Induced differentiation of neural stem cells of astrocytic origin to motor neurons in the rat

Directional induction of neural stem cells, a new therapy for neurodegenerative diseases and ischemic stroke

Due to the limited capacity of the adult mammalian brain to self-repair and regenerate, neurological diseases, especially neurodegenerative disorders and stroke, characterized by irreversible cellular damage are often considered as refractory diseases. Neural stem cells (NSCs) play a unique role in the treatment of neurological diseases for their abilities to self-renew and form different neural lineage cells, such as neurons and glial cells. With the increasing understanding of neurodevelopment and advances in stem cell technology, NSCs can be obtained from different sources and directed to differentiate into a specific neural lineage cell phenotype purposefully, making it possible to replace specific cells lost in some neurological diseases, which provides new approaches to treat neurodegenerative diseases as well as stroke. In this review, we outline the advances in generating several neuronal lineage subtypes from different sources of NSCs. We further summarize the therapeutic effects and possible therapeutic mechanisms of these fated specific NSCs in neurological disease models, with special emphasis on Parkinson's disease and ischemic stroke. Finally, from the perspective of clinical translation, we compare the strengths and weaknesses of different sources of NSCs and different methods of directed differentiation, and propose future research directions for directed differentiation of NSCs in regenerative medicine.

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.

MAP2 IHC detection: a marker of antigenicity in CNS tissues

Immunohistochemistry (IHC) is used to detect antibody-specific antigens in tissues; the results depend on the ability of the primary antibodies to bind to their antigens. Therefore, results depend on the quality of preservation of the specimen. Many investigators have overcome the deleterious effects of over-fixation on the binding of primary antibodies to specimen antigens using IHC, but if the specimen is under-fixed or fixation is delayed, false negative results could be obtained despite certified laboratory practices. Microtubule-associated protein 2 (MAP2) is an abundant microtubule-associate protein that participates in the outgrowth of neuronal processes and synaptic plasticity; it is localized primarily in cell bodies and dendrites of neurons. MAP2 immunolabeling has been reported to be absent in areas of the entorhinal cortex and hippocampus of Alzheimer's disease brains that were co-localized with the dense-core type of amyloid plaques. It was hypothesized that the lack of MAP2 immunolabeling in these structures was due to the degradation of the MAP2 antigen by the neuronal proteases that were released as the neurons lysed leading to the formation of these plaques. Because MAP2 is sensitive to proteolysis, we hypothesized that changes in MAP2 immunolabeling may be correlated with the degree of fixation of central nervous system (CNS) tissues. We detected normal MAP2 immunolabeling in fixed rat brain tissues, but MAP2 immunolabeling was decreased or lost in unfixed and delayed-fixed rat brain tissues. By contrast, two ubiquitous CNS-specific markers, myelin basic protein and glial fibrillary acidic protein, were unaffected by the degree of fixation in the same tissues. Our observations suggest that preservation of various CNS-specific antigens differs with the degree of fixation and that the lack of MAP2 immunolabeling in the rat brain may indicate inadequate tissue fixation. We recommend applying MAP2 IHC for all CNS tissues as a pre-screen to assess the quality of the tissue preservation and to avoid potentially false negative IHC results.