Literatura académica sobre el tema "Neuronal netwrk repairing"

AbstractThe nervous system, which consists of a complex network of millions of neurons, is one of the most highly intricate systems in the body. This complex network is responsible for the physiological and cognitive functions of the human body. Following injuries or degenerative diseases, damage to the nervous system is overwhelming because of its complexity and its limited regeneration capacity. However, neural tissue engineering currently has some capacities for repairing nerve deficits and promoting neural regeneration, with more developments in the future. Nevertheless, controlling the guidance of stem cell proliferation and differentiation is a challenging step towards this goal. Nanomaterials have the potential for the guidance of the stem cells towards the neural lineage which can overcome the pitfalls of the classical methods since they provide a unique microenvironment that facilitates cell–matrix and cell–cell interaction, and they can manipulate the cell signaling mechanisms to control stem cells’ fate. In this article, the suitable cell sources and microenvironment cues for neuronal tissue engineering were examined. Afterward, the nanomaterials that impact stem cell proliferation and differentiation towards neuronal lineage were reviewed.

Digital reconstruction of neurons is a critical step in studying neuronal morphology and exploring the working mechanism of the brain. In recent years, the focus of neuronal morphology reconstruction has gradually shifted from single neurons to multiple neurons in a whole brain. Microscopic images of a whole brain often have low signal-to-noise-ratio, discontinuous neuron fragments or weak neuron signals. It is very difficult to segment neuronal signals from the background of these images, which is the first step of most automatic reconstruction algorithms. In this study, we propose a Nested U-Net based Ultra-Tracer model (NUNU-Tracer) for better multiple neurons image segmentation and morphology reconstruction. The NUNU-Tracer utilizes nested U-Net (UNet++) deep network to segment 3D neuron images, reconstructs neuron morphologies under the framework of the Ultra-Tracer and prunes branches of noncurrent tracing neurons. The 3D UNet++ takes a 3D microscopic image as its input, and uses scale-space distance transform and linear fusion strategy to generate the segmentation maps for voxels in the image. It is capable of removing noise, repairing broken neurite patterns and enhancing neuronal signals. We evaluate the performance of the 3D UNet++ for image segmentation and NUNU-Tracer for neuron morphology reconstruction on image blocks and neurons, respectively. Experimental results show that they significantly improve the accuracy and length of neuron reconstructions.

2011/2012
Nanotechnology underwent a very rapid development in the last decades, thanks to the invention of different techniques that allow reaching the nanoscale. The great interest in this area arises from the variety of possible applications in different fields, such as electronics, where the miniaturization of components is a key factor, but also medicine. The creation of smart systems able to carry out a specific task in the body in a controlled way, either in diagnosis or therapy or tissue engineering, is the ultimate goal of a newborn area of research, called nanomedicine. In fact, to reach such an outstanding objective, a nanometer‐sized material is needed and carbon nanotubes (CNTs) are among the most promising candidates. The aim of this thesis was to study this opportunity and, in particular, the possible application of carbon nanotubes for spinal network repairing. After a review of the main features of neuronal network systems and the most common techniques to study their functionality, possible applications of nanotechnology for nanomedicine purposes are considered, focusing the attention on CNTs as neuronal interface in nerve tissue engineering. The work can be divided into two big parts. In the first part the impact of carbon nanotubes on various neuronal systems was studied. Different form of carbonaceous materials (carbon nanotubes, nanohorns and graphene) were deposited in a homogeneous way on a glass surface playing with organic functionalization and different deposition techniques. Hippocampal neuronal cells were grown on their surface to better understand how morphology and conductivity of the material could influence the activity of the neuronal network evidencing how both these characteristics could affect the electrophysiological properties of neurons. Then, also spinal neurons were grown on carbon nanotubes network deposited on a glass substrate to evaluate, for the first time, the impact of carbon nanotubes on this kind of cells. The tight interaction between these two materials appeared to cause a faster maturation of the spinal neurons with respect II to the control grown on a glass substrate. The long-term impact on a complex tissue (spinal cord slice) grown on carbon nanotubes carpet was also studied. The intimate interaction between the two materials observed by TEM and SEM analysis caused an increase in dimensions and number of neuronal fibers that comes out from the body of a spinal cord slice. An increase in electrophysiological activity of all neuronal network of the slice was also reported. In the second part of the work different conductive biocompatible nanocomposite materials based on carbon nanotubes and “artificial” polymers (such as Nafion, PVA, PET, PEI, PDMS and PANI) were investigated. The idea is to test these materials as neuronal prosthesis to repair spinal cord damage. All the prepared scaffolds showed CNTs on the surface favoring CNTs-neurons interaction. To address this aim different techniques and different organic functionalizations of CNTs were utilized to control supramolecular interactions between the nanomaterial and polymers orienting the deposition of the CNTs and preventing their aggregation. After that, an innovative method to study the possible ability of this nanocomposite materials to transmit a neuronal signal between two portions of spinal cord was designed. Functionalization of gold surfaces with thiolated carbon nanotubes have been conducted in order to develop suitable devices for neuronal stimulation and consequent spinal cord lesions repairing. In particular thiol groups were introduced on the graphitic surface of carbon nanotubes by means of covalent functionalization. First of all, the interaction of CNTs with gold nanoparticles has been evaluated, then a gold surface has been coated by means of contact printing technique with a homogeneous film of CNTs. This hybrid material could be useful to produce innovative electrodes for neuronal stimulation
XXV Ciclo
1985

About 50,000 cases of peripheral nerve injuries occur annually [1] resulting in patient pain or loss of touch. Methods of repairing peripheral nerve gaps is essential for aiding in patient recovery. During development, growth, and joint movement, nerves are exposed to mechanical tension that is hypothesized to aid in their growth. Neurons can grow less than .5–1 mm/day but are known to grow up to ∼3 cm/day during development, theorized from factors of stretch on cell cytoskeleton during growth [2,3]. Our focus was to investigate the effects of mechanical strain on nerve growth. We fabricated biodegradable, electrospun, polycaprolactone (PCL) scaffolds to create three-dimensional, nanofibrous networks for Dorsal Root Ganglia (DRG) neuron extension and growth. To test the effects of scaffold stretch and tension on DRG growth, scaffolds were stretched using a custom scaffold stretcher. DRG growth was investigated for 3mm changes in scaffold length on days 0 and 1 of DRG development. Further investigation of DRG growth on day 2 and 3 as well as stretches of 6 and 9mm are being performed. In addition, an incremental stretch test for total stretches of 3, 6, and 9mm will be performed.