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An immune therapy model for effective treatment on inflammatory bowel disease
Inflammatory bowel disease (IBD) is a disease that causes inflammation throughout the digestive tract. Repeated inflammation and frequent relapses cause intestinal damage and expose the patient to a higher risk. In this work, we proposed an immune therapy model for effective treatment strategy throu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514012/ https://www.ncbi.nlm.nih.gov/pubmed/32970698 http://dx.doi.org/10.1371/journal.pone.0238918 |
Sumario: | Inflammatory bowel disease (IBD) is a disease that causes inflammation throughout the digestive tract. Repeated inflammation and frequent relapses cause intestinal damage and expose the patient to a higher risk. In this work, we proposed an immune therapy model for effective treatment strategy through mathematical modeling for patients with IBD. We evaluated the ability of the patient’s immune system to recover during treatment. For this, we defined the interval of healthy individual, and examined the frequency of compartments such as T cells and cytokines considered in the model maintain the normal state. Based on the fact that each patient has a unique immune system, we have shown at the same drug works differently, depending on the individual immune system characteristics for every patient. It is known that IBD is related to an imbalance between pro- and anti- inflammatory cytokines as the cause of the disease. So the ratios of pro- to anti- inflammatory cytokines are used as an indicator of patient’s condition and inflammation status in various diseases. We compared the ratios of pro- to anti- inflammatory cytokine according to patient’s individual immune system and drugs. Since the effects of biological drugs are highly dependent on the patient’s own immune system, it is essential to define the immune system status before selecting and using a biological drug. |
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