Role of complement C5a in mechanical inflammatory hypernociceptio: potential use of C5a receptor antagonists to control inflammatory pain

particularly neutrophil chemoattraction. Herein, the role of C5a in the genesis of inflammatory hypernociception was investigated in rats and mice using the specific C5a receptor antagonist PMX53 (AcF-[OP(D-Cha)WR]). Experimental approach: Mechanical hypernociception was evaluated with a modification of the Randall-Selitto test in rats and electronic pressure meter paw test in mice. Cytokines were measured by ELISA and neutrophil migration was determined by myeloperoxidase activity. Key results: Local pretreatment of rats with PMX53 (60-180 mg per paw) inhibited zymosan-, carrageenan-, lipopolysaccharide (LPS)- and antigen-induced hypernociception. These effects were associated with C5a receptor blockade since PMX53 also inhibited the hypernociception induced by zymosan- activated serum and C5a but not by the direct-acting hypernociceptive mediators, prostaglandin E-2 and dopamine. Underlying the C5a hypernociceptive mechanisms, PMX53 did not alter the cytokine release induced by inflammatory stimuli. However, PMX53 inhibited cytokine-induced hypernociception. PMX53 also inhibited the recruitment of neutrophils induced by zymosan but not by carrageenan or LPS, indicating an involvement of neutrophils in the hypernociceptive effect of C5a. Furthermore, the C5a-induced hypernociception was reduced in neutrophil-depleted rats. Extending these findings in rats, blocking C5a receptors also reduced zymosan- induced joint hypernociception in mice. Conclusions and implications: These results suggest that C5a is an important inflammatory hypernociceptive mediator, acting by a mechanism independent of hypernociceptive cytokine release, but dependent on the presence of neutrophils. Therefore, we suggest that inhibiting the action of C5a has therapeutic potential in the control of inflammatory pain.

Specification and Evaluation of Safety Properties in a Component-Based Software Engineering Process

Over the past years, component-based software engineering has become an established paradigm in the area of complex software intensive systems. However, many techniques for analyzing these systems for critical properties currently do not make use of the component orientation. In particular, safety analysis of component-based systems is an open field of research. In this chapter we investigate the problems arising and define a set of requirements that apply when adapting the analysis of safety properties to a component-based software engineering process. Based on these requirements some important component-oriented safety evaluation approaches are examined and compared.

N-Methyl-D-aspartate glutamate receptors in the hypothalamic paraventricular nucleus modulate cardiac component of the baroreflex in unanesthetized rats

In the present study, we investigated the role played by the hypothalamic paraventricular nucleus (PVN) in the modulation of cardiac baroreflex activity in unanesthetized rats. Bilateral microinjections of the nonselective neurotransmission blocker CoCl(2) into the PVN decreased the reflex bradycardic response evoked by blood pressure increases, but had no effect on reflex tachycardia evoked by blood pressure decreases. Bilateral microinjections of the selective NMDA glutamate receptor antagonist LY235959 into the PVN caused effects that were similar to those observed after microinjections of CoCl(2), decreasing reflex bradycardia without affecting tachycardic response. The microinjection of the selective non-NMDA glutamate receptor antagonist NBQX into the PVN did not affect the baroreflex activity. Also, the microinjection of L-glutamate into the PVN increased the reflex bradycardia, an effect opposed to that observed after PVN treatment with CoCl(2) or LY235959, and this effect of L-glutamate was blocked by PVN pretreatment with LY235959. LY235959 injected into the PVN after iv. treatment with the selective beta(1)-adrenoceptor antagonist atenolol still decreased the reflex bradycardia. Taken together, our results suggest a facilitatory influence of the PVN on the bradycardic response of the baroreflex through activation of local NMDA glutamate receptors and a modulation of the cardiac parasympathetic activity. (C) 2010 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Insular cortex alpha(1)-adrenoceptors modulate the parasympathetic component of the baroreflex in unanesthetized rats

The insular cortex (IC) has been reported to modulate the cardiac parasympathetic activity of the baroreflex in unanesthetized rats. However, which neurotransmitters are involved in this modulation is still unclear. In the present study, we evaluated the possible involvement of local IC-noradrenergic neurotransmission in modulating reflex bradycardiac responses. Bilateral microinjection of the selective alpha(1)-adrenoceptor antagonist WB4101 (15 nmol/100 nL), into the IC of male Wistar rats, increased the gain of reflex bradycardia in response to mean arterial pressure (MAP) increases evoked by intravenous infusion of phenylephrine. However, bilateral microinjection of equimolar doses of either the selective alpha(2)-adrenoceptor antagonist RX821002 or the non-selective beta-adrenoceptor antagonist propranolol into the IC did not affect the baroreflex response. No effects were observed in basal MAP or heart rate values after bilateral microinjection of noradrenergic antagonists into the IC, thus suggesting no tonic influence of IC-noradrenergic neurotransmission on resting cardiovascular parameters. In conclusion, these data provide evidence that local IC-noradrenergic neurotransmission has an inhibitory influence on baroreflex responses to blood pressure increase evoked by phenylephrine infusion through activation of alpha(1)-adrenoceptors. (C) 2009 Elsevier B.V. All rights reserved.

Allelic status of 1p and 19q in oligodendrogliomas and glioblastomas: multiplex ligation-dependent probe amplification versus loss of heterozygosity

Identification of the 1p/19q allelic status in gliomas, primarily those with a major oligodendroglial component, has become an excellent molecular complement to tumor histology in order to identify those cases sensitive to chemotherapy. In addition to loss of heterozygosity (LOH), fluorescence in situ hybridization (FISH), or comparative genomic hybridization (CGH), multiplex ligation-dependent probe amplification (MLPA) has been shown to be an alternative methodology to identify deletions of those chromosome arms. We used MLPA to explore the 1p and 19q glioblastomas, and a series of 76 gliomas: 41 tumors with a major oligodendroglial component, 34 glioblastomas, and one low-grade astrocytoma. We compared the MLPA findings of the oligodendroglial cases with those previously obtained using LOH in the same samples. Thirty-eight of 41 oligodendrogliomas displayed identical findings by both LOH and MLPA, and losses at either 1p and/or 19q were identified in 12 of 35 (34%) astrocytic tumors. These findings agree with data previously reported comparing MLPA versus FISH or CGH in gliomas and suggest that MLPA can be used in the identification 1p/19q allelic deletions on these brain neoplams. (c) 2009 Elsevier Inc. All rights reserved. reserved.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

Design, modelling and analysis of a six component force balance for hypervelocity wind tunnel testing

A combination of modelling and analysis techniques was used to design a six component force balance. The balance was designed specifically for the measurement of impulsive aerodynamic forces and moments characteristic of hypervelocity shock tunnel testing using the stress wave force measurement technique. Aerodynamic modelling was used to estimate the magnitude and distribution of forces and finite element modelling to determine the mechanical response of proposed balance designs. Simulation of balance performance was based on aerodynamic loads and mechanical responses using convolution techniques. Deconvolution was then used to assess balance performance and to guide further design modifications leading to the final balance design. (C) 2001 Elsevier Science Ltd. All rights reserved.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.