| With the rapid development of society and economy,high speed transportation,population ageing,ecosystem deterioration and other factors,the incidence rate of spinal cord injury(SCI)caused by trauma or disease has increased year by year around the world.The brain and spinal cord together make up the central nervous system(CNS).An injured spinal cord has a poor intrinsic capacity for regeneration,although some functional recovery does occur.The poor CNS regeneration is due,in part,to the presence of myelin-associated inhibitors and the loss of neurotrophic factors in the microenvironment after SCI.SCI can often result in devasting consequences including paralyzed muscle and loss of sensation.This injury can also cause heavy economic burden for patients' family and the whole society.Spinal cord regeneration after SCI has been a challenging problem for centuries in the biomedical field.In the last three decades,the early mortality after SCI has been declining significantly as a result of the breakthrough in neuroscience and medical technology,and this progress has brought the dawn for the possibility of neuron regeneration after SCI.Therefore,neural repair and regeneration after SCI is among the top studied topics in the biomedical field.It is clear that effective treatment will require a multifaceted combination of strategies.Mathematical modeling could provide an opportunity to elucidate the ratio and distribution law of various impact factors,and network analysis could predict unknown compounds and molecules related with the SCI.In this study,mathematical model and network analysis approach were used to explore the mechanisms of axon regeneration after SCI.The results in this study will provide a theoretical reference for researchers to design efficient experiments.The contents and innovations of this dissertation include the following four major aspects:1.Based on the experimental data and biological analysis software,we proposed a network approach for inferring functions,pathways and diseases potentially affected by SCI on humans by using known interactions between SCI and related proteins.The results of network analysis indicated that the top 10 proteins associated with SCI were TNF,FOS,TGFB1,PTGS2,IL6,ICAM1,MMP9,STAT1,EDN1 and AGT.The enriched biological processes revealed that SCI could interfere with response to lipopolysaccharide.The top diseases associated with TNF were seizures,nerve degeneration,memory disorders,neurotoxicity syndromes,learning disorders.Several results were further analyzed to give insights into the mechanisms of SCI.The network approach may offer a better understanding of the potential factors of SCI and a direction for future axonal regeneration research.2.A mathematical model was established to explore how the regenerative axons grow along the surface of a spherical multifunctional scaffold or thro ugh the glial scar.To answer this question,a three-dimensional lattice Boltzmann method(LBM)was employed for the numerical simulation.This model was constructed based on the principle of chemotaxis of cells and the related experimental data available.Concentration gradients of three types of diffusible molecules were tested in this model:(1)Type 1 factors,that is,attractive molecules that are released by the target tissues after nerve injury;(2)Type 2 factors,that is,chondroitin sulfate proteoglycans(CSPGs)that are not neutralized by the Chase-ABC;and(3)Type 3 factors,that is,a variety of growth promoting molecules.These simulations consist of two parts:(1)the reaction-diffusion equation describes the transmission of nerve factors and other guidance molecules during development,and(2)the axonal “growth equation? describes the growth of axons determined by the concentration gradient of the guidance molecules.This model provides a reliable computational platform for research in this field.3.A numerical simulation method,which was based on the experiment for the SCI repair by olfactory ensheathing cells(OECs)transplantation,was used to explore how the regenerative axons grow through the glial scar.Using the simulated data,two significant conclusions were made in this study:(1)thickness of glial scar and inhibitor releasing rate inversely correlate with axonal growth rate;(2)Axon growth rate essentially depends on the ratio of the inhibitor concentration to the promotors' located at the growth cones.The regenerated axons will grow smoothly and reach their target cells successfully when the average ratio is less than a certain threshold(1.5).These results will provide theoretical guidance and reference for researchers to design efficient experiments.4.We proposed and designed a solid spherical multifunctional biomaterial scaffold that bridges the rostral and caudal stumps of a completely transected spinal cord in a rat model.The effects of the entry slope of the scaffold and the biomedical modifications on axonal regeneration were assessed by a mathematical method.In numerical simulations,a slimmer scaffold provided a small slope at the entry ?on-ramp? area that improved the success rate of axonal regeneration.However,a high success rate increased the number of regenerative axons traversing a narrow channel,causing traffic jams and lowering the growth rate.Increasing the number of severed axons(from 300 to 12000)did not significantly affect the growth rate,but reduced the success rate of axonal regeneration.Increasing the seeding densities of complexes on the whole scaffold and chemoattractants on the caudal area improved both the success and growth rates.However,increasing the density of complexes on the whole scaffold risks an over-eutrophic surface can harm the axonal regeneration.The principal reason why the same kind of earlier scaffold has a low success rate or failure for axonal regeneration,has been interpreted successfully in theory. |
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