Adaptive evolution of MRGX2, a human sensory neuron specific gene involved in nociception

MRGX2, a G-protein-coupled receptor, is specifically expressed in the sensory neurons of the human peripheral nervous system and involved in nociception. Here, we studied DNA polymorphism patterns and evolution of the MRGX2 gene in world-wide human populations and the representative nonhuman primate species. Our results demonstrated that MRGX2 had undergone adaptive changes in the path of human evolution, which were likely caused by Darwinian positive selection. The patterns of DNA sequence polymorphisms in human populations showed an excess of derived substitutions, which against the expectation of neutral evolution, implying that the adaptive evolution of MRGX2 in humans was a relatively recent event. The reconstructed secondary structure of the human MRGX2 revealed that three of the four human-specific amino acid substitutions were located in the extra-cellular domains. Such critical substitutions may alter the interactions between MRGX2 protein and its ligand, thus, potentially led to adaptive changes of the pain-perception-related nervous system during human evolution. (c) 2005 Elsevier B.V. All rights reserved.

Islet-1 is required for ventral neuron survival in Xenopus

Islet-1 is a LIM domain transcription factor involved in several processes of embryonic development. Xenopus Islet-1 (Xisl-1) has been shown to be crucial for proper heart development. Here we show that Xisl-1 and Xisl-2 are differentially expressed in th

Telemetric recordings of single neuron activity and visual scenes in monkeys walking in an open field

This paper describes a portable recording system and methods for obtaining chronic recordings of single units and tracking rhesus monkey behavior in an open field. The integrated system consists of four major components: (1) microelectrode assembly; (2) h

DOPAMINE D2 RECEPTOR MECHANISMS CONTRIBUTE TO AGE-RELATED COGNITIVE DECLINE - THE EFFECTS OF QUINPIROLE ON MEMORY AND MOTOR-PERFORMANCE IN MONKEYS

The D2 dopamine (DA) receptor agonist, quinpirole, was characterized in young adult monkeys, young reserpine-treated monkeys and aged monkeys to assess the contribution of DA to age-related loss of prefrontal cortical (PFC) cognitive function, Monkeys were tested on a delayed response memory task that depends on the PFC, and a fine motor task that taps the functions of the motor cortex, In young adult monkeys, low quinpirole doses impaired performance of the PFC and fine motor tasks, while higher doses improved memory performance and induced dyskinesias and ''hallucinatory-like'' behaviors. The pattern of the quinpirole response in reserpine-treated monkeys suggested that the impairments in delayed response and fine motor performance resulted from drug actions at D2 autoreceptors, while the improvement in delayed response performance, dyskinesias and ''hallucinatory-like'' behaviors resulted from actions at postsynaptic receptors. In aged monkeys, low doses of quinpirole continued to impair fine motor performance, but lost their ability to impair delayed response performance. The magnitude of cognitive improvement and the incidence of ''hallucinatory-like'' behaviors were also reduced in the aged animals, suggesting some loss of postsynaptic D2 receptor function, The pattern of results is consistent with the greater loss of DA from the PFC than from motor areas in aged monkey brain (Goldman-Rakic and Brown, 1981; Wenk et al., 1989), and indicates that DA depletion contributes significantly to age-related cognitive decline.

The multi-weight neuron with geometry algorithm and its application

A novel approach for multi-dimension signals processing, that is multi-weight neural network based on high dimensional geometry theory, is proposed. With this theory, the geometry algorithm for building the multi-weight neuron is mentioned. To illustrate the advantage of the novel approach, a Chinese speech emotion recognition experiment has been done. From this experiment, the human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. And the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. Compared with traditional GSVM model, the new method has its superiority. It is noted that this method has significant values for researches and applications henceforth.

Double synaptic weight neuron theory and its application

In this paper, a novel mathematical model of neuron-Double Synaptic Weight Neuron (DSWN)(l) is presented. The DSWN can simulate many kinds of neuron architectures, including Radial-Basis-Function (RBF), Hyper Sausage and Hyper Ellipsoid models, etc. Moreover, this new model has been implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. The flexibility of the DSWN has also been described in constructing neural networks. Based on the theory of Biomimetic Pattern Recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-II neurocomputer. In these two special cases, the result showed DSWN neural network had great potential in pattern recognition.

Application of multi-weighted neuron for iris recognition

In this paper, from the cognition science point of view, we constructed a neuron of multi-weighted neural network, and proposed a new method for iris recognition based on multi-weighted neuron. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the correct rejection rate is 98.9%, the correct cognition rate and the error recognition rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high. It proves the proposed method for iris recognition is effective.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

Continuous speech research based on HyperSausage Neuron

In this paper, we presents HyperSausage Neuron based on the High-Dimension Space(HDS), and proposes a new algorithm for speaker independent continuous digit speech recognition. At last, compared to HMM-based method, the recognition rate of HyperSausage Neuron method is higher than that of in HMM-based method.

A more complex neuron in biomimetic pattern recognition

Biomimetic pattern recognition has been proposed for several years, but the discussion of its neuron was not very wide and deep. In this paper, we propose a new more complex neuron named M-neuron and give the application in the last part of the paper.

Continuous speech research based on HyperSausage Neuron

In this paper, we presents HyperSausage Neuron based on the High-Dimension Space(HDS), and proposes a new algorithm for speaker independent continuous digit speech recognition. At last, compared to HMM-based method, the recognition rate of HyperSausage Neuron method is higher than that of in HMM-based method.

Fucoidan protects against dopaminergic neuron death in vivo and in vitro

Parkinson's disease is a neurodegenerative disorder of uncertain pathogenesis characterized by a loss of dopaminergic neurons in substantia nigra pars compacta, and can be modeled by the neurotoxin 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP). Oxidative stress may contribute to MPTP- and Parkinson's disease-related neurodegeneration. Fucoidan is a sulfated polysaccharide extracted from brown seaweeds which possesses a wide variety of biological activities including potent antioxidative effects. Here we investigated the effect of fucoidan treatment on locomoter activities of animals, striatal dopamine and its metabolites and survival of nigral dopaminergic neurons in MPTP-induced animal model of Parkinsonism in C57/BL mice in vivo and on the neuronal damage induced by 1-methyl-4-phenylpyridinium (MPP+) in vitro, and to study the possible mechanisms. When administered prior to MPTP, fucoidan reduced behavioral deficits, increased striatal dopamine and its metabolites levels, reduced cell death, and led to a marked increase in tyrosine hydroxylase expression relative to mice treated with MPTP alone. Furthermore, we found that fucoidan inhibited MPTP-induced lipid peroxidation and reduction of antioxidant enzyme activity. In addition, pre-treatment with fucoidan significantly protected against MPP+-induced damage in MN9D cells. Taken together, these findings suggest that fucoidan has protective effect in MPTP-induced neurotoxicity in this model of Parkinson's disease via its antioxidative activity. (C) 2009 Elsevier B.V. All rights reserved.