Activation of the Maternal Immune System During Pregnancy Alters Behavioral Development of Rhesus Monkey Offspring

Background: Maternal infection during pregnancy is associated with an increased risk of schizophrenia and autism in the offspring. Supporting this correlation, experimentally activating the maternal immune system during pregnancy in rodents produces offspring with abnormal brain and behavioral development. We have developed a nonhuman primate model to bridge the gap between clinical populations and rodent models of maternal immune activation (MIA). Methods: A modified form of the viral mimic, synthetic double-stranded RNA (polyinosinic:polycytidylic acid stabilized with poly-L-lysine) was delivered to two separate groups of pregnant rhesus monkeys to induce MIA: 1) late first trimester MIA (n = 6), and 2) late second trimester MIA (n = 7). Control animals (n = 11) received saline injections at the same first or second trimester time points or were untreated. Sickness behavior, temperature, and cytokine profiles of the pregnant monkeys confirmed a strong inflammatory response to MIA. Results: Behavioral development of the offspring was studied for 24 months. Following weaning at 6 months of age, MIA offspring exhibited abnormal responses to separation from their mothers. As the animals matured, MIA offspring displayed increased repetitive behaviors and decreased affiliative vocalizations. When evaluated with unfamiliar conspecifics, first trimester MIA offspring deviated from species-typical macaque social behavior by inappropriately approaching and remaining in immediate proximity of an unfamiliar animal. Conclusions: In this rhesus monkey model, MIA yields offspring with abnormal repetitive behaviors, communication, and social interactions. These results extended the findings in rodent MIA models to more human-like behaviors resembling those in both autism and schizophrenia

Simulating Tariff Impact in Electrical Energy Consumption Profiles With Conditional Variational Autoencoders

International audienceThe implementation of efficient demand response (DR) programs for household electricity consumption would benefit from data-driven methods capable of simulating the impact of different tariffs schemes. This paper proposes a novel method based on conditional variational autoencoders (CVAE) to generate, from an electricity tariff profile combined with weather and calendar variables, daily consumption profiles of consumers segmented in different clusters. First, a large set of consumers is gathered into clusters according to their consumption behavior and price-responsiveness. The clustering method is based on a causality model that measures the effect of a specific tariff on the consumption level. Then, daily electrical energy consumption profiles are generated for each cluster with CVAE. This non-parametric approach is compared to a semi-parametric data generator based on generalized additive models. Experiments in a publicly available data set show that, the proposed method presents comparable performance to the semi-parametric one when it comes to generating the average value of the original data (13% difference in root mean square error). The main contribution from this new method is the capacity to reproduce rebound and side effects in the generated consumption profiles. Indeed, the application of a special electricity tariff over a time window may also affect consumption outside this time window. Another contribution is that the proposed clustering approach is capturing the reaction to a tariff change. When compared to a clustering method with classical features (min, max and average consumption), the improvement in the Calinski-Harabasz index was 128% for consumers associated with tariff changes

RBM3 promotes neurogenesis in a niche-dependent manner via IMP2-IGF2 signaling pathway after hypoxic-ischemic brain injury

Hypoxic ischemia (HI) is an acute brain threat across all age groups. Therapeutic hypothermia ameliorates resulting injury in neonates but its side effects prevent routine use in adults. Hypothermia up-regulates a small protein subset that includes RNA-binding motif protein 3 (RBM3), which is neuroprotective under stressful conditions. Here we show how RBM3 stimulates neuronal differentiation and inhibits HI-induced apoptosis in the two areas of persistent adult neurogenesis, the subventricular zone (SVZ) and the subgranular zone (SGZ), while promoting neural stem/progenitor cell (NSPC) proliferation after HI injury only in the SGZ. RBM3 interacts with IGF2 mRNA binding protein 2 (IMP2), elevates its expression and thereby stimulates IGF2 release in SGZ but not SVZ-NSPCs. In summary, we describe niche-dependent regulation of neurogenesis after adult HI injury via the novel RBM3-IMP2-IGF2 signaling pathway

An Enzyme- and Serum-free Neural Stem Cell Culture Model for EMT Investigation Suited for Drug Discovery

Epithelial to mesenchymal transition (EMT) describes the process of epithelium transdifferentiating into mesenchyme. EMT is a fundamental process during embryonic development that also commonly occurs in glioblastoma, the most frequent malignant brain tumor. EMT has also been observed in multiple carcinomas outside the brain including breast cancer, lung cancer, colon cancer, gastric cancer. EMT is centrally linked to malignancy by promoting migration, invasion and metastasis formation. The mechanisms of EMT induction are not fully understood. Here we describe an in vitro system for standardized isolation of cortical neural stem cells (NSCs) and subsequent EMT-induction. This system provides the flexibility to use either single cells or explant culture. In this system, rat or mouse embryonic forebrain NSCs are cultured in a defined medium, devoid of serum and enzymes. The NSCs expressed Olig2 and Sox10, two transcription factors observed in oligodendrocyte precursor cells (OPCs). Using this system, interactions between FGF-, BMP- and TGFbeta-signaling involving Zeb1, Zeb2, and Twist2 were observed where TGFbeta-activation significantly enhanced cell migration, suggesting a synergistic BMP-/TGFbeta-interaction. The results point to a network of FGF-, BMP- and TGFbeta-signaling to be involved in EMT induction and maintenance. This model system is relevant to investigate EMT in vitro. It is cost-efficient and shows high reproducibility. It also allows for the comparison of different compounds with respect to their migration responses (quantitative distance measurement), and high-throughput screening of compounds to inhibit or enhance EMT (qualitative measurement). The model is therefore well suited to test drug libraries for substances affecting EMT