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Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical- In silico Approach Combining In vitro Experiments and Machine Learning.
- Source :
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Frontiers in immunology [Front Immunol] 2018 Mar 20; Vol. 9, pp. 393. Date of Electronic Publication: 2018 Mar 20 (Print Publication: 2018). - Publication Year :
- 2018
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Abstract
- Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical- In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 ( p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical- In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.
- Subjects :
- Algorithms
Animals
Apoptosis
Cardiomyopathies pathology
Caspase 3 metabolism
Cells, Cultured
Cytochromes c metabolism
Humans
Mice
Necrosis
Receptor-Interacting Protein Serine-Threonine Kinases metabolism
Sepsis pathology
Signal Transduction
Wounds and Injuries pathology
Cardiomyopathies metabolism
Cell Culture Techniques methods
Heparitin Sulfate metabolism
Machine Learning
Myocytes, Cardiac physiology
Sepsis metabolism
Wounds and Injuries metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 1664-3224
- Volume :
- 9
- Database :
- MEDLINE
- Journal :
- Frontiers in immunology
- Publication Type :
- Academic Journal
- Accession number :
- 29616016
- Full Text :
- https://doi.org/10.3389/fimmu.2018.00393