Valproic acid elevates HIF-1α-mediated CGB expression and suppresses glucose uptake in BeWo cells.

Placental dysfunction can disrupt pregnancy. However, few studies have assessed the effects of chemical-induced toxicity on placental function. Here, we examined the effects of valproic acid (VPA) as a model chemical on production of hormones and on glucose uptake in human choriocarcinoma cell line BeWo. Cells were treated with forskolin to differentiate into syncytiotrophoblasts, which were then treated with VPA for 72 hr. Real-time RT-PCR analysis showed that VPA significantly increased the mRNA expression of chorionic gonadotropin ß (CGB), a hormone that is produced by the placenta in the first trimester of pregnancy, relative to that in the forskolin-only group. It also suppressed the increase in intracellular glucose uptake and GLUT1 level observed in the forskolin-only group. RNA-seq analysis and pathway database analysis revealed that VPA consistently decreased the level of HIF-1α protein and expression of its downstream target genes HK2 and ADM in the hypoxia pathway. Cobalt chloride, a HIF-1α inducer, inhibited CGB upregulation in VPA-treated cells and rescued VPA-induced suppression of glucose uptake and GLUT1 level. Thus, HIF-1α-mediated elevation of CGB expression and suppression of glucose uptake by VPA is a novel mechanism of placental dysfunction.

Modeling of decision-making process for moving straight using inverse Bayesian inference.

Humans sometimes make unreasonable decisions when viewed in objective terms. Even in the real world, we may lose sense of direction by turning around the corner several times or mistaking the estimation of travel distance. We experimented in virtual space how we lose sense of direction under what circumstances. In the experiment, subjects viewed a three-dimensional space displayed on a computer display in the first person's perspective and were instructed to go straight from the start to the goal position. Results showed that unreasonable selections that strayed from the centerline connecting the start and goal positions were frequently made. The change in the direction is more influential than the change in the distance, and the angle of turning also affects. Furthermore, the subject's decision - making process was modeled using Bayesian inference and inverse Bayesian inference. Comparing the two models, when the decision-making pattern suddenly changed, the model by inverse Bayesian inference could follow up faster than the Bayesian inference.