Estrogens and thyroid hormone: Non-genomic effects are coupled to transcription.

Estrogens and thyroid hormones are regulators of important diverse physiological processes such as reproduction, thermogenesis, neural development, neural differentiation and cardiovascular functions. Both are ligands for receptors in the nuclear receptor superfamily, which act as ligand-dependent transcription factors, regulating transcription. However, estrogens and thyroid hormones also rapidly (within minutes or seconds) activate kinase cascades and calcium increases, presumably initiated at the cell membrane. We discuss the relevance of both modes of hormone action, including the membrane estrogen receptor, to physiology, with particular reference to lordosis behavior. We first showed that estrogen restricted to the membrane can, in fact, lead to subsequent increases in transcription from a consensus estrogen response element-based reporter in the neuroblastoma cell line, SK-N-BE(2)C. Using a novel hormonal paradigm, we also showed that the activation of protein kinase A, protein kinase C, mitogen activated protein kinase and increases in calcium were important in the ability of the membrane-limited estrogen to potentiate transcription. We discuss the source of calcium important in transcriptional potentiation. Since estrogens and thyroid hormones have common effects on neuroprotection, cognition and mood, we also hypothesized that crosstalk could occur between the rapid actions of thyroid hormones and the genomic actions of estrogens. In neural cells, we showed that triiodothyronine acting rapidly via MAPK can increase transcription by the nuclear estrogen receptor ERa from a consensus estrogen response element, possibly by the phosphorylation of the ERa. Novel mechanisms that link signals initiated by hormones from the membrane to the nucleus are physiologically relevant and can achieve neuroendocrine integration

Activation of the G-protein coupled receptor 30 (GPR30) has different effects on anxiety in male and female mice

The GPR30, a former orphan GPCR, is a putative membrane estrogen receptor that can activate rapid signaling pathways such as extracellular regulated kinase (ERK) in a variety of cells and may contribute to estrogen's effects in the central nervous system. The distribution of GPR30 in the limbic system predicts a role for this receptor in the regulation of learning and memory and anxiety by estrogens. Though acute G-1 treatment is reported to be anxiogenic in ovariectomised female mice and in gonadally intact male mice, the effect of GPR30 activation is unknown in gonadectomised male mice. In this study, we show that an acute administration of G-1 to gonadectomised male mice, but not female mice, was anxiolytic on an elevated plus maze task, without affecting locomotor activity. In addition, though G-1 treatment did not regulate ERK, it was associated with increased estrogen receptor (ER)alpha phosphorylation in the ventral, but not dorsal, hippocampus of males. In the female, G-1 increased the ERK activation solely in the dorsal hippocampus, independent of state anxiety. This is the first study to report an anxiolytic effect of GPR30 activation in male mice, in a rapid time frame that is commensurate with non-genomic signaling by estrogen.

Activation of G-protein-coupled receptor 30 is sufficient to enhance spatial recognition memory in ovariectomized rats

In ovariectomized rats, administration of estradiol, or selective estrogen receptor agonists that activate either the alpha or beta isoforms, have been shown to enhance spatial cognition on a variety of learning and memory tasks, including those that capitalize on the preference of rats to seek out novelty. Although the effects of the putative estrogen G-protein-coupled receptor 30 (GPR30) on hippocampus-based tasks have been reported using food-motivated tasks, the effects of activation of GPR30 receptors on tasks that depend on the preference of rats to seek out spatial novelty remain to be determined. Therefore, the aim of the current study was to determine if short-term treatment of ovariectomized rats with G-1, an agonist for GPR30, would mimic the effects on spatial recognition memory observed following short-term estradiol treatment. In Experiment 1, ovariectomized rats treated with a low dose (1mug) of estradiol 48h and 24h prior to the information trial of a Y-maze task exhibited a preference for the arm associated with the novel environment on the retention trial conducted 48h later. In Experiment 2, treatment of ovariectomized rats with G-1 (25mug) 48h and 24h prior to the information trial of a Y-maze task resulted in a greater preference for the arm associated with the novel environment on the retention trial. Collectively, the results indicated that short-term treatment of ovariectomized rats with a GPR30 agonist was sufficient to enhance spatial recognition memory, an effect that also occurred following short-term treatment with a low dose of estradiol.

Decadal predictions with the HiGEM high resolution global coupled climate model: description and basic evaluation

This paper describes the development and basic evaluation of decadal predictions produced using the HiGEM coupled climate model. HiGEM is a higher resolution version of the HadGEM1 Met Office Unified Model. The horizontal resolution in HiGEM has been increased to 1.25◦ × 0.83◦ in longitude and latitude for the atmosphere, and 1/3◦ × 1/3◦ globally for the ocean. The HiGEM decadal predictions are initialised using an anomaly assimilation scheme that relaxes anomalies of ocean temperature and salinity to observed anomalies. 10 year hindcasts are produced for 10 start dates (1960, 1965,..., 2000, 2005). To determine the relative contributions to prediction skill from initial conditions and external forcing, the HiGEM decadal predictions are compared to uninitialised HiGEM transient experiments. The HiGEM decadal predictions have substantial skill for predictions of annual mean surface air temperature and 100 m upper ocean temperature. For lead times up to 10 years, anomaly correlations (ACC) over large areas of the North Atlantic Ocean, the Western Pacific Ocean and the Indian Ocean exceed values of 0.6. Initialisation of the HiGEM decadal predictions significantly increases skill over regions of the Atlantic Ocean,the Maritime Continent and regions of the subtropical North and South Pacific Ocean. In particular, HiGEM produces skillful predictions of the North Atlantic subpolar gyre for up to 4 years lead time (with ACC > 0.7), which are significantly larger than the uninitialised HiGEM transient experiments.

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern An- nular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the re- sponse of the Southern Ocean SST (55◦S−70◦S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step re- sponse function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only three years after a step increase in the SAM. This intermodel diversity can be related to differences in the models’ climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use obser- vational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error

Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.

The impact of two coupled cirrus microphysics-radiation parameterizations on the temperature and specific humidity biases in the tropical tropopause layer in a climate model

The impact of two different coupled cirrus microphysics-radiation parameterizations on the zonally averaged temperature and humidity biases in the tropical tropopause layer (TTL) of a Met Office climate model configuration is assessed. One parameterization is based on a linear coupling between a model prognostic variable, the ice mass mixing ratio, qi, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of qi and temperature, Tc, where the mass coefficients (i.e. scattering and extinction) are parameterized as nonlinear functions of the ratio between qi and Tc. The cirrus microphysics parameterization is based on a moment estimation parameterization of the particle size distribution (PSD), which relates the mass moment (i.e. second moment if mass is proportional to size raised to the power of 2 ) of the PSD to all other PSD moments through the magnitude of the second moment and Tc. This same microphysics PSD parameterization is applied to calculate the integral optical properties used in both radiation parameterizations and, thus, ensures PSD and mass consistency between the cirrus microphysics and radiation schemes. In this paper, the temperature-non-dependent and temperature-dependent parameterizations are shown to increase and decrease the zonally averaged temperature biases in the TTL by about 1 K, respectively. The temperature-dependent radiation parameterization is further demonstrated to have a positive impact on the specific humidity biases in the TTL, as well as decreasing the shortwave and longwave biases in the cloudy radiative effect. The temperature-dependent radiation parameterization is shown to be more consistent with TTL and global radiation observations.