Cyclic AMP increases the survival of ganglion cells in mixed retinal cell cultures in the absence of exogenous neurotrophic molecules, an effect that involves cholinergic activity

Natural cell death is a well-known degenerative phenomenon occurring during development of the nervous system. The role of trophic molecules produced by target and afferent cells as well as by glial cells has been extensively demonstrated. Literature data demonstrate that cAMP can modulate the survival of neuronal cells. Cultures of mixed retinal cells were treated with forskolin (an activator of the enzyme adenylyl cyclase) for 48 h. The results show that 50 µM forskolin induced a two-fold increase in the survival of retinal ganglion cells (RGCs) in the absence of exogenous trophic factors. This effect was dose dependent and abolished by 1 µM H89 (an inhibitor of protein kinase A), 1.25 µM chelerythrine chloride (an inhibitor of protein kinase C), 50 µM PD 98059 (an inhibitor of MEK), 25 µM Ly 294002 (an inhibitor of phosphatidylinositol-3 kinase), 30 nM brefeldin A (an inhibitor of polypeptide release), and 10 µM genistein or 1 ng/ml herbimycin (inhibitors of tyrosine kinase enzymes). The inhibition of muscarinic receptors by 10 µM atropine or 1 µM telenzepine also blocked the effect of forskolin. When we used 25 µM BAPTA, an intracellular calcium chelator, as well as 20 µM 5-fluoro-2'-deoxyuridine, an inhibitor of cell proliferation, we also abolished the effect. Our results indicate that cAMP plays an important role controlling the survival of RGCs. This effect is directly dependent on M1 receptor activation indicating that cholinergic activity mediates the increase in RGC survival. We propose a model which involves cholinergic amacrine cells and glial cells in the increase of RGC survival elicited by forskolin treatment.

Effect of Sapindus trifoliatus on hyperalgesic in vivo migraine models

Phytotherapies have offered alternative sources of therapy for migraine and gained much importance in prophylactic treatment. Sapindus trifoliatus is a medium-sized deciduous tree growing wild in south India that belongs to the family Sapindaceae. The pericarp is reported for various medicinal properties. A thick aqueous solution of the pericarp is used for the treatment of hemicrania, hysteria or epilepsy in folklore medicine. We have investigated the antihyperalgesic effects of the lyophilized aqueous extract of S. trifoliatus in animal models predictive of experimental migraine models using morphine withdrawal-induced hyperalgesia on the hot-plate test and on 0.3% acetic acid-induced abdominal constrictions in adult male Swiss albino mice. The extract significantly (N = 10, P < 0.05) increased the licking latency in the hot-plate test when administered ip at 10 mg/kg (6.70 ± 0.39 s in saline control vs 18.76 ± 0.96 s in S. trifoliatus-treated animals) and significantly (N = 10, P < 0.001) reduced the abdominal constrictions when administered ip at 2 and 10 mg/kg (40.20 ± 1.36 in saline control vs 30.20 ± 1.33 and 23.00 ± 0.98 for 2 and 10 mg/kg, ip, respectively, in S. trifoliatus-treated animals). Furthermore, when administered ip at 20 and 100 mg/kg, the extract significantly (N = 10, P < 0.05) inhibited the apomorphine-induced climbing behavior in mice (climbing duration 15.75 ± 5.0 min for saline control vs 11.4 ± 1.28 and 3.9 ± 1.71 min for 20 and 100 mg/kg, respectively, in S. trifoliatus-treated animals). In receptor radioligand-binding studies, the extract exhibited affinity towards D2 receptors. The findings suggest that dopamine D2 antagonism could be the mechanism involved in the antihyperalgesic activity of the aqueous extract of S. trifoliatus.

Effect of Erythrina velutina and Erythrina mulungu in rats submitted to animal models of anxiety and depression

Erythrina velutina (EV) and Erythrina mulungu (EM), popularly used in Brazil as tranquilizing agents, were studied. The effects of acute and chronic oral treatment with a water:alcohol extract of EV (7:3, plant grounded stem bark; acute = 100, 200, 400 mg/kg; chronic = 50, 100, 200 mg/kg) were evaluated in rats (N = 11-12) submitted to the elevated T-maze (for avoidance and escape measurements) model of anxiety. This model was selected for its presumed capacity to elicit specific subtypes of anxiety disorders recognized in clinical practice: avoidance has been related to generalized anxiety and escape to panic. Additionally, animals were treated with the same doses of EV and EM (water:alcohol 7:3, inflorescence extract) and submitted to the forced swim test for the evaluation of antidepressant activity (N = 7-10). Both treatment regimens with EV impaired elevated T-maze avoidance latencies, without altering escape, in a way similar to the reference drug diazepam (avoidance 1, mean ± SEM, acute study: 131.1 ± 45.5 (control), 9.0 ± 3.3 (diazepam), 12.7 ± 2.9 (200 mg/kg), 28.8 ± 15.3 (400 mg/kg); chronic study: 131.7 ± 46.9 (control), 35.8 ± 29.7 (diazepam), 24.4 ± 10.4 (50 mg/kg), 29.7 ± 11.5 (200 mg/kg)). Neither EV nor EM altered measurements performed in the forced swim test, in contrast to the reference drug imipramine that significantly decreased immobility time after chronic treatment. These results were not due to motor alterations since no significant effects were detected in an open field. These observations suggest that EV exerts anxiolytic-like effects on a specific subset of defensive behaviors which have been associated with generalized anxiety disorder.

Neuroprotective effect of ketamine/xylazine on two rat models of Parkinson's disease

There is a great concern in the literature for the development of neuroprotectant drugs to treat Parkinson's disease. Since anesthetic drugs have hyperpolarizing properties, they can possibly act as neuroprotectants. In the present study, we have investigated the neuroprotective effect of a mixture of ketamine (85 mg/kg) and xylazine (3 mg/kg) (K/X) on the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) or 6-hydroxydopamine (6-OHDA) rat models of Parkinson's disease. The bilateral infusion of MPTP (100 µg/side) or 6-OHDA (10 µg/side) into the substantia nigra pars compacta of adult male Wistar rats under thiopental anesthesia caused a modest (~67%) or severe (~91%) loss of tyrosine hydroxylase-immunostained cells, respectively. On the other hand, an apparent neuroprotective effect was observed when the rats were anesthetized with K/X, infused 5 min before surgery. This treatment caused loss of only 33% of the nigral tyrosine hydroxylase-immunostained cells due to the MPTP infusion and 51% due to the 6-OHDA infusion. This neuroprotective effect of K/X was also suggested by a less severe reduction of striatal dopamine levels in animals treated with these neurotoxins. In the working memory version of the Morris water maze task, both MPTP- and 6-OHDA-lesioned animals spent nearly 10 s longer to find the hidden platform in the groups where the neurotoxins were infused under thiopental anesthesia, compared to control animals. This amnestic effect was not observed in rats infused with the neurotoxins under K/X anesthesia. These results suggest that drugs with a pharmacological profile similar to that of K/X may be useful to delay the progression of Parkinson's disease.

Raw-appearing Restructured fish models made with Sodium alginate or Microbial transglutaminase and effect of chilled storage

Restructuring by adding Sodium Alginate or Microbial Transglutaminase (MTGase) using cold gelation technology make it possible to obtain many different raw products from minced and/or chopped fish muscle that are suitable for being used as the basis of new restructured products with different physicochemical properties and even different compositions. Special consideration must be given to their shelf-life and the changes that may take place during chilling, both in visual appearance and physicochemical properties. After chilled storage, the restructured models made with different muscular particle size and composition at low temperature (5 °C), it was observed that microbial growth limited the shelf-life to 7-14 days. Mechanical properties increased (p < 0.05) during that time, and higher values were observed in samples elaborated by joining small muscle particle size than in those elaborated by homogenization. There was no clear increase in the cooking yield and purge loss, and no significant colour change (p > 0.05) was detected during storage.

Peroxidase activity and sensory quality of ready to cook mixed vegetables for soup: combined effect of biopreservatives and refrigerated storage

Enzymatic senescence processes and browning of fresh cut vegetables negatively affect their sensory properties and nutritional value and finally result in the rejection of affected products by consumers. In order to prevent quality decay, the combined effects of natural antioxidants and storage temperature on peroxidase activity and sensory attributes (overall visual quality, browning and odor) of individual and mixed vegetables for soup (butternut squash, leek and celery) were evaluated. Fresh cut vegetables were treated with antioxidant solutions as tea tree essential oil (15 μl/mL), propolis extract (15 μl/mL) and gallic acid (2 mg/mL) and stored at optimal (5 °C) and abusive (15 °C) temperature for a maximum of 14 days. The application of natural preservatives, plus optimal storage conditions, exerted significant inhibitory effects in peroxidase activity of squash, celery and mixed vegetables throughout the storage. Furthermore, propolis treatment applied on mixed vegetables retarded browning appearance and preserved the visual quality for a longer period when compared to untreated product.

Effect of loading type on the fatigue strength of symmetric and asymmetric welded joints made of ultra high strength steel

In this study, finite element analyses and experimental tests are carried out in order to investigate the effect of loading type and symmetry on the fatigue strength of three different non-load carrying welded joints. The current codes and recommendations do not give explicit instructions how to consider degree of bending in loading and the effect of symmetry in the fatigue assessment of welded joints. The fatigue assessment is done by using effective notch stress method and linear elastic fracture mechanics. Transverse attachment and cover plate joints are analyzed by using 2D plane strain element models in FEMAP/NxNastran and Franc2D software and longitudinal gusset case is analyzed by using solid element models in Abaqus and Abaqus/XFEM software. By means of the evaluated effective notch stress range and stress intensity factor range, the nominal fatigue strength is assessed. Experimental tests consist of the fatigue tests of transverse attachment joints with total amount of 12 specimens. In the tests, the effect of both loading type and symmetry on the fatigue strength is studied. Finite element analyses showed that the fatigue strength of asymmetric joint is higher in tensile loading and the fatigue strength of symmetric joint is higher in bending loading in terms of nominal and hot spot stress methods. Linear elastic fracture mechanics indicated that bending reduces stress intensity factors when the crack size is relatively large since the normal stress decreases at the crack tip due to the stress gradient. Under tensile loading, experimental tests corresponded with finite element analyzes. Still, the fatigue tested joints subjected to bending showed the bending increased the fatigue strength of non-load carrying welded joints and the fatigue test results did not fully agree with the fatigue assessment. According to the results, it can be concluded that in tensile loading, the symmetry of joint distinctly affects on the fatigue strength. The fatigue life assessment of bending loaded joints is challenging since it depends on whether the crack initiation or propagation is predominant.

Effect of iron on reactivity of vanillin in wine models /

Phenolic compounds are important components of grapes and wines. They have been found to have important roles in grape and wine systems and properties that are beneficial for human health. Vanillin (3-methoxy-4-hydroxybenzaldehyde) is a phenolic compound coming from the oxidative degradation of lignin in oak-barrels during the aging of wine. Vanillin is an important flavour component of wine and its concentration in wine influences significantly the aroma and flavour of wine. The concentration of vanillin in wine is affected by various factors including the presence of metal ions. In this work, by using HPLC, HPLC-MS, and MS technologies, iron (III) cations were found to affect the oxidation of vanillin in a model system of wine, and the product of the oxidation was identified as divanillin. The mechanism of the redox reaction between vanillin and Fe^"^ is thought to follow that of other phenol oxidations. Increasing the concentration of Fe ^ in the model system accelerates divanillin production. The best pH condition for the divanillin production in the system is the range of 3.0 ~ 3.5. Increasing temperature from 20°C to 40°C accelerates the divanillin production. Divanillin was found to exist in three commercial red wines in this work. Keeping the storage temperature cool and decreasing the contact of grapes and wines with iron are two major measures suggested by this work in order to decrease the oxidation of vanillin during the making and aging of wine.

Aggregations and Marginalization of GARCH and Stochastic Volatility Models

The GARCH and Stochastic Volatility paradigms are often brought into conflict as two competitive views of the appropriate conditional variance concept : conditional variance given past values of the same series or conditional variance given a larger past information (including possibly unobservable state variables). The main thesis of this paper is that, since in general the econometrician has no idea about something like a structural level of disaggregation, a well-written volatility model should be specified in such a way that one is always allowed to reduce the information set without invalidating the model. To this respect, the debate between observable past information (in the GARCH spirit) versus unobservable conditioning information (in the state-space spirit) is irrelevant. In this paper, we stress a square-root autoregressive stochastic volatility (SR-SARV) model which remains true to the GARCH paradigm of ARMA dynamics for squared innovations but weakens the GARCH structure in order to obtain required robustness properties with respect to various kinds of aggregation. It is shown that the lack of robustness of the usual GARCH setting is due to two very restrictive assumptions : perfect linear correlation between squared innovations and conditional variance on the one hand and linear relationship between the conditional variance of the future conditional variance and the squared conditional variance on the other hand. By relaxing these assumptions, thanks to a state-space setting, we obtain aggregation results without renouncing to the conditional variance concept (and related leverage effects), as it is the case for the recently suggested weak GARCH model which gets aggregation results by replacing conditional expectations by linear projections on symmetric past innovations. Moreover, unlike the weak GARCH literature, we are able to define multivariate models, including higher order dynamics and risk premiums (in the spirit of GARCH (p,p) and GARCH in mean) and to derive conditional moment restrictions well suited for statistical inference. Finally, we are able to characterize the exact relationships between our SR-SARV models (including higher order dynamics, leverage effect and in-mean effect), usual GARCH models and continuous time stochastic volatility models, so that previous results about aggregation of weak GARCH and continuous time GARCH modeling can be recovered in our framework.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.

Asymptotic Distribution of a Simple Linear Estimator for VARMA Models in Echelon Form

In this paper, we study the asymptotic distribution of a simple two-stage (Hannan-Rissanen-type) linear estimator for stationary invertible vector autoregressive moving average (VARMA) models in the echelon form representation. General conditions for consistency and asymptotic normality are given. A consistent estimator of the asymptotic covariance matrix of the estimator is also provided, so that tests and confidence intervals can easily be constructed.

Factor models, VARMA processes and parameter instability with applications in macroeconomics

Avec les avancements de la technologie de l'information, les données temporelles économiques et financières sont de plus en plus disponibles. Par contre, si les techniques standard de l'analyse des séries temporelles sont utilisées, une grande quantité d'information est accompagnée du problème de dimensionnalité. Puisque la majorité des séries d'intérêt sont hautement corrélées, leur dimension peut être réduite en utilisant l'analyse factorielle. Cette technique est de plus en plus populaire en sciences économiques depuis les années 90. Étant donnée la disponibilité des données et des avancements computationnels, plusieurs nouvelles questions se posent. Quels sont les effets et la transmission des chocs structurels dans un environnement riche en données? Est-ce que l'information contenue dans un grand ensemble d'indicateurs économiques peut aider à mieux identifier les chocs de politique monétaire, à l'égard des problèmes rencontrés dans les applications utilisant des modèles standards? Peut-on identifier les chocs financiers et mesurer leurs effets sur l'économie réelle? Peut-on améliorer la méthode factorielle existante et y incorporer une autre technique de réduction de dimension comme l'analyse VARMA? Est-ce que cela produit de meilleures prévisions des grands agrégats macroéconomiques et aide au niveau de l'analyse par fonctions de réponse impulsionnelles? Finalement, est-ce qu'on peut appliquer l'analyse factorielle au niveau des paramètres aléatoires? Par exemple, est-ce qu'il existe seulement un petit nombre de sources de l'instabilité temporelle des coefficients dans les modèles macroéconomiques empiriques? Ma thèse, en utilisant l'analyse factorielle structurelle et la modélisation VARMA, répond à ces questions à travers cinq articles. Les deux premiers chapitres étudient les effets des chocs monétaire et financier dans un environnement riche en données. Le troisième article propose une nouvelle méthode en combinant les modèles à facteurs et VARMA. Cette approche est appliquée dans le quatrième article pour mesurer les effets des chocs de crédit au Canada. La contribution du dernier chapitre est d'imposer la structure à facteurs sur les paramètres variant dans le temps et de montrer qu'il existe un petit nombre de sources de cette instabilité. Le premier article analyse la transmission de la politique monétaire au Canada en utilisant le modèle vectoriel autorégressif augmenté par facteurs (FAVAR). Les études antérieures basées sur les modèles VAR ont trouvé plusieurs anomalies empiriques suite à un choc de la politique monétaire. Nous estimons le modèle FAVAR en utilisant un grand nombre de séries macroéconomiques mensuelles et trimestrielles. Nous trouvons que l'information contenue dans les facteurs est importante pour bien identifier la transmission de la politique monétaire et elle aide à corriger les anomalies empiriques standards. Finalement, le cadre d'analyse FAVAR permet d'obtenir les fonctions de réponse impulsionnelles pour tous les indicateurs dans l'ensemble de données, produisant ainsi l'analyse la plus complète à ce jour des effets de la politique monétaire au Canada. Motivée par la dernière crise économique, la recherche sur le rôle du secteur financier a repris de l'importance. Dans le deuxième article nous examinons les effets et la propagation des chocs de crédit sur l'économie réelle en utilisant un grand ensemble d'indicateurs économiques et financiers dans le cadre d'un modèle à facteurs structurel. Nous trouvons qu'un choc de crédit augmente immédiatement les diffusions de crédit (credit spreads), diminue la valeur des bons de Trésor et cause une récession. Ces chocs ont un effet important sur des mesures d'activité réelle, indices de prix, indicateurs avancés et financiers. Contrairement aux autres études, notre procédure d'identification du choc structurel ne requiert pas de restrictions temporelles entre facteurs financiers et macroéconomiques. De plus, elle donne une interprétation des facteurs sans restreindre l'estimation de ceux-ci. Dans le troisième article nous étudions la relation entre les représentations VARMA et factorielle des processus vectoriels stochastiques, et proposons une nouvelle classe de modèles VARMA augmentés par facteurs (FAVARMA). Notre point de départ est de constater qu'en général les séries multivariées et facteurs associés ne peuvent simultanément suivre un processus VAR d'ordre fini. Nous montrons que le processus dynamique des facteurs, extraits comme combinaison linéaire des variables observées, est en général un VARMA et non pas un VAR comme c'est supposé ailleurs dans la littérature. Deuxièmement, nous montrons que même si les facteurs suivent un VAR d'ordre fini, cela implique une représentation VARMA pour les séries observées. Alors, nous proposons le cadre d'analyse FAVARMA combinant ces deux méthodes de réduction du nombre de paramètres. Le modèle est appliqué dans deux exercices de prévision en utilisant des données américaines et canadiennes de Boivin, Giannoni et Stevanovic (2010, 2009) respectivement. Les résultats montrent que la partie VARMA aide à mieux prévoir les importants agrégats macroéconomiques relativement aux modèles standards. Finalement, nous estimons les effets de choc monétaire en utilisant les données et le schéma d'identification de Bernanke, Boivin et Eliasz (2005). Notre modèle FAVARMA(2,1) avec six facteurs donne les résultats cohérents et précis des effets et de la transmission monétaire aux États-Unis. Contrairement au modèle FAVAR employé dans l'étude ultérieure où 510 coefficients VAR devaient être estimés, nous produisons les résultats semblables avec seulement 84 paramètres du processus dynamique des facteurs. L'objectif du quatrième article est d'identifier et mesurer les effets des chocs de crédit au Canada dans un environnement riche en données et en utilisant le modèle FAVARMA structurel. Dans le cadre théorique de l'accélérateur financier développé par Bernanke, Gertler et Gilchrist (1999), nous approximons la prime de financement extérieur par les credit spreads. D'un côté, nous trouvons qu'une augmentation non-anticipée de la prime de financement extérieur aux États-Unis génère une récession significative et persistante au Canada, accompagnée d'une hausse immédiate des credit spreads et taux d'intérêt canadiens. La composante commune semble capturer les dimensions importantes des fluctuations cycliques de l'économie canadienne. L'analyse par décomposition de la variance révèle que ce choc de crédit a un effet important sur différents secteurs d'activité réelle, indices de prix, indicateurs avancés et credit spreads. De l'autre côté, une hausse inattendue de la prime canadienne de financement extérieur ne cause pas d'effet significatif au Canada. Nous montrons que les effets des chocs de crédit au Canada sont essentiellement causés par les conditions globales, approximées ici par le marché américain. Finalement, étant donnée la procédure d'identification des chocs structurels, nous trouvons des facteurs interprétables économiquement. Le comportement des agents et de l'environnement économiques peut varier à travers le temps (ex. changements de stratégies de la politique monétaire, volatilité de chocs) induisant de l'instabilité des paramètres dans les modèles en forme réduite. Les modèles à paramètres variant dans le temps (TVP) standards supposent traditionnellement les processus stochastiques indépendants pour tous les TVPs. Dans cet article nous montrons que le nombre de sources de variabilité temporelle des coefficients est probablement très petit, et nous produisons la première évidence empirique connue dans les modèles macroéconomiques empiriques. L'approche Factor-TVP, proposée dans Stevanovic (2010), est appliquée dans le cadre d'un modèle VAR standard avec coefficients aléatoires (TVP-VAR). Nous trouvons qu'un seul facteur explique la majorité de la variabilité des coefficients VAR, tandis que les paramètres de la volatilité des chocs varient d'une façon indépendante. Le facteur commun est positivement corrélé avec le taux de chômage. La même analyse est faite avec les données incluant la récente crise financière. La procédure suggère maintenant deux facteurs et le comportement des coefficients présente un changement important depuis 2007. Finalement, la méthode est appliquée à un modèle TVP-FAVAR. Nous trouvons que seulement 5 facteurs dynamiques gouvernent l'instabilité temporelle dans presque 700 coefficients.