A high throughput generative vector autoregression model for stochastic synapses.

By imitating the synaptic connectivity and plasticity of the brain, emerging electronic nanodevices offer new opportunities as the building blocks of neuromorphic systems. One challenge for large-scale simulations of computational architectures based on emerging devices is to accurately capture device response, hysteresis, noise, and the covariance structure in the temporal domain as well as between the different device parameters. We address this challenge with a high throughput generative model for synaptic arrays that is based on a recently available type of electrical measurement data for resistive memory cells.

Maternal nutrient restriction in guinea pigs leads to fetal growth restriction with evidence for chronic hypoxia.

BackgroundWe determined whether maternal nutrient restriction (MNR) in guinea pigs leading to fetal growth restriction (FGR) impacts markers for tissue hypoxia, implicating a mechanistic role for chronic hypoxia.MethodsGuinea pigs were fed ad libitum (Control) or 70% of the control diet before pregnancy, switching to 90% at mid-pregnancy (MNR). Near term, hypoxyprobe-1 (HP-1), a marker of tissue hypoxia, was injected into pregnant sows.

Maternal Nutrient Restriction in Guinea Pigs as an Animal Model for Inducing Fetal Growth Restriction.

We determined the impact of moderate maternal nutrient restriction (MNR) in guinea pigs on pregnancy outcomes, maternal/fetal growth parameters, and blood analytes to further characterize the utility of this model for inducing fetal growth restriction (FGR). Thirty guinea pig sows were fed ad libitum (Control) or 70% of the control diet prepregnant switching to 90% at midpregnancy (MNR). Animals were necropsied near term with weights obtained on all sows, fetuses, and placenta.