Isolating the signal of ocean global warming

Identifying the signature of global warming in the world's oceans is challenging because low frequency circulation changes can dominate local temperature changes. The IPCC fourth assessment reported an average ocean heating rate of 0.21 ± 0.04 Wm−2 over the period 1961–2003, with considerable spatial, interannual and inter-decadal variability. We present a new analysis of millions of ocean temperature profiles designed to filter out local dynamical changes to give a more consistent view of the underlying warming. Time series of temperature anomaly for all waters warmer than 14°C show large reductions in interannual to inter-decadal variability and a more spatially uniform upper ocean warming trend (0.12 Wm−2 on average) than previous results. This new measure of ocean warming is also more robust to some sources of error in the ocean observing system. Our new analysis provides a useful addition for evaluation of coupled climate models, to the traditional fixed depth analyses.

Thermopile radiometer signal conditioning for surface atmospheric radiation measurements

A highly stable microvolt amplifier for use with atmospheric broadband thermopile radiometers is described. The amplifier has a nominal gain of 500, for bipolar input signals in the range +/- 10 mV from a floating source. The noise level at the input is less than 5 mu V (at 100 k Omega input impedance), permitting instantaneous diffuse solar radiation measurements to 0.5 W m(-2) resolution with 12 bit analog to digital conversion. The temperature stability of gain is better than 5 ppm/degrees C (-4 to 20 degrees C). Averaged over a decade of use, the long term drift of the amplifier gain is less than similar to 0.02%/yr. As well as radiometers measuring solar and terrestrial radiations, the amplifier has also been successfully used with low level signals from thermocouples and ground heat flux plates.

CD40 Triggering of Heterodimeric IL-12 p70 Production by Dendritic Cells In Vivo Requires a Microbial Priming Signal

CD40 ligation triggers IL-12 production by dendritic cells (DC) in vitro. Here, we demonstrate that CD40 cross-linking alone is not sufficient to induce IL-12 production by DC in vivo. Indeed, resting DC make neither the IL-12 p35 nor IL-12 p40 subunits and express only low levels of CD40. Nevertheless, after DC activation by microbial stimuli that primarily upregulate IL-12 p40 and augment CD40 expression, CD40 ligation induces a significant increase in IL-12 p35 and IL-12 p70 heterodimer production. Similarly, IL-12 p70 is produced during T cell activation in the presence but not in the absence of microbial stimuli. Thus, production of bioactive IL-12 by DC can be amplified by T cell–derived signals but must be initiated by innate signals.

Functional significance of the signal transduction pathways Akt and Erk in ovarian follicles: in vitro and in vivo studies in cattle and sheep

BACKGROUND: The intracellular signalling mechanisms that regulate ovarian follicle development are unclear; however, we have recently shown differences in the Akt and Erk signalling pathways in dominant compared to subordinate follicles. The aim of this study was to investigate the effects of inhibiting Akt and Erk phosphorylation on IGF- and gonadotropin- stimulated granulosa and theca cell function in vitro, and on follicle development in vivo. METHODS: Bovine granulosa and theca cells were cultured for six days and stimulated with FSH and/or IGF, or LH in combination with PD98059 (Erk inhibitor) and/or LY294002 (Akt inhibitor) and their effect on cell number and hormone secretion (estradiol, activin-A, inhibin-A, follistatin, progesterone and androstenedione) determined. In addition, ovarian follicles were treated in vivo with PD98059 and/or LY294002 in ewes on Day 3 of the cycle and follicles were recovered 48 hours later. RESULTS: We have shown that gonadotropin- and IGF-stimulated hormone production by granulosa and theca cells is reduced by treatment with PD98059 and LY294002 in vitro. Furthermore, treatment with PD98059 and LY294002 reduced follicle growth and oestradiol production in vivo. CONCLUSION: These results demonstrate an important functional role for the Akt and Erk signalling pathways in follicle function, growth and development.

Mapping the landscape of the lymphocytic choriomeningitis virus stable signal peptide reveals novel functional domains

The stable signal peptide (SSP) of the lymphocytic choriomeningitis virus surface glycoprotein precursor has several unique characteristics. The SSP is unusually long, at 58 amino acids, and contains two hydrophobic domains, and its sequence is highly conserved among both Old and New World arenaviruses. To better understand the functions of the SSP, a panel of point and deletion mutants was created by in vitro mutagenesis to target the highly conserved elements within the SSP. We were also able to confirm critical residues required for separate SSP functions by trans-complementation. Using these approaches, it was possible to resolve functional domains of the SSP. In characterizing our SSP mutants, we discovered that the SSP is involved in several distinct functions within the viral life cycle, beyond translocation of the viral surface glycoprotein precursor into the endoplasmic reticulum lumen. The SSP is required for efficient glycoprotein expression, posttranslational maturation cleavage of GP1 and GP2 by SKI-1/S1P protease, glycoprotein transport to the cell surface plasma membrane, formation of infectious virus particles, and acid pH-dependent glycoprotein-mediated cell fusion.

Delineation and modelling of a nucleolar retention signal in the coronavirus nucleocapsid protein

Unlike nuclear localization signals, there is no obvious consensus sequence for the targeting of proteins to the nucleolus. The nucleolus is a dynamic subnuclear structure which is crucial to the normal operation of the eukaryotic cell. Studying nucleolar trafficking signals is problematic as many nucleolar retention signals (NoRSs) are part of classical nuclear localization signals (NLSs). In addition, there is no known consensus signal with which to inform a study. The avian infectious bronchitis virus (IBV), coronavirus nucleocapsid (N) protein, localizes to the cytoplasm and the nucleolus. Mutagenesis was used to delineate a novel eight amino acid motif that was necessary and sufficient for nucleolar retention of N protein and colocalize with nucleolin and fibrillarin. Additionally, a classical nuclear export signal (NES) functioned to direct N protein to the cytoplasm. Comparison of the coronavirus NoRSs with known cellular and other viral NoRSs revealed that these motifs have conserved arginine residues. Molecular modelling, using the solution structure of severe acute respiratory (SARS) coronavirus N-protein, revealed that this motif is available for interaction with cellular factors which may mediate nucleolar localization. We hypothesise that the N-protein uses these signals to traffic to and from the nucleolus and the cytoplasm.

EMG signal filtering based on Empirical Mode Decomposition

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.