Increased opioid dependence in a mouse model of panic disorder

[EN] Panic disorder is a highly prevalent neuropsychiatric disorder that shows co-occurrence with substance abuse. Here, we demonstrate that TrkC, the high-affinity receptor for neurotrophin-3, is a key molecule involved in panic disorder and opiate dependence, using a transgenic mouse model (TgNTRK3). Constitutive TrkC overexpression in TgNTRK3 mice dramatically alters spontaneous firing rates of locus coeruleus (LC) neurons and the response of the noradrenergic system to chronic opiate exposure, possibly related to the altered regulation of neurotrophic peptides observed. Notably, TgNTRK3 LC neurons showed an increased firing rate in saline-treated conditions and profound abnormalities in their response to met5-enkephalin. Behaviorally, chronic morphine administration induced a significantly increased withdrawal syndrome in TgNTRK3 mice. In conclusion, we show here that the NT-3/TrkC system is an important regulator of neuronal firing in LC and could contribute to the adaptations of the noradrenergic system in response to chronic opiate exposure. Moreover, our results indicate that TrkC is involved in the molecular and cellular changes in noradrenergic neurons underlying both panic attacks and opiate dependence and support a functional endogenous opioid deficit in panic disorder patients.

Intranasal Delivery of Plasma and Platelet Growth Factors Using PRGF-Endoret System Enhances Neurogenesis in a Mouse Model of Alzheimer’s Disease

[EN] Neurodegeneration together with a reduction in neurogenesis are cardinal features of Alzheimer’s disease (AD) induced by a combination of toxic amyloid-β peptide (Aβ) and a loss of trophic factor support. Amelioration of these was assessed with diverse neurotrophins in experimental therapeutic approaches. The aim of this study was to investigate whether intranasal delivery of plasma rich in growth factors (PRGF-Endoret), an autologous pool of morphogens and proteins, could enhance hippocampal neurogenesis and reduce neurodegeneration in an amyloid precursor protein/presenilin-1 (APP/PS1) mouse model. Neurotrophic and neuroprotective actions were firstly evident in primary neuronal cultures, where cell proliferation and survival were augmented by Endoret treatment. Translation of these effects in vivo was assessed in wild type and APP/PS1 mice, where neurogenesis was evaluated using 5-bromodeoxyuridine (BdrU), doublecortin (DCX), and NeuN immunostaining 5 weeks after Endoret administration. The number of BrdU, DCX, and NeuN positive cell was increased after chronic treatment. The number of degenerating neurons, detected with fluoro Jade-B staining was reduced in Endoret-treated APP/PS1 mice at 5 week after intranasal administration. In conclusion, Endoret was able to activate neuronal progenitor cells, enhancing hippocampal neurogenesis, and to reduce Aβ-induced neurodegeneration in a mouse model of AD.

An observer-based vaccination control law for an SEIR epidemic model based on feedback linearization techniques for nonlinear systems

This paper presents a vaccination strategy for fighting against the propagation of epidemic diseases. The disease propagation is described by an SEIR (susceptible plus infected plus infectious plus removed populations) epidemic model. The model takes into account the total population amounts as a refrain for the illness transmission since its increase makes the contacts among susceptible and infected more difficult. The vaccination strategy is based on a continuous-time nonlinear control law synthesised via an exact feedback input-output linearization approach. An observer is incorporated into the control scheme to provide online estimates for the susceptible and infected populations in the case when their values are not available from online measurement but they are necessary to implement the control law. The vaccination control is generated based on the information provided by the observer. The control objective is to asymptotically eradicate the infection from the population so that the removed-by-immunity population asymptotically tracks the whole one without precise knowledge of the partial populations. The model positivity, the eradication of the infection under feedback vaccination laws and the stability properties as well as the asymptotic convergence of the estimation errors to zero as time tends to infinity are investigated.

Early astrocytic atrophy in the entorhinal cortex of a triple transgenic animal model of Alzheimer's disease

The EC (entorhinal cortex) is fundamental for cognitive and mnesic functions. Thus damage to this area appears as a key element in the progression of AD (Alzheimer's disease), resulting in memory deficits arising from neuronal and synaptic alterations as well as glial malfunction. In this paper, we have performed an in-depth analysis of astroglial morphology in the EC by measuring the surface and volume of the GFAP (glial fibrillary acidic protein) profiles in a triple transgenic mouse model of AD [3xTg-AD (triple transgenic mice of AD)]. We found significant reduction in both the surface and volume of GFAP-labelled profiles in 3xTg-AD animals from very early ages (1 month) when compared with non-Tg (non-transgenic) controls (48 and 54%, reduction respectively), which was sustained for up to 12 months (33 and 45% reduction respectively). The appearance of Lambda beta (amyloid beta-peptide) depositions at 12 months of age did not trigger astroglial hypertrophy; nor did it result in the close association of astrocytes with senile plaques. Our results suggest that the AD progressive cognitive deterioration can be associated with an early reduction of astrocytic arborization and shrinkage of the astroglial domain, which may affect synaptic connectivity within the EC and between the EC and other brain regions. In addition, the EC seems to be particularly vulnerable to AD pathology because of the absence of evident astrogliosis in response to A beta accumulation. Thus we can consider that targeting astroglial atrophy may represent a therapeutic strategy which might slow down the progression of AD.

Increase in the density of resting microglia precedes neuritic plaque formation and microglial activation in a transgenic model of Alzheimer's disease

The formation of cerebral senile plaques composed of amyloid beta peptide (A beta) is a fundamental feature of Alzheimer's disease (AD). Glial cells and more specifically microglia become reactive in the presence of A beta. In a triple transgenic model of AD (3 x Tg-AD), we found a significant increase in activated microglia at 12 (by 111%) and 18 (by 88%) months of age when compared with non-transgenic (non-Tg) controls. This microglial activation correlated with A beta plaque formation, and the activation in microglia was closely associated with A beta plaques and smaller A beta deposits. We also found a significant increase in the area density of resting microglia in 3 x Tg-AD animals both at plaque-free stage (at 9 months by 105%) and after the development of A plaques (at 12 months by 54% and at 18 months by 131%). Our results show for the first time that the increase in the density of resting microglia precedes both plaque formation and activation of microglia by extracellular A beta accumulation. We suggest that AD pathology triggers a complex microglial reaction: at the initial stages of the disease the number of resting microglia increases, as if in preparation for the ensuing activation in an attempt to fight the extracellular A beta load that is characteristic of the terminal stages of the disease. Cell Death and Disease (2010) 1, e1; doi:10.1038/cddis.2009.2; published online 14 January 2010

A delay model for noise-induced bi-directional switching

Many biological systems can switch between two distinct states. Once switched, the system remains stable for a period of time and may switch back to its original state. A gene network with bistability is usually required for the switching and stochastic effect in the gene expression may induce such switching. A typical bistable system allows one-directional switching, in which the switch from the low state to the high state or from the high state to the low state occurs under different conditions. It is usually difficult to enable bi-directional switching such that the two switches can occur under the same condition. Here, we present a model consisting of standard positive feedback loops and an extra negative feedback loop with a time delay to study its capability to produce bi-directional switching induced by noise. We find that the time delay in the negative feedback is critical for robust bi-directional switching and the length of delay affects its switching frequency.

Multiscale model reduction methods for deterministic and stochastic partial differential equations

Partial differential equations (PDEs) with multiscale coefficients are very difficult to solve due to the wide range of scales in the solutions. In the thesis, we propose some efficient numerical methods for both deterministic and stochastic PDEs based on the model reduction technique.

For the deterministic PDEs, the main purpose of our method is to derive an effective equation for the multiscale problem. An essential ingredient is to decompose the harmonic coordinate into a smooth part and a highly oscillatory part of which the magnitude is small. Such a decomposition plays a key role in our construction of the effective equation. We show that the solution to the effective equation is smooth, and could be resolved on a regular coarse mesh grid. Furthermore, we provide error analysis and show that the solution to the effective equation plus a correction term is close to the original multiscale solution.

For the stochastic PDEs, we propose the model reduction based data-driven stochastic method and multilevel Monte Carlo method. In the multiquery, setting and on the assumption that the ratio of the smallest scale and largest scale is not too small, we propose the multiscale data-driven stochastic method. We construct a data-driven stochastic basis and solve the coupled deterministic PDEs to obtain the solutions. For the tougher problems, we propose the multiscale multilevel Monte Carlo method. We apply the multilevel scheme to the effective equations and assemble the stiffness matrices efficiently on each coarse mesh grid. In both methods, the $\KL$ expansion plays an important role in extracting the main parts of some stochastic quantities.

For both the deterministic and stochastic PDEs, numerical results are presented to demonstrate the accuracy and robustness of the methods. We also show the computational time cost reduction in the numerical examples.

Baryon number violation beyond the standard model

This thesis describes simple extensions of the standard model with new sources of baryon number violation but no proton decay. The motivation for constructing such theories comes from the shortcomings of the standard model to explain the generation of baryon asymmetry in the universe, and from the absence of experimental evidence for proton decay. However, lack of any direct evidence for baryon number violation in general puts strong bounds on the naturalness of some of those models and favors theories with suppressed baryon number violation below the TeV scale. The initial part of the thesis concentrates on investigating models containing new scalars responsible for baryon number breaking. A model with new color sextet scalars is analyzed in more detail. Apart from generating cosmological baryon number, it gives nontrivial predictions for the neutron-antineutron oscillations, the electric dipole moment of the neutron, and neutral meson mixing. The second model discussed in the thesis contains a new scalar leptoquark. Although this model predicts mainly lepton flavor violation and a nonzero electric dipole moment of the electron, it includes, in its original form, baryon number violating nonrenormalizable dimension-five operators triggering proton decay. Imposing an appropriate discrete symmetry forbids such operators. Finally, a supersymmetric model with gauged baryon and lepton numbers is proposed. It provides a natural explanation for proton stability and predicts lepton number violating processes below the supersymmetry breaking scale, which can be tested at the Large Hadron Collider. The dark matter candidate in this model carries baryon number and can be searched for in direct detection experiments as well. The thesis is completed by constructing and briefly discussing a minimal extension of the standard model with gauged baryon, lepton, and flavor symmetries.

A uniform phase representation for the harmonic model in speech synthesis applications

Feature-based vocoders, e.g., STRAIGHT, offer a way to manipulate the perceived characteristics of the speech signal in speech transformation and synthesis. For the harmonic model, which provide excellent perceived quality, features for the amplitude parameters already exist (e.g., Line Spectral Frequencies (LSF), Mel-Frequency Cepstral Coefficients (MFCC)). However, because of the wrapping of the phase parameters, phase features are more difficult to design. To randomize the phase of the harmonic model during synthesis, a voicing feature is commonly used, which distinguishes voiced and unvoiced segments. However, voice production allows smooth transitions between voiced/unvoiced states which makes voicing segmentation sometimes tricky to estimate. In this article, two-phase features are suggested to represent the phase of the harmonic model in a uniform way, without voicing decision. The synthesis quality of the resulting vocoder has been evaluated, using subjective listening tests, in the context of resynthesis, pitch scaling, and Hidden Markov Model (HMM)-based synthesis. The experiments show that the suggested signal model is comparable to STRAIGHT or even better in some scenarios. They also reveal some limitations of the harmonic framework itself in the case of high fundamental frequencies.

In Vitro Surfactant and Perfluorocarbon Aerosol Deposition in a Neonatal Physical Model of the Upper Conducting Airways

Objective: Aerosol delivery holds potential to release surfactant or perfluorocarbon (PFC) to the lungs of neonates with respiratory distress syndrome with minimal airway manipulation. Nevertheless, lung deposition in neonates tends to be very low due to extremely low lung volumes, narrow airways and high respiratory rates. In the present study, the feasibility of enhancing lung deposition by intracorporeal delivery of aerosols was investigated using a physical model of neonatal conducting airways. Methods: The main characteristics of the surfactant and PFC aerosols produced by a nebulization system, including the distal air pressure and air flow rate, liquid flow rate and mass median aerodynamic diameter (MMAD), were measured at different driving pressures (4-7 bar). Then, a three-dimensional model of the upper conducting airways of a neonate was manufactured by rapid prototyping and a deposition study was conducted. Results: The nebulization system produced relatively large amounts of aerosol ranging between 0.3 +/- 0.0 ml/min for surfactant at a driving pressure of 4 bar, and 2.0 +/- 0.1 ml/min for distilled water (H(2)Od) at 6 bar, with MMADs between 2.61 +/- 0.1 mu m for PFD at 7 bar and 10.18 +/- 0.4 mu m for FC-75 at 6 bar. The deposition study showed that for surfactant and H(2)Od aerosols, the highest percentage of the aerosolized mass (similar to 65%) was collected beyond the third generation of branching in the airway model. The use of this delivery system in combination with continuous positive airway pressure set at 5 cmH(2)O only increased total airway pressure by 1.59 cmH(2)O at the highest driving pressure (7 bar). Conclusion: This aerosol generating system has the potential to deliver relatively large amounts of surfactant and PFC beyond the third generation of branching in a neonatal airway model with minimal alteration of pre-set respiratory support.

Self-Organized Criticality, Plasticity and Sensorimotor Coupling. Explorations with a Neurorobotic Model in a Behavioural Preference Task

During the last two decades, analysis of 1/f noise in cognitive science has led to a considerable progress in the way we understand the organization of our mental life. However, there is still a lack of specific models providing explanations of how 1/f noise is generated in coupled brain-body-environment systems, since existing models and experiments typically target either externally observable behaviour or isolated neuronal systems but do not address the interplay between neuronal mechanisms and sensorimotor dynamics. We present a conceptual model of a minimal neurorobotic agent solving a behavioural task that makes it possible to relate mechanistic (neurodynamic) and behavioural levels of description. The model consists of a simulated robot controlled by a network of Kuramoto oscillators with homeostatic plasticity and the ability to develop behavioural preferences mediated by sensorimotor patterns. With only three oscillators, this simple model displays self-organized criticality in the form of robust 1/f noise and a wide multifractal spectrum. We show that the emergence of self-organized criticality and 1/f noise in our model is the result of three simultaneous conditions: a) non-linear interaction dynamics capable of generating stable collective patterns, b) internal plastic mechanisms modulating the sensorimotor flows, and c) strong sensorimotor coupling with the environment that induces transient metastable neurodynamic regimes. We carry out a number of experiments to show that both synaptic plasticity and strong sensorimotor coupling play a necessary role, as constituents of self-organized criticality, in the generation of 1/f noise. The experiments also shown to be useful to test the robustness of 1/f scaling comparing the results of different techniques. We finally discuss the role of conceptual models as mediators between nomothetic and mechanistic models and how they can inform future experimental research where self-organized critically includes sensorimotor coupling among the essential interaction-dominant process giving rise to 1/f noise.

Cytokine pathway disruption in a mouse model of schizophrenia induced by Munc18-1a overexpression in the brain

Background: An accumulating body of evidence points to the significance of neuroinflammation and immunogenetics in schizophrenia, and an imbalance of cytokines in the central nervous system (CNS) has been suggested to be associated with the disorder. Munc18-overexpressing mice (Munc18-OE) have provided a model for the study of the alterations that may underlie the symptoms of subjects with schizophrenia. The aim of the present study was to elucidate the involvement of neuroinflammation and cytokine imbalance in this model. Methods: Cytokines were evaluated in the cortex and the striatum of Munc18-OE and wild-type (WT) mice by enzyme-linked immunosorbent assay (ELISA). Protein levels of specific microglia and macrophage, astrocytic and neuroinflammation markers were quantified by western blot in the cortex and the striatum of Munc18-OE and WT mice. Results: Each cytokine evaluated (Interferon-gamma (IFN-gamma), Tumor Necrosis Factor-alpha (TNF-alpha), Interleukin-2 (IL-2) and CCL2 chemokine) was present at higher levels in the striatum of Munc18-OE mice than WT. Cortical TNF-alpha and IL-2 levels were significantly lower in Munc18-OE mice than WT mice. The microglia and macrophage marker CD11b was lower in the cortexes of Munc18-OE mice than WT, but no differences were observed in the striatum. Glial Fibrillary Acidic Protein (GFAP) and Nuclear Factor-kappaB (NF-kappa B)p65 levels were not different between the groups. Interleukin-1beta (IL-1 beta) and IL-6 levels were beneath detection limits. Conclusions: The disrupted levels of cytokines detected in the brain of Munc18-OE mice was found to be similar to clinical reports and endorses study of this type for analysis of this aspect of the disorder. The lower CD11b expression in the cortex but not in the striatum of the Munc18-OE mice may reflect differences in physiological activity. The cytokine expression pattern observed in Munc18-OE mice is similar to a previously published model of schizophrenia caused by maternal immune activation. Together, these data suggest a possible role for an immune imbalance in this disorder.

Evaluation of Fentanyl Disposition and Effects in Newborn Piglets as an Experimental Model for Human Neonates

Background: Fentanyl is widely used off-label in NICU. Our aim was to investigate its cerebral, cardiovascular and pulmonary effects as well as pharmacokinetics in an experimental model for neonates. Methods: Fentanyl (5 mu g/kg bolus immediately followed by a 90 minute infusion of 3 mu g/kg/h) was administered to six mechanically ventilated newborn piglets. Cardiovascular, ventilation, pulmonary and oxygenation indexes as well as brain activity were monitored from T = 0 up to the end of experiments (T = 225-300 min). Also plasma samples for quantification of fentanyl were drawn. Results: A "reliable degree of sedation" was observed up to T = 210-240 min, consistent with the selected dosing regimen and the observed fentanyl plasma levels. Unlike cardiovascular parameters, which were unmodified except for an increasing trend in heart rate, some of the ventilation and oxygenation indexes as well as brain activity were significantly altered. The pulmonary and brain effects of fentanyl were mostly recovered from T = 210 min to the end of experiment. Conclusion: The newborn piglet was shown to be a suitable experimental model for studying fentanyl disposition as well as respiratory and cardiovascular effects in human neonates. Therefore, it could be extremely useful for further investigating the drug behaviour under pathophysiological conditions.

Brca1 is expressed in human microglia and is dysregulated in human and animal model of ALS

Background: There is growing evidence that microglia are key players in the pathological process of amyotrophic lateral sclerosis (ALS). It is suggested that microglia have a dual role in motoneurone degeneration through the release of both neuroprotective and neurotoxic factors. Results: To identify candidate genes that may be involved in ALS pathology we have analysed at early symptomatic age (P90), the molecular signature of microglia from the lumbar region of the spinal cord of hSOD1(G93A) mice, the most widely used animal model of ALS. We first identified unique hSOD1(G93A) microglia transcriptomic profile that, in addition to more classical processes such as chemotaxis and immune response, pointed toward the potential involvement of the tumour suppressor gene breast cancer susceptibility gene 1 (Brca1). Secondly, comparison with our previous data on hSOD1(G93A) motoneurone gene profile substantiated the putative contribution of Brca1 in ALS. Finally, we established that Brca1 protein is specifically expressed in human spinal microglia and is up-regulated in ALS patients. Conclusions: Overall, our data provide new insights into the pathogenic concept of a non-cell-autonomous disease and the involvement of microglia in ALS. Importantly, the identification of Brca1 as a novel microglial marker and as possible contributor in both human and animal model of ALS may represent a valid therapeutic target. Moreover, our data points toward novel research strategies such as investigating the role of oncogenic proteins in neurodegenerative diseases.