Volatile flavour profile of goat meat extracted by three widely used techniques

Three procedures for the isolation of volatiles from grilled goat meat were compared: dynamic headspace entrainment on Tenax TA, simultaneous steam distillation-extraction, and solid-phase microextraction. Headspace entrainment on Tenax TA extracted the highest number of Maillard-derived volatile compounds. Two hundred and three volatile components were identified: 159 are reported for the first time in goat meat. Most of the volatiles detected (155) were lipid oxidation products, such as hydrocarbons, aldehydes, alcohols, ketones, carboxylic acids and esters. Forty-eight Maillard-derived compounds were identified. comprising pyrazines, pyrroles, thiophenes, furanthiol derivatives, alkyl and alicyclic sulphides, pyridines, and thiazoles. Some reported character impact compounds of cooked meat, e.g., 12-methyltridecanal, (EE)-2,4-decadienal, methional, and dimethyl trisulphide were identified in the volatile profile of goat meat, together with a series of C-2 to C-5 alkylformylcyclopentenes, which have been reported in cooked chicken, pork, beef and lamb, as being important for the characteristic flavour impression of different animal species. (C) 2009 Published by Elsevier Ltd.

Techniques for quantifying effects of dietary antioxidants on transcription factor translocation and nitric oxide production in cultured cells

Dietary antioxidants can affect cellular processes relevant to chronic inflammatory diseases such as atherosclerosis. We have used non- standard techniques to quantify effects of the antioxidant soy isoflavones genistein and daidzein on translocation of Nuclear Factor-KB (NF-KB) and nitric oxide (NO) production, which are important in these diseases. Translocation was quantified using confocal immunofluoresecence microscopy and ratiometric image analysis. NO was quantified by an electrochemical method after reduction of its oxidation products in cell culture supernatants. Activation of the RAW 264.7 murine monocyte/macrophage cell line increased the ratio of nuclear to cytoplasmic immunostaining for NF-kB. The increase was exacerbated by pre-treatment with genistein or daidzein. To show that decreases could also be detected, pre-treatment with the pine bark extract Pycnogenol (R) r was examined, and found to reduce translocation. NO production was also increased by activation, but was reduced by pre-treatment with genistein or daidzein. In the EA. hy926 human endothelial cell line, constitutive production was detectable and was increased by thrombin. The confocal and electrochemical methods gave data that agreed with results obtained using the established electromobility shift and Griess assays, but were more sensitive, more convenient, gave more detailed information and avoided the use of radioisotopes.

Application of semiquantitative proteomics techniques to the Maillard reaction

Proteomic tools-in particular, mass spectrometry (MS)-have advanced significantly in recent years, and the identification of proteins within complex mixtures is now a routine procedure. Quantitative methods of analysis are less well advanced and continue to develop. These include the use of stable isotope ratio approaches, isotopically labeled peptide standards, and nonlabeling methods. This paper summarizes the use of MS as a proteomics tool to identify and semiquantify proteins and their modified forms by using examples of relevance to the Maillard reaction. Finally, some challenges for the future are presented.

The phytocannabinoid Δ9-tetrahydrocannabivarin modulates inhibitory neurotransmission in the cerebellum

Background and purpose: The phytocannabinoid Delta(9)-tetrahydrocannabivarin (Delta(9)-THCV) has been reported to exhibit a diverse pharmacology; here, we investigate functional effects of Delta(9)-THCV, extracted from Cannabis sativa, using electrophysiological techniques to define its mechanism of action in the CNS. Experimental approach: Effects of Delta(9)-THCV and synthetic cannabinoid agents on inhibitory neurotransmission at interneurone-Purkinje cell (IN-PC) synapses were correlated with effects on spontaneous PC output using single-cell and multi-electrode array (MEA) electrophysiological recordings respectively, in mouse cerebellar brain slices in vitro. Key results: The cannabinoid receptor agonist WIN 55,212-2 (WIN55) decreased miniature inhibitory postsynaptic current (mIPSC) frequency at IN-PC synapses. WIN55-induced inhibition was reversed by Delta(9)-THCV, and also by the CB1 receptor antagonist AM251; Delta(9)-THCV or AM251 acted to increase mIPSC frequency beyond basal values. When applied alone, Delta(9)-THCV, AM251 or rimonabant increased mIPSC frequency. Pre-incubation with Delta(9)-THCV blocked WIN55-induced inhibition. In MEA recordings, WIN55 increased PC spike firing rate; Delta(9)-THCV and AM251 acted in the opposite direction to decrease spike firing. The effects of Delta(9)-THCV and WIN55 were attenuated by the GABA(A) receptor antagonist bicuculline methiodide. Conclusions and implications: We show for the first time that Delta(9)-THCV acts as a functional CB1 receptor antagonist in the CNS to modulate inhibitory neurotransmission at IN-PC synapses and spontaneous PC output. Delta(9)-THCV- and AM251-induced increases in mIPSC frequency beyond basal levels were consistent with basal CB1 receptor activity. WIN55-induced increases in PC spike firing rate were consistent with synaptic disinhibition; whilst Delta(9)-THCV-and AM251-induced decreases in spike firing suggest a mechanism of PC inhibition.

Development of multi-electrode array screening for anticonvulsants in acute rat brain slices

The acute hippocampal brain slice preparation is an important in vitro screening tool for potential anticonvulsants. Application of 4-aminopyridine (4-AP) or removal of external Mg2+ ions induces epileptiform bursting in slices which is analogous to electrical brain activity seen in status epilepticus states. We have developed these epileptiform models for use with multi-electrode arrays (MEAs), allowing recording across the hippocampal slice surface from 59 points. We present validation of this novel approach and analyses using two anticonvulsants, felbamate and phenobarbital, the effects of which have already been assessed in these models using conventional extracellular recordings. In addition to assessing drug effects on commonly described parameters (duration, amplitude and frequency), we describe novel methods using the MEA to assess burst propagation speeds and the underlying frequencies that contribute to the epileptiform activity seen. Contour plots are also used as a method of illustrating burst activity. Finally, we describe hitherto unreported properties of epileptiform, bursting induced by 100 mu M 4-AP or removal of external Mg2+ ions. Specifically, we observed decreases over time in burst amplitude and increase over time in burst frequency in the absence of additional pharmacological interventions. These MEA methods enhance the depth, quality and range of data that can be derived from the hippocampal slice preparation compared to conventional extracellular recordings. it may also uncover additional modes of action that contribute to anti-epileptiform drug effects. (C) 2009 Elsevier B.V. All rights reserved.

Autonomous execution of tasks by swarm carrier agents in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing system? The work reported in this paper is motivated towards bridging this gap by proposing swarm-array computing, a novel technique to achieve autonomy for distributed parallel computing systems. Among three proposed approaches, the second approach, namely 'Intelligent Agents' is of focus in this paper. The task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier. agents and can be seamlessly transferred between cores in the event of a pre-dicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed approach is validated on a multi-agent simulator.

Intelligent agents: are they feasible in swarm-array computing?

The work reported in this paper proposes 'Intelligent Agents', a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

Intelligent cores and intelligent agents: two approaches to achieve autonomy in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.

Building reliable systems for space applications using swarm-array computing

Space applications demand the need for building reliable systems. Autonomic computing defines such reliable systems as self-managing systems. The work reported in this paper combines agent-based and swarm robotic approaches leading to swarm-array computing, a novel technique to achieve self-managing distributed parallel computing systems. Two swarm-array computing approaches based on swarms of computational resources and swarms of tasks are explored. FPGA is considered as the computing system. The feasibility of the two proposed approaches that binds the computing system and the task together is simulated on the SeSAm multi-agent simulator.

Building reliable systems for space applications using swarm-array computing

Space applications demand the need for building reliable systems. Autonomic computing defines such reliable systems as self-managing systems. The work reported in this paper combines agent-based and swarm robotic approaches leading to swarm-array computing, a novel technique to achieve self-managing distributed parallel computing systems. Two swarm-array computing approaches based on swarms of computational resources and swarms of tasks are explored. FPGA is considered as the computing system. The feasibility of the two proposed approaches that binds the computing system and the task together is simulated on the SeSAm multi-agent simulator.