Maternal behaviours and adult offspring behavioural deficits are predicted by maternal TNFα concentration in a rat model of neurodevelopmental disorders.

Exposure to inflammatory stressors during fetal development is a major risk factor for neurodevelopmental disorders (NDDs) in adult offspring. Maternal immune activation (MIA), induced by infection, causes an acute increase in pro-inflammatory cytokines which can increase the risk for NDDs directly by inducing placental and fetal brain inflammation, or indirectly through affecting maternal care behaviours thereby affecting postnatal brain development. Which of these two potential mechanisms dominates in increasing offspring risk for NDDs remains unclear. Here, we show that acute systemic maternal inflammation induced by the viral mimetic polyinosinic:polycytidylic acid (poly I:C) on gestational day 15 of rat pregnancy affects offspring and maternal behaviour, offspring cognition, and expression of NDD-relevant genes in the offspring brain. Dams exposed to poly I:C elicited an acute increase in the pro-inflammatory cytokine tumour necrosis factor (TNF; referred to here as TNFα), which predicted disruption of key maternal care behaviours. Offspring of poly I:C-treated dams showed early behavioural and adult cognitive deficits correlated to the maternal TNFα response, but, importantly, not with altered maternal care. We also found interacting effects of sex and treatment on GABAergic gene expression and DNA methylation in these offspring in a brain region-specific manner, including increased parvalbumin expression in the female adolescent frontal cortex. We conclude that the MIA-induced elevation of TNFα in the maternal compartment affects fetal neurodevelopment leading to altered offspring behaviour and cognition. Our results suggest that a focus on prenatal pathways affecting fetal neurodevelopment would provide greater insights into the mechanisms underpinning the TNFα-mediated genesis of altered offspring behaviour and cognition following maternal inflammation.

Estimating distribution of hidden objects with drones: from tennis balls to manatees.

Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.