Prostaglandin E2 Regulates AMPA Receptor Phosphorylation and Promotes Membrane Insertion in Preoptic Area Neurons and Glia during Sexual Differentiation

Sexual differentiation of the rodent brain is dependent upon the organizing actions of the steroid hormone, estradiol. In the preoptic area, a brain region critical for the expression of adult reproductive behavior, there are twice as many dendritic spine synapses per unit length on newborn male neurons compared to female neurons and this sex difference correlates with the expression of adult male copulatory behavior. The sex difference in the POA is achieved via estradiol's upregulation of the membrane-derived lipid signaling molecule prostaglandin E2 (PGE2); PGE2 is necessary and sufficient to masculinize both dendritic spine density and adult sexual behavior in rats. We have previously shown that PGE2 activates EP2 and EP4 receptors which increases protein kinase A (PKA) activity and that masculinized dendritic spine density and sex behavior are both dependent upon PKA as well as activation of AMPA type glutamate receptors. In the current experiments, we build upon this signaling cascade by determining that PGE2 induces phosphorylation of the AMPA receptor subunit, GluR1, which leads to increased AMPA receptor insertion at the membrane. Treating female pups on the day of birth with PGE2 induced the phosphorylation of GluR1 at the PKA-sensitive site within 2 hours of treatment, an effect that was blocked by co-administration of the PKA/AKAP inhibitor, HT31 with PGE2. Brief treatment of mixed neuronal/glial POA cultures with PGE2 or the cAMP/PKA stimulator, forskolin, increased membrane associated GluR1 in both neurons and glia. We speculate that PGE2 induced increases in AMPA receptor associated with the membrane underlies our previously observed increase in dendritic spine density and is a critical component in the masculinization of rodent sex behavior

Testing matter effects in propagation of atmospheric and long-baseline neutrinos

We quantify our current knowledge of the size and flavor structure of the matter effects in the evolution of atmospheric and long-baseline neutrinos based solely on the analysis of the corresponding neutrino data. To this aim we generalize the matter potential of the Standard Model by rescaling its strength, rotating it away from the e-e sector, and rephasing it with respect to the vacuum term. This phenomenological parametrization can be easily translated in terms of non-standard neutrino interactions in matter. We show that in the most general case, the strength of the potential cannot be determined solely by atmospheric and long-baseline data. However its flavor composition is very much constrained and the present determination of the neutrino masses and mixing is robust under its presence. We also present an update of the constraints arising from this analysis in the particular case in which no potential is present in the e-mu and e-tau sectors. Finally we quantify to what degree in this scenario it is possible to alleviate the tension between the oscillation results for neutrinos and antineutrinos in the MINOS experiment and show the relevance of the high energy part of the spectrum measured at MINOS.Comment: PDFLaTeX file using JHEP3 class, 25 pages, 7 figures included. Accepted for publication in JHE

Non-CO2 generating energy shares in the world : cross-country differences and polarization.

The aim of this paper is to examine the spatial distribution of non-CO2 generating energy sources in the world for the period 1990–2009, paying special attention to the evolution of cross-country disparities. To this end, after carrying out a classical convergence analysis, a more thorough investigation of the entire distribution is presented by examining its external shape, the intra-distribution dynamics and the long-run equilibrium distribution. This analysis reveals the existence of a weak, rather insignificant, convergence process and that large crosscountry differences are likely to persist in the long-run. Next, as polarization indicators are a proper way of appraising potential conflict in international environmental negotiations, we test whether, or not, the distribution dynamics concurs with the presence of polarization. Our results indicate that two poles can be clearly differentiated, one with high and other with low non-CO2 generating energy shares. In view of these findings, and to ensure a fair transition to a sustainable energy system, the paper calls for the development of an ambitious clean energy agenda, especially in countries with low non-CO2 generating energy shares

Surrogate markers and survival in women receiving first-line combination anthracycline chemotherapy for advanced breast cancer

Surrogate markers may help predict the effects of first-line treatment on survival. This metaregression analysis examines the relationship between several surrogate markers and survival in women with advanced breast cancer after receiving first-line combination anthracycline chemotherapy 5-fluorouracil, adriamycin and cyclophosphamide (FAC) or 5-fluorouracil, epirubicin and cyclophosphamide (FEC) . From a systematic literature review, we identified 42 randomised trials. The surrogate markers were complete or partial tumour response, progressive disease and time to progression. The treatment effect on survival was quantified by the hazard ratio. The treatment effect on each surrogate marker was quantified by the odds ratio (or ratio of median time to progression). The relationship between survival and each surrogate marker was assessed by a weighted linear regression of the hazard ratio against the odds ratio. There was a significant linear association between survival and complete or partial tumour response (P<0.001, R2=34%), complete tumour response (P=0.02, R2=12%), progressive disease (P<0.001, R2=38%) and time to progression (P<0.0001, R2=56%); R2 is the proportion of the variability in the treatment effect on survival that is explained by the treatment effect on the surrogate marker. Time to progression may be a useful surrogate marker for predicting survival in women receiving first-line anthracycline chemotherapy and could be used to estimate the survival benefit in future trials of first-line chemotherapy compared to FAC or FEC. The other markers, tumour response and progressive disease, were less good

Computational classifiers for predicting the short-term course of Multiple sclerosis

The aim of this study was to assess the diagnostic accuracy (sensitivity and specificity) of clinical, imaging and motor evoked potentials (MEP) for predicting the short-term prognosis of multiple sclerosis (MS). METHODS: We obtained clinical data, MRI and MEP from a prospective cohort of 51 patients and 20 matched controls followed for two years. Clinical end-points recorded were: 1) expanded disability status scale (EDSS), 2) disability progression, and 3) new relapses. We constructed computational classifiers (Bayesian, random decision-trees, simple logistic-linear regression-and neural networks) and calculated their accuracy by means of a 10-fold cross-validation method. We also validated our findings with a second cohort of 96 MS patients from a second center. RESULTS: We found that disability at baseline, grey matter volume and MEP were the variables that better correlated with clinical end-points, although their diagnostic accuracy was low. However, classifiers combining the most informative variables, namely baseline disability (EDSS), MRI lesion load and central motor conduction time (CMCT), were much more accurate in predicting future disability. Using the most informative variables (especially EDSS and CMCT) we developed a neural network (NNet) that attained a good performance for predicting the EDSS change. The predictive ability of the neural network was validated in an independent cohort obtaining similar accuracy (80%) for predicting the change in the EDSS two years later. CONCLUSIONS: The usefulness of clinical variables for predicting the course of MS on an individual basis is limited, despite being associated with the disease course. By training a NNet with the most informative variables we achieved a good accuracy for predicting short-term disability

Multidimensional prognostic indices for use in COPD patient care. A systematic review

Contains fulltext : 98117.pdf (publisher's version ) (Open Access)BACKGROUND: A growing number of prognostic indices for chronic obstructive pulmonary disease (COPD) is developed for clinical use. Our aim is to identify, summarize and compare all published prognostic COPD indices, and to discuss their performance, usefulness and implementation in daily practice. METHODS: We performed a systematic literature search in both Pubmed and Embase up to September 2010. Selection criteria included primary publications of indices developed for stable COPD patients, that predict future outcome by a multidimensional scoring system, developed for and validated with COPD patients only. Two reviewers independently assessed the index quality using a structured screening form for systematically scoring prognostic studies. RESULTS: Of 7,028 articles screened, 13 studies comprising 15 indices were included. Only 1 index had been explored for its application in daily practice. We observed 21 different predictors and 7 prognostic outcomes, the latter reflecting mortality, hospitalization and exacerbation. Consistent strong predictors were FEV1 percentage predicted, age and dyspnoea. The quality of the studies underlying the indices varied between fairly poor and good. Statistical methods to assess the predictive abilities of the indices were heterogenic. They generally revealed moderate to good discrimination, when measured. Limitations: We focused on prognostic indices for stable disease only and, inevitably, quality judgment was prone to subjectivity. CONCLUSIONS: We identified 15 prognostic COPD indices. Although the prognostic performance of some of the indices has been validated, they all lack sufficient evidence for implementation. Whether or not the use of prognostic indices improves COPD disease management or patients' health is currently unknown; impact studies are required to establish this

Prognostic molecular markers in early breast cancer

A multitude of molecules involved in breast cancer biology have been studied as potential prognostic markers. In the present review we discuss the role of established molecular markers, as well as potential applications of emerging new technologies. Those molecules used routinely to make treatment decisions in patients with early-stage breast cancer include markers of proliferation (e.g. Ki-67), hormone receptors, and the human epidermal growth factor receptor 2. Tumor markers shown to have prognostic value but not used routinely include cyclin D(1 )and cyclin E, urokinase-like plasminogen activator/plasminogen activator inhibitor, and cathepsin D. The level of evidence for other molecular markers is lower, in part because most studies were retrospective and not adequately powered, making their findings unsuitable for choosing treatments for individual patients. Gene microarrays have been successfuly used to classify breast cancers into subtypes with specific gene expression profiles and to evaluate prognosis. RT-PCR has also been used to evaluate expression of multiple genes in archival tissue. Proteomics technologies are in development

Fitting the Elementary Rate Constants of the P-gp Transporter Network in the hMDR1-MDCK Confluent Cell Monolayer Using a Particle Swarm Algorithm

P-glycoprotein, a human multidrug resistance transporter, has been extensively studied due to its importance to human health and disease. In order to understand transport kinetics via P-gp, confluent cell monolayers overexpressing P-gp are widely used. The purpose of this study is to obtain the mass action elementary rate constants for P-gp's transport and to functionally characterize members of P-gp's network, i.e., other transporters that transport P-gp substrates in hMDR1-MDCKII confluent cell monolayers and are essential to the net substrate flux. Transport of a range of concentrations of amprenavir, loperamide, quinidine and digoxin across the confluent monolayer of cells was measured in both directions, apical to basolateral and basolateral to apical. We developed a global optimization algorithm using the Particle Swarm method that can simultaneously fit all datasets to yield accurate and exhaustive fits of these elementary rate constants. The statistical sensitivity of the fitted values was determined by using 24 identical replicate fits, yielding simple averages and standard deviations for all of the kinetic parameters, including the efflux active P-gp surface density. Digoxin required additional basolateral and apical transporters, while loperamide required just a basolateral tranporter. The data were better fit by assuming bidirectional transporters, rather than active importers, suggesting that they are not MRP or active OATP transporters. The P-gp efflux rate constants for quinidine and digoxin were about 3-fold smaller than reported ATP hydrolysis rate constants from P-gp proteoliposomes. This suggests a roughly 3∶1 stoichiometry between ATP hydrolysis and P-gp transport for these two drugs. The fitted values of the elementary rate constants for these P-gp substrates support the hypotheses that the selective pressures on P-gp are to maintain a broad substrate range and to keep xenobiotics out of the cytosol, but not out of the apical membrane