Mathematical modeling of gonadotropin-releasing hormone signaling.

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes to control of reproduction. These are Gq-coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. GnRH is secreted in short pulses and GnRH effects on its target cells are dependent upon the dynamics of these pulses. Here we overview GnRH receptors and their signaling network, placing emphasis on pulsatile signaling, and how mechanistic mathematical models and an information theoretic approach have helped further this field.This work was funded Project Grants from MRC (93447) and the BBSRC (J014699). KTA and MV gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1 and an MRC Biomedical Informatics Fellowship (MR/K021826/1), respectively

Information Transfer via Gonadotropin-Releasing Hormone Receptors to ERK and NFAT: Sensing GnRH and Sensing Dynamics

This is the final version of the article. Available from Oxford University Press via the DOI in this record.Information theoretic approaches can be used to quantify information transfer via cell signaling networks. In this study, we do so for gonadotropin-releasing hormone (GnRH) activation of extracellular signal-regulated kinase (ERK) and nuclear factor of activated T cells (NFAT) in large numbers of individual fixed LβT2 and HeLa cells. Information transfer, measured by mutual information between GnRH and ERK or NFAT, was <1 bit (despite 3-bit system inputs). It was increased by sensing both ERK and NFAT, but the increase was <50%. In live cells, information transfer via GnRH receptors to NFAT was also <1 bit and was increased by consideration of response trajectory, but the increase was <10%. GnRH secretion is pulsatile, so we explored information gained by sensing a second pulse, developing a model of GnRH signaling to NFAT with variability introduced by allowing effectors to fluctuate. Simulations revealed that when cell–cell variability reflects rapidly fluctuating effector levels, additional information is gained by sensing two GnRH pulses, but where it is due to slowly fluctuating effectors, responses in one pulse are predictive of those in another, so little information is gained from sensing both. Wet laboratory experiments revealed that the latter scenario holds true for GnRH signaling; within the timescale of our experiments (1 to 2 hours), cell–cell variability in the NFAT pathway remains relatively constant, so trajectories are reproducible from pulse to pulse. Accordingly, joint sensing, sensing of response trajectories, and sensing of repeated pulses can all increase information transfer via GnRH receptors, but in each case the increase is small.This work was supported by Biochemical and Biophysical Science Research Council Grant BBSRC BB/J014699/1 (to C.A.M. and K.T.-A.). M.V. acknowledges the support of the Medical Research Council (a strategic skills development fellowship in biomedical informatics) and the Engineering and Physical Sciences Research Council via Grant EP/N014391/1

Information Transfer in Gonadotropin-releasing Hormone (GnRH) Signaling: extracellular signal-regulated kinase (ERK)-mediated feedback loops control hormone sensing

The computation model used in the study of GnRH signalling which was used to generate the data appearing in this paper is in ORE at http://hdl.handle.net/10871/27844Cell signaling pathways are noisy communication channels, and statistical measures derived from information theory can be used to quantify the information they transfer. Here we use single cell signaling measures to calculate mutual information as a measure of information transfer via gonadotropin-releasing hormone (GnRH) receptors (GnRHR) to extracellular signal-regulated kinase (ERK) or nuclear factor of activated T-cells (NFAT). This revealed mutual information values <1 bit, implying that individual GnRH-responsive cells cannot unambiguously differentiate even two equally probable input concentrations. Addressing possible mechanisms for mitigation of information loss, we focused on the ERK pathway and developed a stochastic activation model incorporating negative feedback and constitutive activity. Model simulations revealed interplay between fast (min) and slow (min-h) negative feedback loops with maximal information transfer at intermediate feedback levels. Consistent with this, experiments revealed that reducing negative feedback (by expressing catalytically inactive ERK2) and increasing negative feedback (by Egr1-driven expression of dual-specificity phosphatase 5 (DUSP5)) both reduced information transfer from GnRHR to ERK. It was also reduced by blocking protein synthesis (to prevent GnRH from increasing DUSP expression) but did not differ for different GnRHRs that do or do not undergo rapid homologous desensitization. Thus, the first statistical measures of information transfer via these receptors reveals that individual cells are unreliable sensors of GnRH concentration and that this reliability is maximal at intermediate levels of ERK-mediated negative feedback but is not influenced by receptor desensitization.This work was supported by a Biochemical and Biophysical Science Research Council award (BBSRC BB/J014699/1; to C. A. M. and K. T.-A.)

Gonadotropin-releasing hormone signaling: An information theoretic approach

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Gonadotropin-releasing hormone (GnRH) is a peptide hormone that mediates central control of reproduction, acting via G-protein coupled receptors that are primarily Gq coupled and mediate GnRH effects on the synthesis and secretion of luteinizing hormone and follicle-stimulating hormone. A great deal is known about the GnRH receptor signaling network but GnRH is secreted in short pulses and much less is known about how gonadotropes decode this pulsatile signal. Similarly, single cell measures reveal considerable cell-cell heterogeneity in responses to GnRH but the impact of this variability on signaling is largely unknown. Ordinary differential equation-based mathematical models have been used to explore the decoding of pulse dynamics and information theory-derived statistical measures are increasingly used to address the influence of cell-cell variability on the amount of information transferred by signaling pathways. Here, we describe both approaches for GnRH signaling, with emphasis on novel insights gained from the information theoretic approach and on the fundamental question of why GnRH is secreted in pulses.This work was funded Project Grants from MRC (93447) and the BBSRC (J014699). KTA and MV gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1 and an MRC Biomedical Informatics Fellowship (MR/K021826/1), respectively

The importance of perceptual experience in the esthetic appreciation of the body.

Several studies suggest that sociocultural models conveying extreme thinness as the widespread ideal of beauty exert an important influence on the perceptual and emotional representation of body image. The psychological mechanisms underlying such environmental influences, however, are unclear. Here, we utilized a perceptual adaptation paradigm to investigate how perceptual experience modulates body esthetic appreciation. We found that the liking judgments of round bodies increased or decreased after brief exposure to round or thin bodies, respectively. No change occurred in the liking judgments of thin bodies. The results suggest that perceptual experience may shape our esthetic appreciation to favor more familiar round body figures. Importantly, individuals with more deficits in interoceptive awareness were less prone to increase their liking ratings of round bodies after exposure, suggesting a specific risk factor for the susceptibility to the influence of the extreme thin vs. round body ideals of beauty portrayed by the media

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Using GIS to create synthetic disease outbreaks

BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

The Economic Impact of Eradicating Peste des Petits Ruminants:A Benefit-Cost Analysis

Peste des petits ruminants (PPR) is an important cause of mortality and production loss among sheep and goats in the developing world. Despite control efforts in a number of countries, it has continued to spread across Africa and Asia, placing an increasing burden on the livelihoods of livestock keepers and on veterinary resources in affected countries. Given the similarities between PPR and rinderpest, and the lessons learned from the successful global eradication of rinderpest, the eradication of PPR seems appealing, both eliminating an important disease and improving the livelihoods of the poor in developing countries. We conducted a benefit-cost analysis to examine the conomic returns from a proposed programme for the global eradication of PPR. Based on our knowledge and experience, we developed the eradication strategy and estimated its costs. The benefits of the programme were determined from (i) the averted mortality costs, based on an analysis of the literature, (ii) the downstream impact of reduced mortality using a social accounting matrix, and (iii) the avoided control costs based on current levels of vaccination. The results of the benefit-cost analysis suggest strong economic returns from PPR eradication. Based on a 15-year programme with total discounted costs of US$2.26 billion, we estimate discounted benefits of US$76.5 billion, yielding a net benefit of US$74.2 billion. This suggests a benefit cost ratio of 33.8, and an internal rate of return (IRR) of 199%. As PPR mortality rates are highly variable in different populations, we conducted a sensitivity analysis based on lower and higher mortality scenarios. All the scenarios examined indicate that investment in PPR eradication would be highly beneficial economically. Furthermore, removing one of the major constraints to small ruminant production would be of considerable benefit to many of the most vulnerable communities in Africa and Asia