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Cardiotocography records fetal heart rates and their temporal relationship to uterine contractions. To identify high risk fetuses, obstetricians inspect cardiotocograms (CTGs) by eye. Therefore, CTG traces are often interpreted differently among obstetricians, resulting in inappropriate interventions. However, few studies have focused on quantitative and nonbiased algorithms for CTG evaluation. In this study, we propose a newly constructed deep neural network model (CTG-net) to detect compromised fetal status. CTG-net consists of three convolutional layers that extract temporal patterns and interrelationships between fetal heart rate and uterine contraction signals. We aimed to classify the abnormal group (umbilical artery pH < 7.20 or Apgar score at 1 min < 7) and the normal group from CTG data. We evaluated the performance of the CTG-net with the F1 score and compared it with conventional algorithms, namely, support vector machine and k-means clustering, and another deep neural network model, long short-term memory. CTG-net showed the area under the receiver operating characteristic curve of 0.73 ± 0.04, which was significantly higher than that of long short-term memory. CTG-net, a quantitative and automated diagnostic aid system, enables early intervention for putatively abnormal fetuses, resulting in a reduction in the number of cases of hypoxic injury. [ABSTRACT FROM AUTHOR]

The receptor for advanced glycation end-products (RAGE) and the G protein-coupled angiotensin II (AngII) type I receptor (AT1) play a central role in cardiovascular diseases. It was recently reported that RAGE modifies AngII-mediated AT1 activation via the membrane oligomeric complex of the two receptors. In this study, we investigated the presence of the different directional crosstalk in this phenomenon, that is, the RAGE/AT1 complex plays a role in the signal transduction pathway of RAGE ligands. We generated Chinese hamster ovary (CHO) cells stably expressing RAGE and AT1, mutated AT1, or AT2 receptor. The activation of two types of G protein α-subunit, Gq and Gi, was estimated through the accumulation of inositol monophosphate and the inhibition of forskolin-induced cAMP production, respectively. Rat kidney epithelial cells were used to assess RAGE ligand-induced cellular responses. We determined that RAGE ligands activated Gi, but not Gq, only in cells expressing RAGE and wildtype AT1. The activation was inhibited by an AT1 blocker (ARB) as well as a RAGE inhibitor. ARBs inhibited RAGE ligand-induced ERK phosphorylation, NF-κB activation, and epithelial–mesenchymal transition of rat renal epithelial cells. Our findings suggest that the activation of AT1 plays a central role in RAGE-mediated cellular responses and elucidate the role of a novel molecular mechanism in the development of cardiovascular diseases. [ABSTRACT FROM AUTHOR]