Preterm infants are especially vulnerable to infection-induced white matter injury, associated with cerebral palsy, cognitive and psychomotor impairment, and other adverse neurological outcomes. The etiology of such lesions is complex and multifactorial. Furthermore, timing and length of exposure to infection also influence neurodevelopmental outcomes. Different mechanisms have been posited to mediate the observed brain injury including microglial activation followed by subsequent release of pro-inflammatory species, glutamate-induced excitotoxicity, and vulnerability of developing oligodendrocytes to cerebral insults. The prevalence of such neurological impairments requires an urgent need for early detection and effective neuroprotective strategies. Accordingly, noninvasive methods of monitoring disease progression and therapy effectiveness are essential. While diagnostic tools using biomarkers from bodily fluids may provide useful information regarding potential risks of developing neurological diseases, the use of magnetic resonance imaging/spectroscopy has emerged as a promising candidate for such purpose. Various pharmacological agents have demonstrated protective effects in the immature brain in animal models; however, few studies have progressed to clinical trials with promising results.

Introduction: Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition segmenting 6-month-old infant magnetic resonance images, but neonatal cerebral tissue type identification is challenging given its uniquely inverted tissue contrasts. The current study aims to evaluate the two architectures to segment neonatal brain tissue types at term equivalent age. Methods: Both networks were retrained over 24 pairs of neonatal T1 and T2 data from the Developing Human Connectome Project public data set and validated on another eight pairs against ground truth. We then reported the best-performing model from training and its performance by computing the Dice similarity coefficient (DSC) for each tissue type against eight test subjects. Results: During the testing phase, among the segmentation approaches tested, the dual-modality HyperDense-Net achieved the best statistically significantly test mean DSC values, obtaining 0.94/0.95/0.92 for the tissue types and took 80 h to train and 10 min to segment, including preprocessing. The single-modality LiviaNET was better at processing T2-weighted images than processing T1-weighted images across all tissue types, achieving mean DSC values of 0.90/0.90/0.88 for gray matter, white matter, and cerebrospinal fluid, respectively, while requiring 30 h to train and 8 min to segment each brain, including preprocessing. Discussion: Our evaluation demonstrates that both neural networks can segment neonatal brains, achieving previously reported performance. Both networks will be continuously retrained over an increasingly larger repertoire of neonatal brain data and be made available through the Canadian Neonatal Brain Platform to better serve the neonatal brain imaging research community.

Printable, self-healing, stretchable, and conductive materials have tremendous potential for the fabrication of advanced electronic devices. Poly(3,4-ethylenedioxithiopene) doped with polystyrene sulfonate (PEDOT:PSS) has been the focus of extensive research due to its tunable electrical and mechanical properties. Owing to its solution-processability and self-healing ability, PEDOT:PSS is an excellent candidate for developing printable inks. In this study, we developed printable, stretchable, dry, lightly adhesive, and self-healing materials for biomedical applications. Polyurethane diol (PUD), polyethylene glycol, and sorbitol were investigated as additives for PEDOT:PSS. In this study, we identified an optimal printable mixture obtained by adding PUD to PEDOT:PSS, which improved both the mechanical and electrical properties. PUD/PEDOT:PSS free-standing films with optimized composition showed a conductivity of approximately 30 S cm⁻¹, stretchability of 30%, and Young’s modulus of 15 MPa. A low resistance change (<20%) was achieved when the strain was increased to 30%. Excellent electrical stability under cyclic mechanical strain, biocompatibility, and 100% electrical self-healing were also observed. The potential biomedical applications of this mixture were demonstrated by fabricating a printed epidermal electrode on a stretchable silicone substrate. The PUD/PEDOT:PSS electrodes displayed a skin-electrode impedance similar to commercially available ones, and successfully captured physiological signals. This study contributes to the development of improved customization and enhanced mechanical durability of soft electronic materials.

The extension of sepsis encompassing the preterm newborn’s brain is often overlooked due to technical challenges in this highly vulnerable population, yet it leads to substantial long-term neurodevelopmental disabilities. In this study, we demonstrate how neonatal neuroinflammation following postnatal E. coli lipopolysaccharide (LPS) exposure in rat pups results in persistent reduction in sialylation of cerebral glycoproteins. Male Sprague-Dawley rat pups at postnatal day 3 (P3) were injected in the corpus callosum with saline or LPS. Twenty-four hours (P4) or 21 days (P24) following injection, brains were extracted and analyzed for neuraminidase activity and expression as well as for sialylation of cerebral glycoproteins and glycolipids. At both P4 and P24, we detected a significant increase of the acidic neuraminidase activity in LPS-exposed rats. It correlated with significantly increased neuraminidase 1 (Neu1) mRNA in LPS-treated brains at P4 and with neuraminidases 1 and 4 at P24 suggesting that these enzymes were responsible for the rise of neuraminidase activity. At both P4 and P24, sialylation of N-glycans on brain glycoproteins decreased according to both mass-spectrometry analysis and lectin blotting, but the ganglioside composition remained intact. Finally, at P24, analysis of brain tissues by immunohistochemistry showed that neurons in the upper layers (II–III) of somatosensory cortex had a reduced surface content of polysialic acid. Together, our data demonstrate that neonatal LPS exposure results in specific and sustained induction of Neu1 and Neu4, causing long-lasting negative changes in sialylation of glycoproteins on brain cells. Considering the important roles played by sialoglycoproteins in CNS function, we speculate that observed re-programming of the brain sialome constitutes an important part of pathophysiological consequences in perinatal infectious exposure.