116 research outputs found
Spinors, Inflation, and Non-Singular Cyclic Cosmologies
We consider toy cosmological models in which a classical, homogeneous, spinor
field provides a dominant or sub-dominant contribution to the energy-momentum
tensor of a flat Friedmann-Robertson-Walker universe. We find that, if such a
field were to exist, appropriate choices of the spinor self-interaction would
generate a rich variety of behaviors, quite different from their widely studied
scalar field counterparts. We first discuss solutions that incorporate a stage
of cosmic inflation and estimate the primordial spectrum of density
perturbations seeded during such a stage. Inflation driven by a spinor field
turns out to be unappealing as it leads to a blue spectrum of perturbations and
requires considerable fine-tuning of parameters. We next find that, for simple,
quartic spinor self-interactions, non-singular cyclic cosmologies exist with
reasonable parameter choices. These solutions might eventually be incorporated
into a successful past- and future-eternal cosmological model free of
singularities. In an Appendix, we discuss the classical treatment of spinors
and argue that certain quantum systems might be approximated in terms of such
fields.Comment: 12 two-column pages, 3 figures; uses RevTeX
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Fluorinated Adenosine A2A Receptor Antagonists Inspired by Preladenant as Potential Cancer Immunotherapeutics
Antagonism of the adenosine A2A receptor on T cells blocks the hypoxia-adenosinergic pathway to promote tumor rejection. Using an in vivo immunoassay based on the Concanavalin A mouse model, a series of A2A antagonists were studied and identified preladenant as a potent lead compound for development. Molecular modeling was employed to assist drug design and subsequent synthesis of analogs and those of tozadenant, including fluorinated polyethylene glycol PEGylated derivatives. The efficacy of the analogs was evaluated using two in vitro functional bioassays, and compound 29, a fluorinated triethylene glycol derivative of preladenant, was confirmed as a potential immunotherapeutic agent
Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects
Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects
Detection of microRNA Expression in Human Peripheral Blood Microvesicles
MicroRNAs (miRNA) are small non-coding RNAs that regulate translation of mRNA and protein. Loss or enhanced expression of miRNAs is associated with several diseases, including cancer. However, the identification of circulating miRNA in healthy donors is not well characterized. Microvesicles, also known as exosomes or microparticles, circulate in the peripheral blood and can stimulate cellular signaling. In this study, we hypothesized that under normal healthy conditions, microvesicles contain miRNAs, contributing to biological homeostasis.Microvesicles were isolated from the plasma of normal healthy individuals. RNA was isolated from both the microvesicles and matched mononuclear cells and profiled for 420 known mature miRNAs by real-time PCR. Hierarchical clustering of the data sets indicated significant differences in miRNA expression between peripheral blood mononuclear cells (PBMC) and plasma microvesicles. We observed 71 miRNAs co-expressed between microvesicles and PBMC. Notably, we found 33 and 4 significantly differentially expressed miRNAs in the plasma microvesicles and mononuclear cells, respectively. Prediction of the gene targets and associated biological pathways regulated by the detected miRNAs was performed. The majority of the miRNAs expressed in the microvesicles from the blood were predicted to regulate cellular differentiation of blood cells and metabolic pathways. Interestingly, a select few miRNAs were also predicted to be important modulators of immune function.This study is the first to identify and define miRNA expression in circulating plasma microvesicles of normal subjects. The data generated from this study provides a basis for future studies to determine the predictive role of peripheral blood miRNA signatures in human disease and will enable the definition of the biological processes regulated by these miRNA
Endovascular strategy or open repair for ruptured abdominal aortic aneurysm: one-year outcomes from the IMPROVE randomized trial.
AIMS: To report the longer term outcomes following either a strategy of endovascular repair first or open repair of ruptured abdominal aortic aneurysm, which are necessary for both patient and clinical decision-making. METHODS AND RESULTS: This pragmatic multicentre (29 UK and 1 Canada) trial randomized 613 patients with a clinical diagnosis of ruptured aneurysm; 316 to an endovascular first strategy (if aortic morphology is suitable, open repair if not) and 297 to open repair. The principal 1-year outcome was mortality; secondary outcomes were re-interventions, hospital discharge, health-related quality-of-life (QoL) (EQ-5D), costs, Quality-Adjusted-Life-Years (QALYs), and cost-effectiveness [incremental net benefit (INB)]. At 1 year, all-cause mortality was 41.1% for the endovascular strategy group and 45.1% for the open repair group, odds ratio 0.85 [95% confidence interval (CI) 0.62, 1.17], P = 0.325, with similar re-intervention rates in each group. The endovascular strategy group and open repair groups had average total hospital stays of 17 and 26 days, respectively, P < 0.001. Patients surviving rupture had higher average EQ-5D utility scores in the endovascular strategy vs. open repair groups, mean differences 0.087 (95% CI 0.017, 0.158), 0.068 (95% CI -0.004, 0.140) at 3 and 12 months, respectively. There were indications that QALYs were higher and costs lower for the endovascular first strategy, combining to give an INB of £3877 (95% CI £253, £7408) or €4356 (95% CI €284, €8323). CONCLUSION: An endovascular first strategy for management of ruptured aneurysms does not offer a survival benefit over 1 year but offers patients faster discharge with better QoL and is cost-effective. CLINICAL TRIAL REGISTRATION: ISRCTN 48334791
Low exposure long-baseline neutrino oscillation sensitivity of the DUNE experiment
The Deep Underground Neutrino Experiment (DUNE) will produce world-leading
neutrino oscillation measurements over the lifetime of the experiment. In this
work, we explore DUNE's sensitivity to observe charge-parity violation (CPV) in
the neutrino sector, and to resolve the mass ordering, for exposures of up to
100 kiloton-megawatt-years (kt-MW-yr). The analysis includes detailed
uncertainties on the flux prediction, the neutrino interaction model, and
detector effects. We demonstrate that DUNE will be able to unambiguously
resolve the neutrino mass ordering at a 3 (5) level, with a 66
(100) kt-MW-yr far detector exposure, and has the ability to make strong
statements at significantly shorter exposures depending on the true value of
other oscillation parameters. We also show that DUNE has the potential to make
a robust measurement of CPV at a 3 level with a 100 kt-MW-yr exposure
for the maximally CP-violating values \delta_{\rm CP}} = \pm\pi/2.
Additionally, the dependence of DUNE's sensitivity on the exposure taken in
neutrino-enhanced and antineutrino-enhanced running is discussed. An equal
fraction of exposure taken in each beam mode is found to be close to optimal
when considered over the entire space of interest
A Gaseous Argon-Based Near Detector to Enhance the Physics Capabilities of DUNE
This document presents the concept and physics case for a magnetized gaseous argon-based detector system (ND-GAr) for the Deep Underground Neutrino Experiment (DUNE) Near Detector. This detector system is required in order for DUNE to reach its full physics potential in the measurement of CP violation and in delivering precision measurements of oscillation parameters. In addition to its critical role in the long-baseline oscillation program, ND-GAr will extend the overall physics program of DUNE. The LBNF high-intensity proton beam will provide a large flux of neutrinos that is sampled by ND-GAr, enabling DUNE to discover new particles and search for new interactions and symmetries beyond those predicted in the Standard Model
Snowmass Neutrino Frontier: DUNE Physics Summary
The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment with a primary physics goal of observing neutrino and antineutrino oscillation patterns to precisely measure the parameters governing long-baseline neutrino oscillation in a single experiment, and to test the three-flavor paradigm. DUNE's design has been developed by a large, international collaboration of scientists and engineers to have unique capability to measure neutrino oscillation as a function of energy in a broadband beam, to resolve degeneracy among oscillation parameters, and to control systematic uncertainty using the exquisite imaging capability of massive LArTPC far detector modules and an argon-based near detector. DUNE's neutrino oscillation measurements will unambiguously resolve the neutrino mass ordering and provide the sensitivity to discover CP violation in neutrinos for a wide range of possible values of δCP. DUNE is also uniquely sensitive to electron neutrinos from a galactic supernova burst, and to a broad range of physics beyond the Standard Model (BSM), including nucleon decays. DUNE is anticipated to begin collecting physics data with Phase I, an initial experiment configuration consisting of two far detector modules and a minimal suite of near detector components, with a 1.2 MW proton beam. To realize its extensive, world-leading physics potential requires the full scope of DUNE be completed in Phase II. The three Phase II upgrades are all necessary to achieve DUNE's physics goals: (1) addition of far detector modules three and four for a total FD fiducial mass of at least 40 kt, (2) upgrade of the proton beam power from 1.2 MW to 2.4 MW, and (3) replacement of the near detector's temporary muon spectrometer with a magnetized, high-pressure gaseous argon TPC and calorimeter
Snowmass Neutrino Frontier: DUNE Physics Summary
The Deep Underground Neutrino Experiment (DUNE) is a next-generation
long-baseline neutrino oscillation experiment with a primary physics goal of
observing neutrino and antineutrino oscillation patterns to precisely measure
the parameters governing long-baseline neutrino oscillation in a single
experiment, and to test the three-flavor paradigm. DUNE's design has been
developed by a large, international collaboration of scientists and engineers
to have unique capability to measure neutrino oscillation as a function of
energy in a broadband beam, to resolve degeneracy among oscillation parameters,
and to control systematic uncertainty using the exquisite imaging capability of
massive LArTPC far detector modules and an argon-based near detector. DUNE's
neutrino oscillation measurements will unambiguously resolve the neutrino mass
ordering and provide the sensitivity to discover CP violation in neutrinos for
a wide range of possible values of . DUNE is also uniquely
sensitive to electron neutrinos from a galactic supernova burst, and to a broad
range of physics beyond the Standard Model (BSM), including nucleon decays.
DUNE is anticipated to begin collecting physics data with Phase I, an initial
experiment configuration consisting of two far detector modules and a minimal
suite of near detector components, with a 1.2 MW proton beam. To realize its
extensive, world-leading physics potential requires the full scope of DUNE be
completed in Phase II. The three Phase II upgrades are all necessary to achieve
DUNE's physics goals: (1) addition of far detector modules three and four for a
total FD fiducial mass of at least 40 kt, (2) upgrade of the proton beam power
from 1.2 MW to 2.4 MW, and (3) replacement of the near detector's temporary
muon spectrometer with a magnetized, high-pressure gaseous argon TPC and
calorimeter.Comment: Contribution to Snowmass 202
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