Simulation of Spread and Control of Lesions in Brain
A simulation model for the spread and control of lesions in the brain is constructed using a planar network (graph) representation for the central nervous system (CNS). The model is inspired by the lesion structures observed in the case of multiple sclerosis (MS), a chronic disease of the CNS. The i...
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description | A simulation model for the spread and control of lesions in the brain is constructed using a planar network (graph) representation for the central nervous system (CNS). The model is inspired by the lesion structures observed in the case of multiple sclerosis (MS), a chronic disease of the CNS. The initial lesion site is at the center of a unit square and spreads outwards based on the success rate in damaging edges (axons) of the network. The damaged edges send out alarm signals which, at appropriate intensity levels, generate programmed cell death. Depending on the extent and timing of the programmed cell death, the lesion may get controlled or aggravated akin to the control of wild fires by burning of peripheral vegetation. The parameter phase space of the model shows smooth transition from uncontrolled situation to controlled situation. The simulations show that the model is capable of generating a wide variety of lesion growth and arrest scenarios. |
doi_str_mv | 10.1155/2012/383546 |
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The model is inspired by the lesion structures observed in the case of multiple sclerosis (MS), a chronic disease of the CNS. The initial lesion site is at the center of a unit square and spreads outwards based on the success rate in damaging edges (axons) of the network. The damaged edges send out alarm signals which, at appropriate intensity levels, generate programmed cell death. Depending on the extent and timing of the programmed cell death, the lesion may get controlled or aggravated akin to the control of wild fires by burning of peripheral vegetation. The parameter phase space of the model shows smooth transition from uncontrolled situation to controlled situation. 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The simulations show that the model is capable of generating a wide variety of lesion growth and arrest scenarios.</description><subject>Apoptosis - physiology</subject><subject>Brain - pathology</subject><subject>Computer Simulation</subject><subject>Humans</subject><subject>Models, Biological</subject><subject>Multiple Sclerosis - pathology</subject><subject>Signal Transduction</subject><issn>1748-670X</issn><issn>1748-6718</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><recordid>eNqFkM1Lw0AQxRdRrFZPnpXcBKV2Zz-ym4ugxS8oeKiCt2XS7NqVNFuzqeJ_b0pq0ZOnGWZ-vHnzCDkCegEg5ZBRYEOuuRTpFtkDJfQgVaC3Nz196ZH9GN8olaAk7JIeYxwyKbI9IiZ-viyx8aFKgksmi9pikWBVJKNQNXUoV9Oxje0-Jr5Krmv01QHZcVhGe7iuffJ8e_M0uh-MH-8eRlfjwVRw1QwKprWzOs1ToLlWMuMMFHNUOtA5OIpSFFxqTDPkea6xUBkoTHMBCDkvHO-Ty053sczntpja1hGWZlH7OdZfJqA3fzeVn5nX8GE4U5wDawVO1wJ1eF_a2Ji5j1NblljZsIwmYwCCcpa25HlHTusQY23d5gpQs4rZrGI2XcwtffLb2Ib9ybUFzjpg5qsCP_0_ascdbFvEOtzAIlWqfeQbVh2Njw</recordid><startdate>20120101</startdate><enddate>20120101</enddate><creator>Thamattoor Raman, Krishna Mohan</creator><general>Hindawi Puplishing Corporation</general><general>Hindawi Publishing Corporation</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20120101</creationdate><title>Simulation of Spread and Control of Lesions in Brain</title><author>Thamattoor Raman, Krishna Mohan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c437t-d288fe86b610b875932172f05f18b1f0a54d358a69a3bb8ad7917a6b41a1b3df3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Apoptosis - physiology</topic><topic>Brain - pathology</topic><topic>Computer Simulation</topic><topic>Humans</topic><topic>Models, Biological</topic><topic>Multiple Sclerosis - pathology</topic><topic>Signal Transduction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Thamattoor Raman, Krishna Mohan</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational and mathematical methods in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Thamattoor Raman, Krishna Mohan</au><au>Rai, Vikas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation of Spread and Control of Lesions in Brain</atitle><jtitle>Computational and mathematical methods in medicine</jtitle><addtitle>Comput Math Methods Med</addtitle><date>2012-01-01</date><risdate>2012</risdate><volume>2012</volume><issue>2012</issue><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1748-670X</issn><eissn>1748-6718</eissn><abstract>A simulation model for the spread and control of lesions in the brain is constructed using a planar network (graph) representation for the central nervous system (CNS). 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subjects | Apoptosis - physiology Brain - pathology Computer Simulation Humans Models, Biological Multiple Sclerosis - pathology Signal Transduction |
title | Simulation of Spread and Control of Lesions in Brain |
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