Interpreting the Evolution of the Size - Luminosity Relation for Disk Galaxies from Redshift 1 to the Present

A sample of very high resolution cosmological disk galaxy simulations is used to investigate the evolution of galaxy disk sizes back to redshift 1 within the Lambda CDM cosmology. Artificial images in the rest frame B band are generated, allowing for a measurement of disk scale lengths using surface brightness profiles as observations would, and avoiding any assumption that light must follow mass as previous models have assumed. We demonstrate that these simulated disks are an excellent match to the observed magnitude - size relation for both local disks, and for disks at z=1 in the magnitude/mass range of overlap. We disentangle the evolution seen in the population as a whole from the evolution of individual disk galaxies. In agreement with observations, our simulated disks undergo roughly 1.5 magnitudes/arcsec^2 of surface brightness dimming since z=1. We find evidence that evolution in the magnitude - size plane varies by mass, such that galaxies with M* > 10^9 M_sun undergo more evolution in size than luminosity, while dwarf galaxies tend to evolve potentially more in luminosity. The disks grow in such a way as to stay on roughly the same stellar mass - size relation with time. Finally, due to an evolving stellar mass - SFR relation, a galaxy at a given stellar mass (or size) at z=1 will reside in a more massive halo and have a higher SFR, and thus a higher luminosity, than a counterpart of the same stellar mass at z=0.Comment: Version resubmitted to ApJ, after referee's comment

Human genomic Z-DNA segments probed by the Zα domain of ADAR1

Double-stranded DNA is a dynamic molecule that adopts different secondary structures. Experimental evidence indicates Z-DNA plays roles in DNA transactions such as transcription, chromatin remodeling and recombination. Furthermore, our computational analysis revealed that sequences with high Z-DNA forming potential at moderate levels of DNA supercoiling are enriched in human promoter regions. However, the actual distribution of Z-DNA segments in genomes of mammalian cells has been elusive due to the unstable nature of Z-DNA and lack of specific probes. Here we present a first human genome map of most stable Z-DNA segments obtained with A549 tumor cells. We used the Z-DNA binding domain, Zα, of the RNA editing enzyme ADAR1 as probe in conjunction with a novel chromatin affinity precipitation strategy. By applying stringent selection criteria, we identified 186 genomic Z-DNA hotspots. Interestingly, 46 hotspots were located in centromeres of 13 human chromosomes. There was a very strong correlation between these hotspots and high densities of single nucleotide polymorphism. Our study indicates that genetic instability and rapid evolution of human centromeres might, at least in part, be driven by Z-DNA segments. Contrary to in silico predictions, however, we found that only two of the 186 hotspots were located in promoter regions

Spatial Stereoresolution for Depth Corrugations May Be Set in Primary Visual Cortex

Stereo “3D” depth perception requires the visual system to extract binocular disparities between the two eyes' images. Several current models of this process, based on the known physiology of primary visual cortex (V1), do this by computing a piecewise-frontoparallel local cross-correlation between the left and right eye's images. The size of the “window” within which detectors examine the local cross-correlation corresponds to the receptive field size of V1 neurons. This basic model has successfully captured many aspects of human depth perception. In particular, it accounts for the low human stereoresolution for sinusoidal depth corrugations, suggesting that the limit on stereoresolution may be set in primary visual cortex. An important feature of the model, reflecting a key property of V1 neurons, is that the initial disparity encoding is performed by detectors tuned to locally uniform patches of disparity. Such detectors respond better to square-wave depth corrugations, since these are locally flat, than to sinusoidal corrugations which are slanted almost everywhere. Consequently, for any given window size, current models predict better performance for square-wave disparity corrugations than for sine-wave corrugations at high amplitudes. We have recently shown that this prediction is not borne out: humans perform no better with square-wave than with sine-wave corrugations, even at high amplitudes. The failure of this prediction raised the question of whether stereoresolution may actually be set at later stages of cortical processing, perhaps involving neurons tuned to disparity slant or curvature. Here we extend the local cross-correlation model to include existing physiological and psychophysical evidence indicating that larger disparities are detected by neurons with larger receptive fields (a size/disparity correlation). We show that this simple modification succeeds in reconciling the model with human results, confirming that stereoresolution for disparity gratings may indeed be limited by the size of receptive fields in primary visual cortex

Short-Lived Trace Gases in the Surface Ocean and the Atmosphere

The two-way exchange of trace gases between the ocean and the atmosphere is important for both the chemistry and physics of the atmosphere and the biogeochemistry of the oceans, including the global cycling of elements. Here we review these exchanges and their importance for a range of gases whose lifetimes are generally short compared to the main greenhouse gases and which are, in most cases, more reactive than them. Gases considered include sulphur and related compounds, organohalogens, non-methane hydrocarbons, ozone, ammonia and related compounds, hydrogen and carbon monoxide. Finally, we stress the interactivity of the system, the importance of process understanding for modeling, the need for more extensive field measurements and their better seasonal coverage, the importance of inter-calibration exercises and finally the need to show the importance of air-sea exchanges for global cycling and how the field fits into the broader context of Earth System Science

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability