Frequency Domain Estimation of Continuous Time Cointegrated Models with Mixed Frequency and Mixed Sample Data

Recent work by the author on mixed frequency data analysis has focused on the estimation of cointegrated systems in continuous time based on a fully specified dynamic system of equations, while the estimation of cointegrating vectors in a discrete time system has been approached using a semiparametric frequency domain estimator. We extend the latter approach to cover the continuous time case, establishing the asymptotic properties of the frequency domain estimator and explore, in a simulation study, the effects of misspecifying the continuous time dynamic model in discrete time compared to treating the dynamics non‐parametrically. An empirical illustration is also provided

Fluoxetine: a case history of its discovery and preclinical development

Introduction: Depression is a multifactorial mood disorder with a high prevalence worldwide. Until now, treatments for depression have focused on the inhibition of monoaminergic reuptake sites, which augment the bioavailability of monoamines in the CNS. Advances in drug discovery have widened the therapeutic options with the synthesis of so-called selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine. Areas covered: The aim of this case history is to describe and discuss the pharmacokinetic and pharmacodynamic profiles of fluoxetine, including its acute effects and the adaptive changes induced after long-term treatment. Furthermore, the authors review the effect of fluoxetine on neuroplasticity and adult neurogenesis. In addition, the article summarises the preclinical behavioural data available on fluoxetine’s effects on depressive-like behaviour, anxiety and cognition as well as its effects on other diseases. Finally, the article describes the seminal studies validating the antidepressant effects of fluoxetine. Expert opinion: Fluoxetine is the first selective SSRI that has a recognised clinical efficacy and safety profile. Since its discovery, other molecules that mimic its mechanism of action have been developed, commencing a new age in the treatment of depression. Fluoxetine has also demonstrated utility in the treatment of other disorders for which its prescription has now been approved

Slightly Non-Minimal Dark Matter in PAMELA and ATIC

We present a simple model in which dark matter couples to the standard model through a light scalar intermediary that is itself unstable. We find this model has several notable features, and allows a natural explanation for a surplus of positrons, but no surplus of anti-protons, as has been suggested by early data from PAMELA and ATIC. Moreover, this model yields a very small nucleon coupling, well below the direct detection limits. In this paper we explore the effect of this model in both the early universe and in the galaxy.Comment: 7 pages, 6 figures, v3: updated for new data, added discussion of Ferm

Pavlovian Fear Conditioning Activates a Common Pattern of Neurons in the Lateral Amygdala of Individual Brains

Understanding the physical encoding of a memory (the engram) is a fundamental question in neuroscience. Although it has been established that the lateral amygdala is a key site for encoding associative fear memory, it is currently unclear whether the spatial distribution of neurons encoding a given memory is random or stable. Here we used spatial principal components analysis to quantify the topography of activated neurons, in a select region of the lateral amygdala, from rat brains encoding a Pavlovian conditioned fear memory. Our results demonstrate a stable, spatially patterned organization of amygdala neurons are activated during the formation of a Pavlovian conditioned fear memory. We suggest that this stable neuronal assembly constitutes a spatial dimension of the engram

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

Quantitative cross-species extrapolation between humans and fish: The case of the anti-depressant fluoxetine

This article has been made available through the Brunel Open Access Publishing Fund.Fish are an important model for the pharmacological and toxicological characterization of human pharmaceuticals in drug discovery, drug safety assessment and environmental toxicology. However, do fish respond to pharmaceuticals as humans do? To address this question, we provide a novel quantitative cross-species extrapolation approach (qCSE) based on the hypothesis that similar plasma concentrations of pharmaceuticals cause comparable target-mediated effects in both humans and fish at similar level of biological organization (Read-Across Hypothesis). To validate this hypothesis, the behavioural effects of the anti-depressant drug fluoxetine on the fish model fathead minnow (Pimephales promelas) were used as test case. Fish were exposed for 28 days to a range of measured water concentrations of fluoxetine (0.1, 1.0, 8.0, 16, 32, 64 μg/L) to produce plasma concentrations below, equal and above the range of Human Therapeutic Plasma Concentrations (HTPCs). Fluoxetine and its metabolite, norfluoxetine, were quantified in the plasma of individual fish and linked to behavioural anxiety-related endpoints. The minimum drug plasma concentrations that elicited anxiolytic responses in fish were above the upper value of the HTPC range, whereas no effects were observed at plasma concentrations below the HTPCs. In vivo metabolism of fluoxetine in humans and fish was similar, and displayed bi-phasic concentration-dependent kinetics driven by the auto-inhibitory dynamics and saturation of the enzymes that convert fluoxetine into norfluoxetine. The sensitivity of fish to fluoxetine was not so dissimilar from that of patients affected by general anxiety disorders. These results represent the first direct evidence of measured internal dose response effect of a pharmaceutical in fish, hence validating the Read-Across hypothesis applied to fluoxetine. Overall, this study demonstrates that the qCSE approach, anchored to internal drug concentrations, is a powerful tool to guide the assessment of the sensitivity of fish to pharmaceuticals, and strengthens the translational power of the cross-species extrapolation

Decaying into the Hidden Sector

The existence of light hidden sectors is an exciting possibility that may be tested in the near future. If DM is allowed to decay into such a hidden sector through GUT suppressed operators, it can accommodate the recent cosmic ray observations without over-producing antiprotons or interfering with the attractive features of the thermal WIMP. Models of this kind are simple to construct, generic and evade all astrophysical bounds. We provide tools for constructing such models and present several distinct examples. The light hidden spectrum and DM couplings can be probed in the near future, by measuring astrophysical photon and neutrino fluxes. These indirect signatures are complimentary to the direct production signals, such as lepton jets, predicted by these models.Comment: 40 pages, 5 figure

Increased expression of urokinase plasminogen activator and its cognate receptor in human seminomas

<p>Abstract</p> <p>Background</p> <p>The urokinase plasminogen activating system (uPAS) is implicated in neoplastic progression and high tissue levels of uPAS components correlate with a poor prognosis in different human cancers. Despite that, relative few studies are available on the expression and function of the uPAS components in human seminomas. In the present study we characterized the expression of the urokinase plasminogen activator (uPA), its cognate receptor (uPAR) and the uPA inhibitors PAI-1 and PAI-2 in normal human testis and seminomas.</p> <p>Methods</p> <p>The expression of the above genes was evaluated by means of quantitative RT-PCR, western blot, zymographic analysis and immunohistochemistry.</p> <p>Results</p> <p>Quantitative RT-PCR analysis of 14 seminomas demonstrated that uPA and uPAR mRNAs were, with respect to control tissues, increased in tumor tissues by 3.80 ± 0.74 (p < 0.01) and 6.25 ± 1.18 (p < 0.01) fold, respectively. On the other hand, PAI-1 mRNA level was unchanged (1.02 ± 0.24 fold), while that of PAI-2 was significantly reduced to 0.34 ± 0.18 (p < 0.01) fold. Western blot experiments performed with protein extracts of three seminomas and normal tissues from the same patients showed that uPA protein levels were low or undetectable in normal tissues and induced in tumor tissues. On the same samples, zymographic analysis demonstrated increased uPA activity in tumor tissue extracts. Western blot experiments showed that also the uPAR protein was increased in tumor tissues by 1.83 ± 0.15 fold (p < 0.01). The increased expression of uPA and uPAR was further confirmed by immunohistochemical staining performed in 10 seminomas and autologous uninvolved peritumoral tissues. Finally, variation in the mRNA level of PAI-1 significantly correlated with tumor size.</p> <p>Conclusions</p> <p>We demonstrated the increased expression of uPA and uPAR in human seminomas with respect to normal testis tissues, which may be relevant in testicular cancer progression.</p