A Turnover in the Galaxy Main Sequence of Star Formation at M∗∼1010M⊙M_{*} \sim 10^{10} M_{\odot} for Redshifts z<1.3z < 1.3

The relationship between galaxy star formation rates (SFR) and stellar masses ($M_\ast$) is re-examined using a mass-selected sample of $\sim$62,000 star-forming galaxies at $z \le 1.3$ in the COSMOS 2-deg$^2$ field. Using new far-infrared photometry from $Herschel$-PACS and SPIRE and $Spitzer$-MIPS 24 $\mu$m, along with derived infrared luminosities from the NRK method based on galaxies' locations in the restframe color-color diagram $(NUV - r)$ vs. $(r - K)$, we are able to more accurately determine total SFRs for our complete sample. At all redshifts, the relationship between median $SFR$ and $M_\ast$ follows a power-law at low stellar masses, and flattens to nearly constant SFR at high stellar masses. We describe a new parameterization that provides the best fit to the main sequence and characterizes the low mass power-law slope, turnover mass, and overall scaling. The turnover in the main sequence occurs at a characteristic mass of about $M_{0} \sim 10^{10} M_{\odot}$ at all redshifts. The low mass power-law slope ranges from 0.9-1.3 and the overall scaling rises in SFR as a function of $(1+z)^{4.12 \pm 0.10}$. A broken power-law fit below and above the turnover mass gives relationships of $SFR \propto M_{*}^{0.88 \pm 0.06}$ below the turnover mass and $SFR \propto M_{*}^{0.27 \pm 0.04}$ above the turnover mass. Galaxies more massive than $M_\ast \gtrsim 10^{10}\ M_{\rm \odot}$ have on average, a much lower specific star formation rate (sSFR) than would be expected by simply extrapolating the traditional linear fit to the main sequence found for less massive galaxies.Comment: 16 pages, 7 figures. Accepted for publication in Ap

Cilostazol for Secondary Stroke Prevention: History, Evidence, Limitations, and Possibilities

Cilostazol is a phosphodiesterase III inhibitor with a long track record of safety that is FDA and EMA approved for the treatment of claudication in patients with peripheral arterial disease. In addition, cilostazol has been approved for secondary stroke prevention in several Asian countries based on trials that have demonstrated a reduction in stroke recurrence among patients with non-cardioembolic stroke. The onset of benefit appears after 60–90 days of treatment, which is consistent with cilostazol’s pleiotropic effects on platelet aggregation, vascular remodeling, blood flow, and plasma lipids. Cilostazol appears safe and does not increase the risk of major bleeding when given alone or in combination with aspirin or clopidogrel. Adverse effects such as headache, gastrointestinal symptoms and palpitations, however, contributed to a 6% increase in drug discontinuation among patients randomized to cilostazol in a large secondary stroke prevention trial (CSPS.com). Due to limitations of prior trials, such as open label design, premature trial termination, large loss to follow-up, lack of functional or cognitive outcome data, and exclusive enrollment in Asia, the existing trials have not led to a change in clinical practice or guidelines in Western countries. These limitations could be addressed by a double-blind placebo-controlled randomized trial conducted in a broader population. If positive, it would increase the evidence in support of long-term treatment with cilostazol for secondary prevention in the millions of patients worldwide who have suffered a non-cardioembolic ischemic stroke

Galaxy Zoo: The Environmental Dependence of Bars and Bulges in Disc Galaxies

We present an analysis of the environmental dependence of bars and bulges in disc galaxies, using a volume-limited catalogue of 15810 galaxies at z<0.06 from the Sloan Digital Sky Survey with visual morphologies from the Galaxy Zoo 2 project. We find that the likelihood of having a bar, or bulge, in disc galaxies increases when the galaxies have redder (optical) colours and larger stellar masses, and observe a transition in the bar and bulge likelihoods, such that massive disc galaxies are more likely to host bars and bulges. We use galaxy clustering methods to demonstrate statistically significant environmental correlations of barred, and bulge-dominated, galaxies, from projected separations of 150 kpc/h to 3 Mpc/h. These environmental correlations appear to be independent of each other: i.e., bulge-dominated disc galaxies exhibit a significant bar-environment correlation, and barred disc galaxies show a bulge-environment correlation. We demonstrate that approximately half (50 +/- 10%) of the bar-environment correlation can be explained by the fact that more massive dark matter haloes host redder disc galaxies, which are then more likely to have bars. Likewise, we show that the environmental dependence of stellar mass can only explain a small fraction (25 +/- 10%) of the bar-environment correlation. Therefore, a significant fraction of our observed environmental dependence of barred galaxies is not due to colour or stellar mass dependences, and hence could be due to another galaxy property. Finally, by analyzing the projected clustering of barred and unbarred disc galaxies with halo occupation models, we argue that barred galaxies are in slightly higher-mass haloes than unbarred ones, and some of them (approximately 25%) are satellite galaxies in groups. We also discuss implications about the effects of minor mergers and interactions on bar formation.Comment: 20 pages, 18 figures; references updated; published in MNRA

Galaxy Zoo: CANDELS barred discs and bar fractions

The formation of bars in disc galaxies is a tracer of the dynamical maturity of the population. Previous studies have found that the incidence of bars in discs decreases from the local Universe to z ~ 1, and by z > 1 simulations predict that bar features in dynamically mature discs should be extremely rare. Here, we report the discovery of strong barred structures in massive disc galaxies at z ~ 1.5 in deep rest-frame optical images from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey. From within a sample of 876 disc galaxies identified by visual classification in Galaxy Zoo, we identify 123 barred galaxies. Selecting a subsample within the same region of the evolving galaxy luminosity function (brighter than L*), we find that the bar fraction across the redshift range 0.5 ≤ z ≤ 2 (fbar = 10.7+6.3 -3.5 per cent after correcting for incompleteness) does not significantly evolve.We discuss the implications of this discovery in the context of existing simulations and our current understanding of the way disc galaxies have evolved over the last 11 billion yearsPeer reviewedFinal Accepted Versio

Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI

Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH ($\rho$=.85) and hippocampal volumes (r=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg

Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI

Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated segmentation and quantification is desirable but existing methods require high-resolution MRI with good signal-to-noise ratio (SNR). This precludes application to clinical and low-field portable MRI (pMRI) scans, thus hampering large-scale tracking of atrophy and WMH progression, especially in underserved areas where pMRI has huge potential. Here we present a method that segments white matter hyperintensity and 36 brain regions from scans of any resolution and contrast (including pMRI) without retraining. We show results on eight public datasets and on a private dataset with paired high- and low-field scans (3T and 64mT), where we attain strong correlation between the WMH ($\rho$=.85) and hippocampal volumes (r=.89) estimated at both fields. Our method is publicly available as part of FreeSurfer, at: http://surfer.nmr.mgh.harvard.edu/fswiki/WMH-SynthSeg

Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people

BackgroundPortable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in low-resource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people.MethodsT1- and T2-weighted structural MR images were obtained from a low-field (64mT) Hyperfine and high-field (3T) Siemens system in N = 70 individuals (mean age = 20.39 years, range 9–26 years). We tested two super-resolution approaches to improve image correspondence between images acquired at high- and low-field: (1) processing via a convolutional neural network (‘SynthSR’), and (2) multi-orientation image averaging. We extracted brain region volumes, cortical thickness, and cortical surface area estimates. We used Pearson correlations to test the correspondence between these measures, and Steiger Z tests to compare the difference in correspondence between standard imaging and super-resolution approaches.ResultsSingle pairs of T1- and T2-weighted images acquired at low field showed high correspondence to high-field-strength images for estimates of total intracranial volume, surface area cortical volume, subcortical volume, and total brain volume (r range = 0.60–0.88). Correspondence was lower for cerebral white matter volume (r = 0.32, p = 0.007, q = 0.009) and non-significant for mean cortical thickness (r = −0.05, p = 0.664, q = 0.664). Processing images with SynthSR yielded significant improvements in correspondence for total brain volume, white matter volume, total surface area, subcortical volume, cortical volume, and total intracranial volume (r range = 0.85–0.97), with the exception of global mean cortical thickness (r = 0.14). An alternative multi-orientation image averaging approach improved correspondence for cerebral white matter and total brain volume. Processing with SynthSR also significantly improved correspondence across widespread regions for estimates of cortical volume, surface area and subcortical volume, as well as within isolated prefrontal and temporal regions for estimates of cortical thickness.ConclusionApplying super-resolution approaches to low-field imaging improves regional brain volume and surface area accuracy in young people. Finer-scale brain measurements, such as cortical thickness, remain challenging with the limited resolution of low-field systems