Lesions in the Hippocampus and Substantia Nigra of Wistar Rats’ Brains Induced by Organophosphate Insecticide

As little is known about the neurotoxicity of the histological structure of the brain, this study focuses on the histological side of four- to six-month-old adult Wistar rat brains, which were examined after 0.1 mg\g organophosphate had been administered orally. In this study, the lesions were mainly localized at the hippocampus and substantia nigra (compacta pars) region. Distinct areas of necrotic and apoptotic tissues were detected in the CA1, CA2, and dentate gyrus of the hippocampus and compacta pars of the substantia nigra. Programmed cell death in the dentate gyrus was observed as early as 72 hours after treatment and necrosis of some brain regions. Moreover, Lewy bodies were noticed in the compacta pars of the substantia nigra. The most important symptoms of parkinsonism were observed in the substantia nigra (compacta pars). These were decreased neurons, increased neuronal melanin in the neurons, and increased glial cells. The degeneration of some neurons was reported in the polymorphic and pyramidal layers. The data showed an increase in the density of the axon membrane and several changes to the axis structure, such as the disappearance of the myelin sheath in some areas along the axis.

Local CPG Self Growing Network Model with Multiple Physical Properties

Compared with traditional control methods, the advantage of CPG (Central Pattern Generator) network control is that it can significantly reduce the size of the control variable without losing the complexity of its motion mode output. Therefore, it has been widely used in the motion control of robots. To date, the research into CPG network has been polarized: one direction has focused on the function of CPG control rather than biological rationality, which leads to the poor functional adaptability of the control network and means that the control network can only be used under fixed conditions and cannot adapt to new control requirements. This is because, when there are new control requirements, it is difficult to develop a control network with poor biological rationality into a new, qualified network based on previous research; instead, it must be explored again from the basic link. The other direction has focused on the rationality of biology instead of the function of CPG control, which means that the form of the control network is only similar to a real neural network, without practical use. In this paper, we propose some physical characteristics (including axon resistance, capacitance, length and diameter, etc.) that can determine the corresponding parameters of the control model to combine the growth process and the function of the CPG control network. Universal gravitation is used to achieve the targeted guidance of axon growth, Brownian random motion is used to simulate the random turning of axon self-growth, and the signal of a single neuron is established by the Rall Cable Model that simplifies the axon membrane potential distribution. The transfer model, which makes the key parameters of the CPG control network—the delay time constant and the connection weight between the synapses—correspond to the axon length and axon diameter in the growth model and the growth and development of the neuron processes and control functions are combined. By coordinating the growth and development process and control function of neurons, we aim to realize the control function of the CPG network as much as possible under the conditions of biological reality. In this way, the complexity of the control model we develop will be close to that of a biological neural network, and the control network will have more control functions. Finally, the effectiveness of the established CPG self-growth control network is verified through the experiments of the simulation prototype and experimental prototype.

Neurons define non-myelinated axon segments by the regulation of galectin-4-containing axon membrane domains

The mechanism underlying selective myelination of axons versus dendrites or neuronal somata relies on the expression of somatodendritic membrane myelination inhibitors (i.e. JAM2). However, axons still present long unmyelinated segments proposed to contribute to axonal plasticity and higher order brain functions. Why these segments remain unmyelinated is still an unresolved issue. The bifunctional lectin galectin-4 (Gal-4) organizes the transport of axon glycoproteins by binding to N-acetyllactosamine (LacNac) termini of N-glycans. We have shown that Gal-4 is sorted to segmental domains (G4Ds) along the axon surface, reminiscent of these long unmyelinated axon segments in cortical neurons. We report here that oligodendrocytes (OLGs) do not deposit myelin on Gal-4 covered surfaces or myelinate axonal G4Ds. In addition, Gal-4 interacts and co-localizes in G4Ds with contactin-1, a marker of non-myelinated nodes of Ranvier. Neither Gal-4 expression nor G4D dimensions are affected by myelin extracts or myelinating OLGs, but are reduced with neuron maturation. As in vitro, Gal-4 is consistently segregated from myelinated structures in the brain. Our data shape the novel concept that neurons establish and regulate axon membrane domains expressing Gal-4, the first inhibitor of myelination identified in axons, whose boundaries delineate myelination-incompetent axon segments along neuron development.