16 research outputs found
The dependence of galaxy clustering on stellar mass, star-formation rate and redshift at z = 0.8–2.2, with HiZELS
The deep, near-infrared narrow-band survey HiZELS has yielded robust samples of H α-emitting star-forming galaxies within narrow redshift slices at z = 0.8,  1.47 and 2.23. In this paper, we distinguish the stellar mass and star-formation rate (SFR) dependence of the clustering of these galaxies. At high stellar masses (M*/M⊙ ≳ 2 × 1010), where HiZELS selects galaxies close to the so-called star-forming main sequence, the clustering strength is observed to increase strongly with stellar mass (in line with the results of previous studies of mass-selected galaxy samples) and also with SFR. These two dependencies are shown to hold independently. At lower stellar masses, however, where HiZELS probes high specific SFR galaxies, there is little or no dependence of the clustering strength on stellar mass, but the dependence on SFR remains: high-SFR low-mass galaxies are found in more massive dark matter haloes than their lower SFR counterparts. We argue that this is due to environmentally driven star formation in these systems. We apply the same selection criteria to the EAGLE cosmological hydrodynamical simulations. We find that, in EAGLE, the high-SFR low-mass galaxies are central galaxies in more massive dark matter haloes, in which the high SFRs are driven by a (halo-driven) increased gas content
The H α luminosity-dependent clustering of star-forming galaxies from z ∼ 0.8 to ∼2.2 with HiZELS
We present clustering analyses of identically selected star-forming galaxies in three narrow redshift slices (at z = 0.8, 1.47 and 2.23), from the High-Redshift(Z) Emission Line Survey (HiZELS), a deep, near-infrared narrow-band survey. The HiZELS samples span the peak in the cosmic star formation rate density, identifying typical star-forming galaxies at each epoch. Narrow-band samples have well-defined redshift distributions and are therefore ideal for clustering analyses. We quantify the clustering of the three samples, and of H α luminosity-selected subsamples, initially using simple power-law fits to the two-point correlation function. We extend this work to link the evolution of star-forming galaxies and their host dark matter haloes over cosmic time using sophisticated dark matter halo models. We find that the clustering strength, r0, and the bias of galaxy populations relative to the clustering of dark matter increase linearly with H α luminosity (and, by implication, star formation rate) at all three redshifts, as do the host dark matter halo masses of the HiZELS galaxies. The typical galaxies in our samples are star-forming centrals, residing in haloes of mass Mhalo ∼ a few times 1012 M⊙. We find a remarkably tight redshift-independent relation between the H α luminosity scaled by the characteristic luminosity, LHα/L∗Hα(z) LHα/LHα∗(z) , and the minimum host dark matter halo mass of central galaxies. This reveals that the dark matter halo environment is a strong driver of galaxy star formation rate and therefore of the evolution of the star formation rate density in the Universe
The clustering of Hα emitters at z = 2.23 from HiZELS
We present a clustering analysis of 370 high-confidence Hα emitters (HAEs) at z = 2.23. The HAEs are detected in the Hi-Z Emission Line Survey (HiZELS), a large-area blank field 2.121 μm narrow-band survey using the United Kingdom Infrared Telescope Wide Field Camera (WFCAM). Averaging the two-point correlation function of HAEs in two ˜1° scale fields [United Kingdom Infrared Deep Sky Survey/Ultra Deep Survey (UDS) and Cosmological Evolution Survey (COSMOS) fields] we find a clustering amplitude equivalent to a correlation length of r0 = 3.7 ± 0.3 h-1 Mpc for galaxies with star formation rates of ≳7 M⊙ yr-1. The data are also well-fitted by the expected correlation function of cold dark matter (CDM), scaled by a bias factor: ωHAE = b2ωDM where b=2.4-0.2+0.1. The corresponding 'characteristic' mass for the haloes hosting HAEs is log (Mh/[h-1 M⊙]) = 11.7 ± 0.1. Comparing to the latest semi-analytic GALFORM predictions for the evolution of HAEs in a ΛCDM cosmology, we find broad agreement with the observations, with GALFORM predicting an HAE correlation length of ˜4 h-1 Mpc. Motivated by this agreement, we exploit the simulations to construct a parametric model of the halo occupation distribution (HOD) of HAEs, and use this to fit the observed clustering. Our best-fitting HOD can adequately reproduce the observed angular clustering of HAEs, yielding an effective halo mass and bias in agreement with that derived from the scaled ωDM fit, but with the relatively small sample size the current data provide a poor constraint on the HOD. However, we argue that this approach provides interesting hints into the nature of the relationship between star-forming galaxies and the matter field, including insights into the efficiency of star formation in massive haloes. Our results support the broad picture that 'typical' (≲L★) star-forming galaxies have been hosted by dark matter haloes with Mh ≲ 1012 h-1 M⊙ since z ≈ 2, but with a broad occupation distribution and clustering that is likely to be a strong function of luminosity
Inhibition of protein kinase CbetaII increases glucose uptake in 3T3-L1 adipocytes through elevated expression of glucose transporter 1 at the plasma membrane.
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143690.pdf (Publisher’s version ) (Closed access)The mechanism via which diacylglycerol-sensitive protein kinase Cs (PKCs) stimulate glucose transport in insulin-sensitive tissues is poorly defined. Phorbol esters, such as phorbol-12-myristate-13-acetate (PMA), are potent activators of conventional and novel PKCs. Addition of PMA increases the rate of glucose uptake in many different cell systems. We attempted to investigate the mechanism via which PMA stimulates glucose transport in 3T3-L1 adipocytes in more detail. We observed a good correlation between the rate of disappearance of PKCbetaII during prolonged PMA treatment and the increase in glucose uptake. Moreover, inhibition of PKCbetaII with a specific myristoylated PKCbetaC2-4 peptide inhibitor significantly increased the rate of glucose transport. Western blot analysis demonstrated that both PMA treatment and incubation with the myristoylated PKCbetaC2-4 pseudosubstrate resulted in more glucose transporter (GLUT)-1 but not GLUT-4 at the plasma membrane. To our knowledge, we are the first to demonstrate that inactivation of PKC, most likely PKCbetaII, elevates glucose uptake in 3T3-L1 adipocytes. The observation that PKCbetaII influences the rate of glucose uptake through manipulation of GLUT-1 expression levels at the plasma membrane might reveal a yet unidentified regulatory mechanism involved in glucose homeostasis