Protective Autoimmunity: A Unifying Model for the Immune Network Involved in CNS Repair

2014 ◽  
Vol 20 (4) ◽  
pp. 343-358 ◽  
Author(s):  
M. Schwartz ◽  
C. Raposo
Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1078
Author(s):  
Debasish Roy ◽  
Andrea Tedeschi

Axons in the adult mammalian nervous system can extend over formidable distances, up to one meter or more in humans. During development, axonal and dendritic growth requires continuous addition of new membrane. Of the three major kinds of membrane lipids, phospholipids are the most abundant in all cell membranes, including neurons. Not only immature axons, but also severed axons in the adult require large amounts of lipids for axon regeneration to occur. Lipids also serve as energy storage, signaling molecules and they contribute to tissue physiology, as demonstrated by a variety of metabolic disorders in which harmful amounts of lipids accumulate in various tissues through the body. Detrimental changes in lipid metabolism and excess accumulation of lipids contribute to a lack of axon regeneration, poor neurological outcome and complications after a variety of central nervous system (CNS) trauma including brain and spinal cord injury. Recent evidence indicates that rewiring lipid metabolism can be manipulated for therapeutic gain, as it favors conditions for axon regeneration and CNS repair. Here, we review the role of lipids, lipid metabolism and ectopic lipid accumulation in axon growth, regeneration and CNS repair. In addition, we outline molecular and pharmacological strategies to fine-tune lipid composition and energy metabolism in neurons and non-neuronal cells that can be exploited to improve neurological recovery after CNS trauma and disease.


Author(s):  
Seyed M Matloobi ◽  
Mohammad Riahi

Reducing the cost of unscheduled shutdowns and enhancing the reliability of production systems is an important goal for various industries; this could be achieved by condition monitoring and artificial intelligence. Cavitation is a common undesired phenomenon in centrifugal pumps, which causes damage and its detection in the preliminary stage is very important. In this paper, cavitation is identified by use of vibration and current signal and artificial immune network that is modeled on the base of the human immune system. For this purpose, first data collection were done by a laboratory setup in health and five stages damage condition; then various features in time, frequency, and time–frequency were extracted from vibration and current signals in addition to pressure and flow rate; next feature selection and dimensions reduction were done by artificial immune method to use for classification; finally, they were used by artificial immune network and some other methods to identify the system condition and classification. The results of this study showed that this method is more accurate in the detection of cavitation in the initial stage compared to methods such as non-linear supportive vector machine, multi-layer artificial neural network, K-means and fuzzy C-means with the same data. Also, selected features with artificial immune system were better than principal component analysis results.


2015 ◽  
Vol 296 (2) ◽  
pp. 122-132 ◽  
Author(s):  
Milos Kostic ◽  
Ivana Stojanovic ◽  
Goran Marjanovic ◽  
Nikola Zivkovic ◽  
Ana Cvetanovic

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