Atherosclerosis, a pathology affecting arterial blood vessels, is one of most common disease of the developed countries. We present studies on the increased atherosclerosis risk using an agent based model of atherogenesis that has been previously validated using clinical data. It is well known that the major risk in atheroscle- rosis is the persistent high level of low density lipoprotein (LDL) concentration. However, it is not known if short period of high LDL con- centration can cause irreversible damage and if reduction of the LDL concentration (either by life style or drug) can drastically or partially reduce the already acquired risk. We used the Sicilian Grid infrastructure to simulate three different clinical situations in a large set of virtual patients (200 per clinical scenario). In the first one the patients lifestyle maintains the concentration of LDL in a no risk range. This is the control case simulation. In the second and in the third simu- lations, the lifestyle of the virtual patients raises the LDL concentration to a risk level. Differences in the foam cells formation can be interpreted as permanent or non-permanent risk effects. Finally we consider virtual patients whose life style raises many times the level of LDL concentration just above the normal but this is quickly reduced using appropriate treatment. Those preliminary results obviously need to be clinically investigated. The Grid power allowed us to retrieve results of the simulation in a short time.

Atherosclerosis, a pathology affecting arterial blood vessels, is one of most common disease of the developed countries. We present studies on the increased atherosclerosis risk using an agent based model of atherogenesis that has been previously validated using clinical data. It is well known that the major risk in atherosclerosis is the persistent high level of low density lipoprotein (LDL) concentration. However, it is not known if short period of high LDL concentration can cause irreversible damage and if reduction of the LDL concentration (either by life style or drug) can drastically or partially reduce the already acquired risk. We used the Sicilian GRID infrastructure to simulate three different clinical situations in a large set of virtual patients (200 per clinical scenario). In the first one the patients lifestyle maintains the concentration of LDL in a no risk range. This is the control case simulation. In the second and in the third simulations, the lifestyle of the virtual patients raises the LDL concentration to a risk level. Differences in the foam cells formation can be interpreted as permanent or non-permanent risk effects. Finally we consider virtual patients whose life style raises many times the level of LDL concentration just above the normal but this is quickly reduced using appropriate treatment. Those preliminary results obviously need to be clinically investigated. The GRID power allowed us to retrieve results of the simulation in a short time.

Grid-based atherosclerosis simulations

PAPPALARDO, FRANCESCO;PENNISI, MARZIO ALFIO;MOTTA, Santo
2009-01-01

Abstract

Atherosclerosis, a pathology affecting arterial blood vessels, is one of most common disease of the developed countries. We present studies on the increased atherosclerosis risk using an agent based model of atherogenesis that has been previously validated using clinical data. It is well known that the major risk in atheroscle- rosis is the persistent high level of low density lipoprotein (LDL) concentration. However, it is not known if short period of high LDL con- centration can cause irreversible damage and if reduction of the LDL concentration (either by life style or drug) can drastically or partially reduce the already acquired risk. We used the Sicilian Grid infrastructure to simulate three different clinical situations in a large set of virtual patients (200 per clinical scenario). In the first one the patients lifestyle maintains the concentration of LDL in a no risk range. This is the control case simulation. In the second and in the third simu- lations, the lifestyle of the virtual patients raises the LDL concentration to a risk level. Differences in the foam cells formation can be interpreted as permanent or non-permanent risk effects. Finally we consider virtual patients whose life style raises many times the level of LDL concentration just above the normal but this is quickly reduced using appropriate treatment. Those preliminary results obviously need to be clinically investigated. The Grid power allowed us to retrieve results of the simulation in a short time.
2009
9788895892023
Atherosclerosis, a pathology affecting arterial blood vessels, is one of most common disease of the developed countries. We present studies on the increased atherosclerosis risk using an agent based model of atherogenesis that has been previously validated using clinical data. It is well known that the major risk in atherosclerosis is the persistent high level of low density lipoprotein (LDL) concentration. However, it is not known if short period of high LDL concentration can cause irreversible damage and if reduction of the LDL concentration (either by life style or drug) can drastically or partially reduce the already acquired risk. We used the Sicilian GRID infrastructure to simulate three different clinical situations in a large set of virtual patients (200 per clinical scenario). In the first one the patients lifestyle maintains the concentration of LDL in a no risk range. This is the control case simulation. In the second and in the third simulations, the lifestyle of the virtual patients raises the LDL concentration to a risk level. Differences in the foam cells formation can be interpreted as permanent or non-permanent risk effects. Finally we consider virtual patients whose life style raises many times the level of LDL concentration just above the normal but this is quickly reduced using appropriate treatment. Those preliminary results obviously need to be clinically investigated. The GRID power allowed us to retrieve results of the simulation in a short time.
Agent-based model; GRID; HPC
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/76144
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