 (SR45), regulates pre-mRNA splicing by interacting with other regulatory proteins and spliceosomal subunits. Although SR45 has orthologs in diverse eukaryotes, including human RNPS1, the sr45–1 null mutant is viable. Narrow flower petals and reduced seed formation suggest that SR45 regulates genes involved in diverse processes, including reproduction. To understand how SR45 is involved in the regulation of reproductive processes, we studied mRNA from the wild-type and sr45–1 inflorescences using RNA-seq, and identified SR45-bound RNAs by immunoprecipitation.ResultsUsing a variety of bioinformatics tools, we identified a total of 358 SR45 differentially regulated (SDR) genes, 542 SR45-dependent alternative splicing (SAS) events, and 1812 SR45-associated RNAs (SARs). There is little overlap between SDR genes and SAS genes, and neither set of genes is enriched for flower or seed development. However, transcripts from reproductive process genes are significantly overrepresented in SARs. In exploring the fate of SARs, we found that a total of 81 SARs are subject to alternative splicing, while 14 of them are known Nonsense-Mediated Decay (NMD) targets. Motifs related to GGNGG are enriched both in SARs and near different types of SAS events, suggesting that SR45 recognizes this motif directly. Genes involved in plant defense are significantly over-represented among genes whose expression is suppressed by SR45, and sr45–1 plants do indeed show enhanced immunity.ConclusionWe find that SR45 is a suppressor of innate immunity. We find that a single motif (GGNGG) is highly enriched in both RNAs bound by SR45 and in sequences near SR45- dependent alternative splicing events in inflorescence tissue. We find that the alternative splicing events regulated by SR45 are enriched for this motif whether the effect of SR45 is activation or repression of the particular event. Thus, our data suggests that SR45 acts to control splice site choice in a way that defies simple categorization as an activator or repressor of splicing.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4183-7) contains supplementary material, which is available to authorized users.
An in situ synthesis to form an organic-inorganic hybrid film with tunable optical properties is described. The nanocomposite comprises a titania nanophase that is formed from titanium alkoxide in the presence of a matrix polymer. XPS study indicates that titanium (Ti) in the nanophase is fully oxidized to Ti(IV), similar to that in TiO 2 . When a random copolymer, of styrene and 3-methacryloxypropyltrimethoxysilane (MPTMS), comprising functional groups that form a covalent bond with the in situ synthesized TiO 2 is used, TEM and AFM show no phase contrast between the organic and inorganic phases at the nanometer level. This suggests a molecular level mixing of the polymer and formed inorganics and thus the formation of a molecular composite. This synthesis generates transparent composite films with any level of incorporation of TiO 2 . The refractive indices of these molecular composite films are much higher than that predicted on the basis of effective medium theories; e.g., at a TiO 2 loading of 27 vol %, the resulting molecular composite film exhibits a measured refractive index of 1.76 compared to that of 1.66 predicted by effective medium theories.
The ForceFit program package has been developed for fitting classical force field parameters based upon a force matching algorithm to quantum mechanical gradients of configurations that span the potential energy surface of the system. The program, which runs under UNIX and is written in C++, is an easy-to-use, nonproprietary platform that enables gradient fitting of a wide variety of functional force field forms to quantum mechanical information obtained from an array of common electronic structure codes. All aspects of the fitting process are run from a graphical user interface, from the parsing of quantum mechanical data, assembling of a potential energy surface database, setting the force field, and variables to be optimized, choosing a molecular mechanics code for comparison to the reference data, and finally, the initiation of a least squares minimization algorithm. Furthermore, the code is based on a modular templated code design that enables the facile addition of new functionality to the program.
The recipient vessels are of prime importance in free flap transfers to the lower limbs. To determine the incidence and pattern of vascular trauma, a study was carried out in 126 patients who had Gustillo Type III open fractures of the distal legs and feet that required free flaps for wound coverage. In comparison with the posterior tibial artery, the anterior tibial artery has a much higher incidence of injury with more extensive damage. It can be injured at a more proximal level than estimated from gross inspection during surgery. This should be borne in mind when the anterior tibial artery is selected as the recipient artery in order to prevent reexploration and failure of the flaps. However, the posterior tibial artery is much less vulnerable to damage in most injuries and is more reliable as the recipient artery. In this series there was no problem in finding proper recipient veins in the legs. A general principle is proposed for selecting recipient vessels in crushed legs, with a warning against the pitfalls that have been encountered.
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance Statement This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.
In a two-chamber ultrahigh vacuum system, epitaxial TiO2 thin films have been deposited by metalorganic chemical vapor deposition on single crystal oxide substrates over a temperature range of 250–800 °C, using titanium (IV) isopropoxide as the precursor. During the initial stage of epitaxial film deposition, the growing surface quickly planarized and the film’s orientations was determined by the substrate structure. This substrate influence is manifested in the growth of anatase (the low temperature phase of TiO2) on (001) SrTiO3, at high deposition temperatures (800 °C), whereas on either (0001) or (11̄02) Al2O3 sapphire, epitaxial rutile (the high temperature phase) is formed. In situ Auger electron spectroscopy analyses, before and after growth, revealed a film composition identical to that of a bulk TiO2 standard. No carbon contamination was detected in films grown throughout the deposition temperature range. The decomposition mechanism of this precursor that leads to the absence of incorporated carbon in the deposited film is discussed. X-ray diffraction confirmed the film crystallinity and the structural orientation between the film and substrate. Cross-section transmission electron microscopy showed an abrupt interface between the film and substrate. High tilt angle scanning electron microscopy revealed that the surface of the films became increasingly smooth with increasing growth temperatures. Conditioning the substrate surface at high temperatures in an O2 environment improved the structural quality and surface smoothness of the subsequently deposited films.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.