The early transcriptomic response to interleukin 1β and interleukin 33 in rat neonatal cardiomyocytes

In the heart, inflammatory cytokines including interleukin (IL) 1β are implicated in regulating adaptive and maladaptive changes, whereas IL33 negatively regulates cardiomyocyte hypertrophy and promotes cardioprotection. These agonists signal through a common co-receptor but, in cardiomyocytes, IL1β more potently activates mitogen-activated protein kinases and NFκB, pathways that regulate gene expression. We compared the effects of external application of IL1β and IL33 on the cardiomyocyte transcriptome. Neonatal rat cardiomyocytes were exposed to IL1β or IL33 (0.5, 1 or 2h). Transcriptomic profiles were determined using Affymetrix rat genome 230 2.0 microarrays and data were validated by quantitative PCR. IL1β induced significant changes in more RNAs than IL33 and, generally, to a greater degree. It also had a significantly greater effect in downregulating mRNAs and in regulating mRNAs associated with selected pathways. IL33 had a greater effect on a small, select group of specific transcripts. Thus, differences in intensity of intracellular signals can deliver qualitatively different responses. Quantitatively different responses in production of receptor agonists and transcription factors may contribute to qualitative differences at later times resulting in different phenotypic cellular responses.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

Keratinocyte growth factor: a new mesothelial targeted therapy to reduce postoperative pericardial adhesions

Background: Several methods have been utilized to prevent pericardial and retrosternal adhesions, but none of them evaluated the mesothelial regenerative hypothesis. There are evidences that the mesothelial trauma reduces pericardial fibrinolytic capability and induces an adhesion process. Keratinocyte growth factor (KGF) has proven to improve mesothelial cells proliferation. This study investigated the influence of keratinocyte growth factor in reducing post-surgical adhesions. Methods: Twelve pigs were operated and an adhesion protocol was employed. Following a stratified randomization, the animals received a topical application of KGF or saline. At 8 weeks, intrapericardial adhesions were evaluated and a severity score was established. The time spent to dissect the adhesions and the amount of sharp dissection used, were recorded. Histological sections were stained with sirius red and morphometric analyses were assessed with a computer-assisted image analysis system. Results: The severity score was lower in the KGF group than in the control group (11.5 vs 17, p = 0.005). The dissection time was lower in the KGF group (9.2 +/- 1.4 min vs 33.9 +/- 9.2 min, p = 0.004) and presented a significant correlation with the severity score (r = 0.83, p = 0.001). A significantly less sharp dissection was also required in the KGF group. Also, adhesion area and adhesion collagen were significantly tower in the KGF group than in the control group. Conclusion: The simulation of pericardial cells with KGF reduced the intensity of postoperative adhesions and facilitated the re-operation. This study suggests that the mesothelial regeneration is the new horizon in anti-adhesion therapies. (C) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Grain refinement of pure magnesium using rolled Zirmax® master alloy (MG-33.3ZR)

Owing to the limited solubility of zirconium in molten magnesium, almost all of the zirconium contained in the Zirmax® master alloy (Mg-33.3Zr) is present in the form of nearly pure zirconium particles. Of them, zirconium particle clusters and individual zirconium particles greater than 5

Intersections between disability, type of impairment, gender and socio-economic disadvantage in a nationally representative sample of 33,101 working aged Australians

Background:People with disabilities are socio-economically disadvantaged and have poorer health than people without disabilities; however, little is known about the way in which disadvantage is patterned by gender and type of impairment.Objectives:1. To describe whether socio-economic circumstances vary according to type of impairment (sensory and speech, intellectual, physical, psychological and acquired brain injury) 2. To compare levels of socio-economic disadvantage for women and men with the same impairment typeMethods:We used a large population-based disability-focused survey of Australians, analysing data from 33,101 participants aged 25 to 64. Indicators of socio-economic disadvantage included education, income, employment, housing vulnerability, and multiple disadvantage. Stratified by impairment type, we estimated: the population weighted prevalence of socio-economic disadvantage; the relative odds of disadvantage compared to people without disabilities; and the relative odds of disadvantage between women and men.Results:With few exceptions, people with disabilities fared worse for every indicator compared to people without disability; those with intellectual and psychological impairments and acquired brain injuries were most disadvantaged. While overall women with disabilities were more disadvantaged than men, the magnitude of the relative differences was lower than the same comparisons between women and men without disabilities, and there were few differences between women and men with the same impairment types.Conclusions:Crude comparisons between people with and without disabilities obscure how disadvantage is patterned according to impairment type and gender. The results emphasise the need to unpack how gender and disability intersect to shape socio-economic disadvantage.

Analysis of the four wave mixing effect (FWM) in a dispersion decreasing fiber (DDF) for a WDM system

We did a numerical investigation of the propagation of short light pulses in the region of 1.55 mu m and the conversion efficiency (CE) for the four wave mixing generation (FWM) of ordinary and dispersion decreasing fibers for use in wavelength division multiplexing (WDM) systems, Our simulations studies three different profiles, linear, hyperbolic. and constant, One conclude that for all the profiles there is decrease of the conversion efficiency with the increase in the channel separation. The hyperbolic profile present a higher efficiency of around 1000 above in magnitude compared with the others profiles at 0.2 nm of channel separation. We calculate the conversion efficiency versus the fiber length for the three profiles. The conversion efficiency for the hyperbolic profile is higher when compared to the constant and linear profiles. The other interesting point of the hyperbolic profile is that the increase of the CE in the beginning of the fiber does not show my oscillation in the CE value (log eta), which was observed for the constant and linear profiles. For all the profiles there is an increase of the conversion efficiency with the increase of the pump power. The compression factor C-i for the generated FWM signal at omega(3) was measured along the DDF's and the constant profile fibers. One can conclude that with the use of decreasing dispersion profile (DDF) fibers one can have a control of the (CE) conversion efficiency and the compression factor of the four wave mixing (FWM) generation in WDM systems. (c) 2005 Elsevier B.V. All rights reserved.