Predominant differentiation of rat fetal neural stem cells into functional oligodendrocytes in vitro

Consequences of oxygen deprivation on myelination and sex-dependent alterations

Oxygen deprivation is one of the main causes of morbidity and mortality in newborns, occurring with a higher prevalence in preterm infants, reaching 20 % to 50 % mortality in newborns in the perinatal period. When they survive, 25 % exhibit neuropsychological pathologies, such as learning difficulties, epilepsy, and cerebral palsy. White matter injury is one of the main features found in oxygen deprivation injury, which can lead to long-term functional impairments, including cognitive delay and motor deficits. The myelin sheath accounts for much of the white matter in the brain by surrounding axons and enabling the efficient conduction of action potentials. Mature oligodendrocytes, which synthesize and maintain myelination, also comprise a significant proportion of the brain's white matter. In recent years, oligodendrocytes and the myelination process have become potential therapeutic targets to minimize the effects of oxygen deprivation on the central nervous system. Moreover, evidence indicate that neuroinflammation and apoptotic pathways activated during oxygen deprivation may be influenced by sexual dimorphism. To summarize the most recent research about the impact of sexual dimorphism on the neuroinflammatory state and white matter injury after oxygen deprivation, this review presents an overview of the oligodendrocyte lineage development and myelination, the impact of oxygen deprivation and neuroinflammation on oligodendrocytes in neurodevelopmental disorders, and recent reports about sexual dimorphism regarding the neuroinflammation and white matter injury after neonatal oxygen deprivation.

Message in a Scaffold: Natural Biomaterials for Three-Dimensional (3D) Bioprinting of Human Brain Organoids

Brain organoids are invaluable tools for pathophysiological studies or drug screening, but there are still challenges to overcome in making them more reproducible and relevant. Recent advances in three-dimensional (3D) bioprinting of human neural organoids is an emerging approach that may overcome the limitations of self-organized organoids. It requires the development of optimal hydrogels, and a wealth of research has improved our knowledge about biomaterials both in terms of their intrinsic properties and their relevance on 3D culture of brain cells and tissue. Although biomaterials are rarely biologically neutral, few articles have reviewed their roles on neural cells. We here review the current knowledge on unmodified biomaterials amenable to support 3D bioprinting of neural organoids with a particular interest in their impact on cell homeostasis. Alginate is a particularly suitable bioink base for cell encapsulation. Gelatine is a valuable helper agent for 3D bioprinting due to its viscosity. Collagen, fibrin, hyaluronic acid and laminin provide biological support to adhesion, motility, differentiation or synaptogenesis and optimize the 3D culture of neural cells. Optimization of specialized hydrogels to direct differentiation of stem cells together with an increased resolution in phenotype analysis will further extend the spectrum of possible bioprinted brain disease models.

Gold Nanorod Substrate for Rat Fetal Neural Stem Cell Differentiation into Oligodendrocytes

Gold nanorods (AuNRs) have been proposed to promote stem cell differentiation in vitro and in vivo. In this study, we examined a particular type of AuNR in supporting the differentiation of rat fetal neural stem cells (NSCs) into oligodendrocytes (ODCs). AuNRs were synthesized according to the seed-mediated method resulting in nanorods with an aspect ratio of around 3 (~12 nm diameter, 36 nm length) and plasmon resonance at 520 and 780 nm, as confirmed by transmission electron microscopy (TEM) and UV-vis spectroscopy, respectively. A layer-by-layer approach was used to fabricate the AuNR substrate on the functionalized glass coverslips. NSCs were propagated for 10 days using fibroblast growth factor, platelet-derived growth-factor-supplemented culture media, and differentiated on an AuNR or poly-D-lysine (PDL)-coated surface using differentiation media containing triiodothyronine for three weeks. Results showed that NSCs survived better and differentiated faster on the AuNRs compared to the PDL surface. By week 1, almost all cells had differentiated on the AuNR substrate, whereas only ~60% differentiated on the PDL surface, with similar percentages of ODCs and astrocytes. This study indicates that functionalized AuNR substrate does promote NSC differentiation and could be a viable tool for tissue engineering to support the differentiation of stem cells.

Delving into the recent advancements of spinal cord injury treatment: a review of recent progress

Spinal cord injury (SCI) research is a very complex field lending to why reviews of SCI literatures can be beneficial to current and future researchers. This review focuses on recent articles regarding potential modalities for the treatment and management of SCI. The modalities were broken down into four categories: neuroprotection-pharmacologic, neuroprotection-non-pharmacologic, neuroregeneration-pharmacologic, neuroregeneration-non-pharmacologic. Peer-reviewed articles were found using PubMed with search terms: "spinal cord injury", "spinal cord injury neuroregeneration", "olfactory ensheathing cells spinal cord injury", "rho-rock inhibitors spinal cord injury", "neural stem cell", "scaffold", "neural stem cell transplantation", "exosomes and SCI", "epidural stimulation SCI", "brain-computer interfaces and SCI". Most recent articles spanning two years were chosen for their relevance to the categories of SCI management and treatment. There has been a plethora of pre-clinical studies completed with their results being difficult to replicate in clinical studies. Therefore, scientists should focus on understanding and applying the results of previous research to develop more efficacious preclinical studies and clinical trials.

Deep learning-based predictive identification of neural stem cell differentiation

The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in devising potential cell-based therapeutic strategies for central nervous system (CNS) diseases, however, the determination and prediction of differentiation is complex and not yet clearly established, especially at the early stage. We hypothesize that deep learning could extract minutiae from large-scale datasets, and present a deep neural network model for predictable reliable identification of NSCs fate. Remarkably, using only bright field images without artificial labelling, our model is surprisingly effective at identifying the differentiated cell types, even as early as 1 day of culture. Moreover, our approach showcases superior precision and robustness in designed independent test scenarios involving various inducers, including neurotrophins, hormones, small molecule compounds and even nanoparticles, suggesting excellent generalizability and applicability. We anticipate that our accurate and robust deep learning-based platform for NSCs differentiation identification will accelerate the progress of NSCs applications.

The differentiation of neural stem cells (NSCs) into neurons is a critical part in devising potential cell-based therapeutic strategies for central nervous system diseases but NSCs fate determination and prediction is problematic. Here, the authors present a deep neural network model for predictable reliable identification of NSCs fate.