Reconstruction of in vivo time-evolving neuroendocrine dose - response properties unveils admixed deterministic and stochastic elements

Homeostasis in the intact organism is achieved implicitly by repeated incremental feedback (inhibitory) and feedforward (stimulatory) adjustments enforced via intermittent signal exchange. In separated systems, neurohormone signals act deterministically on target cells via quantifiable effector-response functions. On the other hand, in vivo interglandular signaling dynamics have not been estimable to date. Indeed, experimentally isolating components of an interactive network definitionally disrupts time-sensitive linkages. We implement and validate analytical reconstruction of endogenous effector-response properties via a composite model comprising (i) a deterministic basic feedback and feedforward ensemble structure; (ii) judicious statistical allowance for possible stochastic variability in individual biologically interpretable dose–response properties; and (iii) the sole data requirement of serially observed concentrations of a paired signal (input) and response (output). Application of this analytical strategy to a prototypical neuroendocrine axis in the conscious uninjected horse, sheep, and human (i) illustrates probabilistic estimation of endogenous effector dose–response properties; and (ii) unmasks statistically vivid (2- to 5-fold) random fluctuations in inferred target-gland responsivity within any given pulse train. In conclusion, balanced mathematical formalism allows one to (i) reconstruct deterministic properties of interglandular signaling in the intact mammal and (ii) quantify apparent signal-response variability over short time scales in vivo. The present proof-of-principle experiments introduce a previously undescribed means to estimate time-evolving signal-response relationships without isotope infusion or pathway disruption.

Retinal sensitivity loss in third-generation n-3 PUFA-deficient rats

A previous study conducted in guinea pigs suggested that ingestion of diets high in EPA and DHA may result in suboptimal retinal function. The aim of the present study was to evaluate retinal function in pigmented (Long-Evans) rats, raised to a third generation on diets that were either deficient in n-3 PUFA or adequate (with the addition of DHA). Electroretinographic assessment employed full-field white flash stimulation. Photoreceptor responses were evaluated in terms of peak amplitudes and implicit times (a-wave, b-wave), intensity-response functions (Naka-Rushton), and the parameters of a model of transduction (P3). Retinal phospholipid FA composition was measured by capillary GLC. DHA levels were reduced by 55% in n-3-deficient animals compared with the n-3-adequate group, whereas the levels of docosapentaenoic acid n-6 were 44 times higher in n-3-deficient animals. The level of arachidonic acid was marginally higher (12.8%) in n-6-adequate animals. The n-3-deficient animals exhibited significantly reduced retinal sensitivity (σ and S values were both affected by 0.29 log units) and increased b-wave implicit times compared with those fed the n-3-adequate diet. These data suggest that n-3 PUFA are required for development of retinal sensitivity, more so than other indices of retinal function assessed by current methods, such as maximal response amplitude. However, the benefit for retinal function of adding preformed DHA to diets already replete in n-3 PUFA remains unclear.

Female labour force participation, fertility and infant mortality in Australia : some empirical evidence from Granger causality tests

This study applies Granger causality tests within a multivariate error correction framework to examine the relationship between female participation rates, infant mortality rates and fertility rates for Australia using annual data from 1960 to 2000. Decomposition of variance and impulse response functions are also considered. The main findings are twofold. First, in the short run there is unidirectional Granger causality running from the fertility rate to female labour force participation and from the infant mortality rate to female labour force participation while there is neutrality between the fertility rate and infant mortality rate. Second, in the long run both the fertility rate and infant mortality rate Granger cause female labour participation.

Temporal causality and the dynamics of judicial appellate caseload, real income and socio-economic complexity in Australia

This study applies Granger causality tests within a multivariate error correction framework to examine the relationship between judicial caseload, real income and urbanization for Australia using annual data from 1904 to 2001. Decomposition of variance and impulse response functions are also considered. The Granger causality results as well as the decomposition of variance and impulse response functions suggest that urbanization is the most exogenous of the three variables in both the long run and short run while judicial caseload and real income are relatively exogenous in the short run.

Higher education, real income and real investment in China : evidence from Granger causality tests

This paper employs cointegration and error-correction modelling to test the causal relationship between real income, real investment and tertiary education using data for the People's Republic of China over the period 1952-1999. To proxy tertiary education we use higher education enrolments and higher education graduates in alternative empirical specifications. One of the paper's main findings is that real income, real investment and tertiary education are cointegrated when real investment is the dependent variable, but are not cointegrated when either tertiary education or real income is the dependent variable. We also extend the in-sample analysis to examine the decomposition of variance and impulse response functions.

Temporal causality and the dynamics of democracy, emigration and real income in Fiji

This study is the first to explore temporal causality between democracy, emigration and real income in Fiji within a multivariate cointegration model. We find three long run relationships between democracy, emigration and real income. In the long run there is evidence that migration and democracy Granger cause real GDP in Fiji; real GDP and democracy Granger cause migration from Fiji and that real GDP and migration Granger cause democracy in Fiji. In the short run we find unidirectional Granger causality running from migration to real GDP and from democracy to real GDP, but neutrality between democracy and migration in the short run. We also extend the analysis to examine the degree of exogeneity of the variables beyond the sample period through considering the decomposition of variance and impulse response functions.

A factor-augmented VAR approach : the effect of a rise in the US personal income tax rate on the US and Canada

In this paper a factor-augmented vector autoregressive (FAVAR) model is estimated to characterize the dynamic effects of shocks in the personal income tax rate in the United States on United States and Canadian economies. The representation and the estimate of the FAVAR model is based on Stock and Watson (2005) and the shocks are recovered applying the identification scheme proposed by Bernanke et al. (2005); this method allows impulse response functions to be generated for all the variables in the dataset and provides a description of the domestic and international transmission mechanisms of United States movements in the personal income tax rate. A distinguishing feature of our model is the disaggregation of traded goods sector where imports and exports are disaggregated into 12 and 13 industries, respectively. This provides extra information on the domestic and international transmission mechanism across the two countries. The results show that the FAVAR approach generates a reasonable characterisation of the effects of United States movements in the US personal income tax rate on the United States economy and its transmission to the Canadian economy.

Ripple effects of house prices : considering spatial correlations in geography and demography

Purpose: Studies into ripple effects have previously focused on the interconnections between house price movements across cities over space and time. These interconnections were widely investigated in previous research using vector autoregression models. However, the effects generated from spatial information could not be captured by conventional vector autoregression models. This research aimed to incorporate spatial lags into a vector autoregression model to illustrate spatial-temporal interconnections between house price movements across the Australian capital cities. Design/methodology/approach: Geographic and demographic correlations were captured by assessing geographic distances and demographic structures between each pair of cities, respectively. Development scales of the housing market were also used to adjust spatial weights. Impulse response functions based on the estimated SpVAR model were further carried out to illustrate the ripple effects. Findings: The results confirmed spatial correlations exist in housing price dynamics in the Australian capital cities. The spatial correlations are dependent more on the geographic rather than the demographic information. Originality/value: This research investigated the spatial heterogeneity and autocorrelations of regional house prices within the context of demographic and geographic information. A spatial vector autoregression model was developed based on the demographic and geographic distance. The temporal and spatial effects on house prices in Australian capital cities were then depicted.

A panel error correction approach to explore spatial correlation patterns of the dominant housing market in Australian capital cities

Purpose - A panel error correction model has been developed to investigate the spatial correlation patterns among house prices. This paper aims to identify a dominant housing market in the ripple down process. Design/methodology/approach - Seemingly unrelated regression estimators are adapted to deal with the contemporary correlations and heterogeneity across cities. Impulse response functions are subsequently implemented to simulate the spatial correlation patterns. The newly developed approach is then applied to the Australian capital city house price indices. Findings - The results suggest that Melbourne should be recognised as the dominant housing market. Four levels were classified within the Australian house price interconnections, namely: Melbourne; Adelaide, Canberra, Perth and Sydney; Brisbane and Hobart; and Darwin. Originality/value - This research develops a panel regression framework in addressing the spatial correlation patterns of house prices across cities. The ripple-down process of house price dynamics across cities was explored by capturing both the contemporary correlations and heterogeneity, and by identifying the dominant housing market.

Does oil price volatility matter for Asian emerging economies?

This article investigates the impact of oil price volatility on six major emerging economies in Asia using time-series cross-section and time-series econometric techniques. To assess the robustness of the findings, we further implement such heterogeneous panel data estimation methods as Mean Group (MG), Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators to allow for cross-sectional dependence. The empirical results reveal that oil price volatility has a detrimental effect on these emerging economies. In the short run, oil price volatility influenced output growth in China and affected both GDP growth and inflation in India. In the Philippines, oil price volatility impacted on inflation, but in Indonesia, it impacted on both GDP growth and inflation before and after the Asian financial crisis. In Malaysia, oil price volatility impacted on GDP growth, although there is notably little feedback from the opposite side. For Thailand, oil price volatility influenced output growth prior to the Asian financial crisis, but the impact disappeared after the crisis. It appears that oil subsidization by the Thai Government via introduction of the oil fund played a significant role in improving the economic performance by lessening the adverse effects of oil price volatility on macroeconomic indicators.

Energy consumption and income in six Asian developing countries: a multivariate cointegration analysis

 This article examines the short- and long-run causal relationship between energy consumption and GDP of six emerging economies of Asia. Based on cointegration and vector error correction modeling the empirical results show that there exists unidirectional short- and long-run causality running from energy consumption to GDP for China, uni-directional short-run causality from output to energy consumption for India, whilst bi-directional short-run causality for Thailand. Neutrality between energy consumption and income is found for Indonesia, Malaysia and Philippines. Both the generalized variance decompositions and impulse response functions confirm the direction of causality. These findings have important policy implications for the countries concerned. The results suggest that while India may directly initiate energy conservation measures, China and Thailand may opt for a balanced combination of alternative polices.

Thresholds, incidence functions, and species-specific cues : responses of woodland birds to landscape structure in south-eastern Australia

Looking out from a vantage point across a large tract of forest gives a superficial impression of uniformity: the crowns of canopy trees follow the folds and contours of the landscape to provide a continuous cover of wooded vegetation. But this visual appearance belies the truth: forested landscapes are far from uniform. On closer examination, they comprise a complex mosaic of different vegetation types and and stands of different age-classes, differing structural features, and modified to a varying extent by human land-uses. Forests have a critical role in the conservation of biodiversity throughout the world (Peterken 1996; Laurance and Bierregard 1997; Lindenmayer and Franklin 2002) and a key feature contributing to their conservation value is the response of forest biota to the heterogeneity inherent in forested landscapes (Lindenmayer et al. 2006). Consequently, an understanding of the implications of landscape structure for the maintainance of species and ecological processes is an important foundation for forest management and biodiversity conservation.

An antiviral response directed by PKR phosphorylation of the RNA helicase A

The double-stranded RNA-activated protein kinase R (PKR) is a key regulator of the innate immune response. Activation of PKR during viral infection culminates in phosphorylation of the α subunit of the eukaryotic translation initiation factor 2 (eIF2α) to inhibit protein translation. A broad range of regulatory functions has also been attributed to PKR. However, as few additional PKR substrates have been identified, the mechanisms remain unclear. Here, PKR is shown to interact with an essential RNA helicase, RHA. Moreover, RHA is identified as a substrate for PKR, with phosphorylation perturbing the association of the helicase with double-stranded RNA (dsRNA). Through this mechanism, PKR can modulate transcription, as revealed by its ability to prevent the capacity of RHA to catalyze transactivating response (TAR)–mediated type 1 human immunodeficiency virus (HIV-1) gene regulation. Consequently, HIV-1 virions packaged in cells also expressing the decoy RHA peptides subsequently had enhanced infectivity. The data demonstrate interplay between key components of dsRNA metabolism, both connecting RHA to an important component of innate immunity and delineating an unanticipated role for PKR in RNA metabolism.