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2018 ; 9
(ä): 393
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Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico
Approach Combining In vitro Experiments and Machine Learning
#MMPMID29616016
Zechendorf E
; Vaßen P
; Zhang J
; Hallawa A
; Martincuks A
; Krenkel O
; Müller-Newen G
; Schuerholz T
; Simon TP
; Marx G
; Ascheid G
; Schmeink A
; Dartmann G
; Thiemermann C
; Martin L
Front Immunol
2018[]; 9
(ä): 393
PMID29616016
show ga
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
? 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.
|*Machine Learning
[MESH]
|Algorithms
[MESH]
|Animals
[MESH]
|Apoptosis
[MESH]
|Cardiomyopathies/*metabolism/pathology
[MESH]
|Caspase 3/metabolism
[MESH]
|Cell Culture Techniques/*methods
[MESH]
|Cells, Cultured
[MESH]
|Cytochromes c/metabolism
[MESH]
|Heparitin Sulfate/*metabolism
[MESH]
|Humans
[MESH]
|Mice
[MESH]
|Myocytes, Cardiac/*physiology
[MESH]
|Necrosis
[MESH]
|Receptor-Interacting Protein Serine-Threonine Kinases/metabolism
[MESH]