Boland, R. | bioRxiv Science

bioRxiv2026

Pediatric traumatic brain injury elicits acute neuroinflammation and long-term changes in social, cognitive, and decision-making behaviors in male and female rats

Traumatic brain injury (TBI) is one of the leading causes of emergency room visits in children under 10. Children are potentially more vulnerable to the adverse effects of TBI, given that their brains are still developing at the time of injury. Indeed, early life TBI has been linked to cognitive, social, and mood-related impairments later in life. The neuroimmune system has been implicated in adult TBI mechanisms and plays numerous key roles in brain development, making it an interesting candidate for linking pediatric TBI and prolonged behavioral alterations. Here we establish a rat model of mild pediatric TBI to investigate the relationship between early life TBI, acute responses of neuroimmune cells, and chronic behavioral dysregulation. At postnatal day 15, which is roughly equivalent to toddler age, male and female rat pups received a TBI via lateral fluid percussion injury. At 3 days post injury, TBI increased microglia and astrocyte coverage locally in the Perilesional Cortex but not in more distant corticolimbic regions. However, the hippocampus and prefrontal cortex did exhibit increased expression of the phagocytic marker CD68 in microglia, suggesting widespread glial activation even in the absence of gross coverage change. TBI also impacted mast cells, early-response innate immune cells, increasing their number and degranulation in multiple regions. In the juvenile and early adult periods, TBI impaired cognitive function, reduced sociability, and increased avoidance, with no change in anxiety-like behavior. Later in adulthood, TBI continued to impact cognitive behavior, increasing risky decision-making and impairing optimization months after injury. Together, these results suggest that pediatric TBI causes lasting cognitive and social dysregulation, possibly via acute neuroimmune alterations following injury at a critical period of brain development.

neuroscience↗

bioRxiv2018

Deep learning image recognition enables efficient genome editing in zebrafish by automated injections

One of the most popular techniques in zebrafish research is microinjection, as it is a rapid and efficient way to genetically manipulate early developing embryos, and to introduce microbes or tracers at larval stages.\n\nHere we demonstrate the development of a machine learning software that allows for microinjection at a trained target site in zebrafish eggs at unprecedented speed. The software is based on the open-source deep-learning library Inception v3.\n\nIn a first step, the software distinguishes wells containing embryos at one-cell stage from wells to be skipped with an accuracy of 93%. A second step was developed to pinpoint the injection site. Deep learning allows to predict this location on average within 42 {micro}m to manually annotated sites. Using a Graphics Processing Unit (GPU), both steps together take less than 100 milliseconds. We first tested our system by injecting a morpholino into the middle of the yolk and found that the automated injection efficiency is as efficient as manual injection (~ 80%). Next, we tested both CRISPR/Cas9 and DNA construct injections into the zygote and obtained a comparable efficiency to that of an experienced experimentalist. Combined with a higher throughput, this results in a higher yield. Hence, the automated injection of CRISPR/Cas9 will allow high-throughput applications to knock out and knock in relevant genes to study their mechanisms or pathways of interest in diverse areas of biomedical research.

molecular biology↗